Your country data and more on using R for SAE

Nairobi Workshop: Day 1

Ann-Kristin Kreutzmann
Josh Merfeld

August 26, 2024

Session 1: Country data in R

By you!

Welcome

  • Welcome to the first day of the workshop!
  • We are going to start with the task you were given as your pre-workshop assignment.

A quick reminder

  • What did we ask from you?

  1. Describe your country data set, e.g., number of observations and variables, content, sampling design, etc.

  2. Describe the variable of interest, e.g., distribution, missing values, outstanding observations, etc.

  3. Describe variables that you think are related to the variable of interest.

  4. Demonstrate basic visualization of the selected indicators.

Session 2: Hands-on session

Data preparation for SAE

My slides

  • Before we get into it, I have put all of my material on the web

  • You can find my slides (along with copy-pasteable code) AND the data I’m using on my GitHub repository:

Let’s get started!

  • Let’s get started with the hands-on session.

  • As a first step, I’d like to hear from all of you:

    • How much experience do you have using R?
    • This is all experience, not just with SAE

Some things to note

  • We will be using RStudio throughout the workshops
    • There are other options you are welcome to use (VS Code is the most common alternative)
  • Two general “data cleaning” pipelines:
  • We will be using the tidyverse

Getting started with RStudio

  • Let’s start by looking at the layout of RStudio.

  • For those of you with ample R experience, nothing here will be new!

Why don’t you all give it a try

  • Create a script in RStudio

  • Save that script in a specific place (folder) on your computer

    • Make sure to keep track of where you save it!
    • I create a folder for each specific project I work on
    • e.g. you could create “Nairobi Workshops” and save the script as “day1.R”

First things first: the working directory

  • The working directory is the folder that R is currently working in
    • This is where R will look for files
    • This is where R will save files
    • This is where R will create files
  • You can always write out an entire file path, but this is tedious
    • More importantly, it makes your code less reproducible since the path is specific to YOUR computer

First things first: the working directory

  • One nice thing about RStudio is that the working directory will automatically be where you open the script from
    • Let’s try this. Save your script to a folder on your computer, then open the script from that folder.
    • Let’s see if it worked!
Code 
getwd() # this command will show you your current working directory
[1] "/Users/Josh/Dropbox/Papers/UN-SAE/workshops/africa/nairobiworkshops"

First things first: the working directory

  • You can also set the working directory in RStudio
    • Session > Set Working Directory > Choose Directory (or Source File Location)
    • Give it a try and let’s see if it worked!
Code 
getwd() # this command will show you your current working directory
[1] "/Users/Josh/Dropbox/Papers/UN-SAE/workshops/africa/nairobiworkshops"

Always use the same working directory!

  • Make sure to always set the working directory to the same location when working in the same script!

  • This will avoid problems later

    • It also makes your code more reproducible (e.g. if a colleague wants to run it, you just send the entire folder and it works with no changes)

R packages

  • R is a language that is built on packages
    • Packages are collections of functions that do specific things
    • R comes with a set of “base” packages that are installed automatically
  • We are going to use one package consistently, called the “tidyverse”
    • This consists of a set of packages that are designed to work together, with data cleaning in mind

R packages

The one exception to always using a script? I install packages in the CONSOLE. You can install packages like this:

Code 
install.packages("tidyverse") # this will install the tidyverse package. Note the quotes!
  • You only need to install a package once on your computer.

R packages

The first thing you’ll do in your script is load packages. You do it like this:

Code 
'''
This script is part of the Nairobi Workshop on SAE.
Date: 26 August 2024 (written earlier!)
Author: Josh Merfeld
'''
# Load packages (libraries)
library(tidyverse)
  • Note that the first part is a comment I’ve added to the script.
    • I make a lot of comments!

Loading data

  • Let’s start by loading some data.
    • This is survey data from Tanzania (NPS 5, 2020)
    • It is a list of all individuals in all households in the survey
    • You can find this in the day1data folder in the repository

Loading data

  • Let’s start by loading some data.
    • This is survey data from Tanzania (NPS 5, 2020)
    • It is a list of all individuals in all households in the survey
    • You can find this in the day1data folder in the repository

Loading data

  • Let’s load the csv version. Tidyverse has a command for this: read_csv()

  • Note that you may have to change the path! Mine is in the day1data folder within my working directory (WD).
    • You need to point to the location of the file from your WD!

Code 
# Load packages (libraries)
library(tidyverse)
# load data
df <- read_csv("day1data/tanzanialsms.csv")

Looking at the data

  • glimpse is an easy way to look at the data:
Code 
# Load packages (libraries)
library(tidyverse)
# load data
df <- read_csv("day1data/tanzanialsms.csv")
glimpse(df)
Rows: 23,592
Columns: 46
$ interview__key <chr> "39-26-37-98", "39-26-37-98", "39-26-37-98", "39-26-37-98", "04-06-65-04", "97-90-78-65", "97-90-78-65", "97-90-78-65", "97-90-78-65", "97-90-78-65", "97-90-78-65", "69-87-77-12", "69-87-77-12", "69-87-77-12", "48-07-72-07", "48-07-72-07", "48-07-72-07", "48-07-72-07", "48-07-72-07", "48-07-72-07", "48-07-72-07", "48-07-72-07", "87-35-70-53", "87-35-70-53", "87-35-70-53", "90-92-88-29", "90-92-88-29", "90-92-88-29", "16-34-22-80", "16-34-22-80", "16-34-22-80", "16-34-22-80", "16-34-22-80", "16-34-22-80", "66-03-93-27", "66-03-93-27", "66-03-93-27", "66-03-93-27", "71-71-16-36", "71-71-16-36", "71-71-16-36", "93-03-21-31", "93-03-21-31", "93-03-21-31", "93-03-21-31", "64-95-83-64", "64-95-83-64", "64-95-83-64", "54-26-09-51", "54-26-09-51", "54-26-09-51", "54-26-09-51", "54-26-09-51", "91-42-46-84", "91-42-46-84", "91-42-46-84", "91-42-46-84", "34-08-29-97", "34-08-29-97", "34-08-29-97", "25-94-08-50", "25-94-08-50", "25-94-08-50", "42-43-09-21", "88-63-59-87", "88-63-59-87", "88-63-59-87", "88-63-59-87", "88-63-59-87", "88-63-59-87", "67-34-56-15", "67-34-56-15", "67-34-56-15", "67-34-56-15", "61-09-84-51", "61-09-84-51", "61-09-84-51", "49-38-79-42", "36-53-30-05", "36-53-30-05", "36-53-30-05", "36-53-30-05", "06-31-99-33", "06-31-99-33", "06-31-99-33", "06-31-99-33", "06-31-99-33", "98-68-74-00", "86-53-32-92", "86-53-32-92", "86-53-32-92", "59-59-99-49", "68-38-43-94", "68-38-43-94", "68-38-43-94", "68-38-43-94", "68-38-43-94", "68-38-43-94", "68-3…
$ y5_hhid        <chr> "1000-001-01", "1000-001-01", "1000-001-01", "1000-001-01", "1000-001-02", "1000-001-03", "1000-001-03", "1000-001-03", "1000-001-03", "1000-001-03", "1000-001-03", "1000-001-06", "1000-001-06", "1000-001-06", "1001-001-01", "1001-001-01", "1001-001-01", "1001-001-01", "1001-001-01", "1001-001-01", "1001-001-01", "1001-001-01", "1002-001-01", "1002-001-01", "1002-001-01", "1003-001-01", "1003-001-01", "1003-001-01", "1005-001-01", "1005-001-01", "1005-001-01", "1005-001-01", "1005-001-01", "1005-001-01", "1006-001-01", "1006-001-01", "1006-001-01", "1006-001-01", "1006-001-03", "1006-001-03", "1006-001-03", "1006-001-04", "1006-001-04", "1006-001-04", "1006-001-04", "1006-001-05", "1006-001-05", "1006-001-05", "1007-001-01", "1007-001-01", "1007-001-01", "1007-001-01", "1007-001-01", "1009-001-01", "1009-001-01", "1009-001-01", "1009-001-01", "1019-001-01", "1019-001-01", "1019-001-01", "1020-001-01", "1020-001-01", "1020-001-01", "1021-001-01", "1022-001-01", "1022-001-01", "1022-001-01", "1022-001-01", "1022-001-01", "1022-001-01", "1023-001-01", "1023-001-01", "1023-001-01", "1023-001-01", "1024-001-01", "1024-001-01", "1024-001-01", "1025-001-02", "1038-001-02", "1038-001-02", "1038-001-02", "1038-001-02", "1039-001-01", "1039-001-01", "1039-001-01", "1039-001-01", "1039-001-01", "1041-001-01", "1042-001-01", "1042-001-01", "1042-001-01", "1042-001-02", "1043-001-01", "1043-001-01", "1043-001-01", "1043-001-01", "1043-001-01", "1043-001-01", "1043…
$ y4_hhid        <chr> "1000-001", "1000-001", "1000-001", "1000-001", "1000-001", "1000-001", "1000-001", "1000-001", "1000-001", "1000-001", "1000-001", "1000-001", "1000-001", "1000-001", "1001-001", "1001-001", "1001-001", "1001-001", "1001-001", "1001-001", "1001-001", "1001-001", "1002-001", "1002-001", "1002-001", "1003-001", "1003-001", "1003-001", "1005-001", "1005-001", "1005-001", "1005-001", "1005-001", "1005-001", "1006-001", "1006-001", "1006-001", "1006-001", "1006-001", "1006-001", "1006-001", "1006-001", "1006-001", "1006-001", "1006-001", "1006-001", "1006-001", "1006-001", "1007-001", "1007-001", "1007-001", "1007-001", "1007-001", "1009-001", "1009-001", "1009-001", "1009-001", "1019-001", "1019-001", "1019-001", "1020-001", "1020-001", "1020-001", "1021-001", "1022-001", "1022-001", "1022-001", "1022-001", "1022-001", "1022-001", "1023-001", "1023-001", "1023-001", "1023-001", "1024-001", "1024-001", "1024-001", "1025-001", "1038-001", "1038-001", "1038-001", "1038-001", "1039-001", "1039-001", "1039-001", "1039-001", "1039-001", "1041-001", "1042-001", "1042-001", "1042-001", "1042-001", "1043-001", "1043-001", "1043-001", "1043-001", "1043-001", "1043-001", "1043-001", "1043-001", "1044-001", "1044-001", "1044-001", "1045-001", "1045-001", "1058-001", "1058-001", "1058-001", "1058-001", "1058-001", "1058-001", "1058-001", "1059-001", "1059-001", "1059-001", "1059-001", "1059-001", "1059-001", "1059-001", "1059-001", "1059-001", "1059-001", "1059-001",…
$ indidy5        <dbl> 1, 3, 5, 7, 1, 1, 2, 4, 6, 7, 8, 1, 2, 4, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 1, 2, 3, 1, 2, 3, 4, 5, 6, 1, 2, 6, 7, 1, 2, 3, 1, 2, 3, 4, 1, 2, 3, 1, 2, 3, 4, 5, 1, 2, 3, 4, 1, 2, 3, 1, 2, 3, 1, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 1, 2, 3, 2, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 1, 3, 4, 1, 1, 2, 3, 4, 5, 6, 10, 11, 1, 4, 5, 1, 2, 1, 2, 3, 4, 5, 6, 7, 1, 2, 6, 7, 9, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 5, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 3, 4, 1, 2, 3, 4, 1, 3, 4, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 5, 1, 2, 4, 1, 2, 4, 5, 1, 2, 3, 4, 5, 6, 1, 2, 5, 6, 7, 8, 9, 1, 2, 3, 1, 3, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 1, 2, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 5, 6, 1, 2, 3, 2, 1, 2, 4, 5, 6, 7, 1, 2, 4, 5, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 2, 3, 5, 2, 3, 4, 1, 2, 3, 6, 8, 9, 10, 11, 12, 13, 1, 2, 3, 1, 2, 4, 5, 1, 2, 3, 4, 1, 2, 3, 4, 1, 1, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 6, 7, 1, 1, 2, 3, 4, 1, 2, 3, 3, 1, 2, 1, 1, 2, 4, 5, 6, 7, 1, 2, 1, 7, 8, 9, 1, 2, 3, 4, 1, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 1, 2, 3, 4, 5, 6, 1, 2, 3, 5, 6, 1, 2, 3, 1, 2, 3, 1, 2, 3, 5, 6, 7, 8, 9, 1, 1, 2, 3, 4, 5, 6, 1, 2, 5, 7, 8, 9, 1, 2, 3, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 5, 1, 4, 5, 6, 7, 1, 2, 1, 2, 3, 4, 1, 2, 3, 4, 9, 10, 11, 1, 2, 3, 4, 1, 2, 5, 6, 7, 8, 9, …
$ hh_b01         <chr> "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL…
$ hh_b02         <chr> "male", "female", "male", "male", "male", "male", "female", "female", "male", "female", "female", "male", "female", "male", "male", "female", "male", "female", "male", "male", "female", "male", "male", "female", "female", "female", "female", "male", "male", "female", "male", "female", "male", "male", "male", "female", "male", "female", "male", "female", "male", "male", "female", "male", "female", "male", "female", "male", "male", "female", "female", "female", "male", "male", "female", "male", "female", "female", "female", "female", "male", "female", "male", "male", "male", "female", "male", "female", "male", "male", "male", "female", "female", "male", "male", "female", "female", "female", "female", "male", "male", "female", "male", "female", "male", "male", "male", "male", "male", "female", "male", "female", "male", "female", "female", "female", "male", "male", "female", "female", "male", "female", "male", "male", "male", "male", "female", "male", "female", "female", "male", "male", "male", "female", "male", "female", "male", "female", "female", "female", "male", "female", "female", "male", "male", "female", "female", "female", "female", "male", "female", "female", "female", "female", "male", "male", "female", "female", "male", "male", "male", "female", "female", "female", "male", "female", "female", "male", "female", "male", "female", "female", "male", "male", "female", "male", "male", "female", "female", "male", "female", "male", "male", "male", "ma…
$ hh_b03_1       <chr> "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL…
$ hh_b03_2       <chr> "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL…
$ hh_b04         <dbl> 74, 44, 35, 9, 47, 36, 42, 21, 1, 1, 6, 32, 32, 2, 48, 45, 23, 21, 17, 14, 8, 2, 79, 71, 34, 63, 41, 22, 44, 35, 12, 10, 6, 3, 59, 52, 16, 14, 31, 27, 3, 28, 25, 6, 1, 42, 26, 2, 29, 28, 7, 4, 2, 42, 32, 11, 6, 37, 16, 3, 45, 36, 7, 33, 40, 34, 14, 11, 4, 0, 34, 29, 6, 3, 36, 28, 2, 43, 33, 14, 11, 8, 38, 40, 14, 7, 15, 76, 35, 29, 3, 27, 44, 44, 20, 18, 10, 9, 5, 3, 47, 15, 13, 57, 35, 33, 30, 7, 6, 4, 2, 0, 57, 53, 25, 25, 7, 14, 5, 3, 1, 18, 34, 10, 7, 5, 1, 42, 14, 11, 22, 19, 3, 1, 7, 5, 0, 3, 3, 4, 26, 25, 21, 55, 22, 17, 15, 13, 9, 7, 5, 3, 1, 55, 50, 14, 27, 21, 4, 1, 49, 10, 8, 5, 66, 35, 17, 13, 9, 7, 5, 2, 62, 59, 39, 17, 15, 12, 9, 35, 2, 6, 7, 5, 6, 39, 6, 2, 46, 29, 7, 5, 46, 22, 18, 13, 32, 3, 42, 36, 14, 17, 11, 6, 1, 54, 48, 22, 20, 17, 13, 9, 37, 26, 10, 8, 7, 4, 1, 42, 41, 10, 6, 2, 67, 38, 33, 52, 32, 21, 0, 46, 20, 12, 8, 6, 2, 61, 40, 12, 11, 8, 2, 0, 30, 20, 0, 38, 20, 15, 13, 10, 7, 10, 5, 2, 56, 22, 1, 25, 23, 32, 12, 8, 7, 5, 3, 1, 25, 6, 4, 2, 36, 13, 10, 7, 6, 4, 1, 31, 11, 9, 9, 7, 3, 30, 27, 7, 26, 47, 42, 13, 11, 8, 5, 71, 70, 50, 15, 28, 23, 18, 8, 36, 52, 44, 22, 9, 17, 45, 38, 14, 8, 41, 16, 25, 64, 57, 36, 24, 38, 28, 29, 3, 2, 35, 41, 38, 20, 48, 43, 19, 16, 28, 23, 6, 3, 54, 34, 15, 11, 63, 72, 38, 37, 8, 19, 5, 45, 36, 13, 9, 78, 40, 35, 47, 49, 37, 17, 9, 58, 31, 19, 31, 42, 15, 46, 55, 74, 28, 8, 16, 3, 32, 1, 66, 30, 4, 17, 34, 33, 4, 2, 32, 29, 35, 64, 53, 9, 4, 2, 48, 40, 18, 10, 51, 39, 21, 17, 14, 5, 44, 38…
$ hh_b05         <chr> "head", "SON/DAUGHTER", "SON/DAUGHTER", "grandchild", "head", "head", "spouse", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "grandchild", "head", "spouse", "SON/DAUGHTER", "head", "spouse", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "head", "spouse", "SON/DAUGHTER", "head", "SON/DAUGHTER", "SON/DAUGHTER", "head", "spouse", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "head", "spouse", "SON/DAUGHTER", "SON/DAUGHTER", "head", "spouse", "SON/DAUGHTER", "head", "spouse", "SON/DAUGHTER", "SON/DAUGHTER", "head", "spouse", "SON/DAUGHTER", "head", "spouse", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "head", "spouse", "SON/DAUGHTER", "SON/DAUGHTER", "head", "SON/DAUGHTER", "SON/DAUGHTER", "head", "spouse", "SON/DAUGHTER", "head", "head", "spouse", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "head", "spouse", "SON/DAUGHTER", "SON/DAUGHTER", "head", "spouse", "SON/DAUGHTER", "head", "head", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "head", "spouse", "SON/DAUGHTER", "SON/DAUGHTER", "OTHER RELATIVE (SPECIFY)", "head", "head", "spouse", "SON/DAUGHTER", "head", "head", "spouse", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "head", "SON/DAUGHTER", "SON/DAUGHTER", "head", "OTHER NON- RELATIVES (SPECIFY)", "head", "spouse", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "head", "sp…
$ hh_b06         <chr> "1", "3", "5", "NOT PREVIOUSLY PRESENT", "2", "4", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "6", "NOT PREVIOUSLY PRESENT", "1", "2", "3", "4", "5", "6", "7", "NOT PREVIOUSLY PRESENT", "1", "2", "3", "1", "2", "3", "1", "2", "3", "4", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "1", "2", "6", "7", "3", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "4", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "5", "NOT PREVIOUSLY PRESENT", "1", "2", "3", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "1", "2", "3", "NOT PREVIOUSLY PRESENT", "1", "2", "NOT PREVIOUSLY PRESENT", "1", "2", "3", "1", "1", "2", "3", "4", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "1", "2", "3", "NOT PREVIOUSLY PRESENT", "1", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "2", "2", "3", "4", "5", "1", "2", "3", "4", "NOT PREVIOUSLY PRESENT", "1", "1", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "2", "1", "2", "3", "4", "5", "6", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "1", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "1", "NOT PREVIOUSLY PRESENT", "1", "2", "6", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "1", "2", "6", "7", "8", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRE…
$ hh_b07         <chr> "yes", "yes", "no", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "no", "yes", "yes", "yes", "yes", "yes", "yes", "no", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "no", "no", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "no", "yes", "yes", "yes", "yes", "yes", "yes", "no", "no", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "no", "yes", "no", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "no", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "no", "yes", "yes", "no", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "no", "no", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes",…
$ hh_b08         <dbl> 31, 31, 0, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 0, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 30, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 8, 31, 31, 14, 31, 31, 31, 31, 0, 31, 0, 0, 31, 31, 31, 20, 30, 30, 30, 30, 30, 30, 30, 30, 30, 28, 31, 31, 31, 31, 31, 31, 30, 30, 30, 30, 30, 27, 30, 30, 30, 30, 0, 30, 30, 30, 30, 30, 30, 0, 0, 30, 30, 30, 30, 27, 7, 30, 30, 30, 0, 30, 30, 30, 30, 30, 0, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 20, 30, 30, 30, 30, 30, 30, 30, 0, 30, 30, 14, 31, 31, 31, 31, 31, 31, 31, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 31, 31, 31, 31, 31, 31, 31, 31, 31, 0, 0, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 4, 31, 31, 31, 31, 31, 31, 31, 31, 0, 14, 14, 31, 31, 31, 31, 31, 31, 0, 31, 31, 31, 31, 31, 31, 10, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 3, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 30, 0, 30, 8, 30, 30, 30, 31, 31, 31, 31, 31, 31, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 0, 30, 30, 30, 2, 30, 30, 30, 30, 30, 30, 30, 30, 31, 30, 30, 24, 30, 30, 30, 30, 30, 0, 30, 30, 30, 31, 30, 18, 31, 31, 31, 18, 18, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 30, 30, 30, 31, 30, 30, 31, 25, 25, 25, 31, 31, 25, 31, 31,…
$ hh_b09_1       <chr> "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "no", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes",…
$ hh_b0a         <chr> "yes", "yes", "no", "no", "yes", "yes", "yes", "yes", "yes", "no", "yes", "no", "yes", "no", "yes", "yes", "no", NA, "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "no", "yes", "yes", "yes", "no", "no", "no", "no", "yes", "yes", "no", "no", "yes", "yes", "no", "yes", "yes", "no", "no", "yes", "yes", "no", "yes", "yes", "no", "no", "no", "yes", "yes", "no", "no", "yes", "yes", "no", "yes", "no", "no", "yes", "no", "yes", "yes", "no", "no", "no", "yes", "yes", "no", "no", "yes", "yes", "no", "yes", "yes", "no", "no", "no", "yes", "yes", "no", "no", "no", "yes", "yes", "yes", "no", "yes", "no", "yes", "no", "no", "no", "no", "no", "no", "yes", "no", "no", "yes", "yes", "no", "yes", "no", "no", "no", "no", "no", "yes", "yes", "yes", "yes", "yes", "no", "no", "no", "no", "yes", "yes", "no", "no", "no", "no", "yes", "no", "no", "yes", "no", "no", "no", "no", "no", "no", "no", "no", "no", "yes", "yes", "yes", "no", "yes", "no", "no", "no", "no", "no", "no", "no", "no", "no", "yes", "yes", "yes", "yes", "no", "no", "yes", "no", "no", "no", "no", "yes", "no", "no", "no", "no", "no", "no", "yes", "yes", "yes", "no", "no", "no", "no", "yes", "no", "no", "no", "no", "no", "yes", "no", "no", "yes", "yes", "no", "no", "yes", "yes", "no", "no", "yes", "no", "no", "yes", "yes", "yes", "no", "no", "no", "yes", "yes", "yes", "no", "no", "yes", "no", "no", "yes", "yes", "no", "no", "no", "no", "no", "yes", "no", "no", "no", "yes", "yes", "yes", "yes", "no", "ye…
$ hh_b0b         <dbl> NA, NA, 3, 3, NA, NA, NA, NA, NA, 1, NA, 2, NA, 2, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, 3, NA, NA, NA, 1, 2, 2, 2, NA, NA, 1, 1, NA, NA, 2, NA, NA, 2, 2, NA, NA, 2, NA, NA, 2, 2, 2, NA, NA, 2, 2, NA, NA, 1, NA, 1, 1, NA, 2, NA, NA, 2, 2, 2, NA, NA, 2, 2, NA, NA, 2, NA, NA, 2, 2, 2, NA, NA, 1, 1, 1, NA, NA, NA, 3, NA, 2, NA, 1, 2, 2, 2, 2, 2, NA, 1, 1, NA, NA, 2, NA, 2, 2, 2, 2, 2, NA, NA, NA, NA, NA, 1, 1, 1, 1, NA, NA, 1, 1, 1, 6, NA, 1, 1, NA, 1, 1, 1, 1, 1, 1, 1, 1, 1, NA, NA, NA, 1, NA, 1, 1, 1, 1, 1, 1, 1, 1, 2, NA, NA, NA, NA, 2, 2, NA, 5, 5, 5, 2, NA, 2, 2, 2, 2, 2, 2, NA, NA, NA, 1, 1, 1, 1, NA, 8, 8, 8, 8, 1, NA, 1, 1, NA, NA, 1, 1, NA, NA, 6, 6, NA, 6, 2, NA, NA, NA, 2, 2, 2, NA, NA, NA, 1, 2, NA, 1, 2, NA, NA, 2, 2, 2, 2, 2, NA, 2, 2, 2, NA, NA, NA, NA, 1, NA, 2, NA, 1, 1, 1, 1, 1, 2, NA, 2, 2, 2, 2, 2, NA, NA, 2, NA, NA, 3, 3, 3, 3, 3, 3, 3, NA, NA, 1, NA, NA, NA, 1, 1, 1, 1, 1, 1, NA, 1, 1, 1, NA, 1, 1, 1, 1, 1, 1, NA, 1, 1, 1, NA, 1, 2, NA, 2, NA, NA, NA, 2, 2, 2, 2, NA, NA, NA, NA, 6, 6, NA, 6, NA, 6, 6, 6, 6, 6, 6, NA, 2, 2, NA, 2, 3, NA, NA, NA, NA, 6, 6, 6, 6, 6, NA, NA, NA, NA, 2, NA, 2, 2, NA, NA, 1, 1, NA, NA, 2, 2, NA, NA, 2, NA, 2, 2, 2, NA, NA, NA, 2, NA, 2, NA, NA, NA, NA, 1, 1, NA, 1, 1, NA, NA, 1, NA, NA, 1, NA, 1, 1, 4, NA, 1, NA, NA, 1, 1, NA, NA, 2, 2, NA, 2, NA, 2, 2, 2, 2, 2, NA, 1, 1, 1, NA, NA, 1, NA, NA, 1, 3, NA, NA, NA, NA, 2, NA, 2, NA, 1, 1, NA, NA, NA, 2, NA, NA, 3, 3, NA, NA, NA, NA, 1, 1, 1, 2, NA, 2…
$ hh_b10         <dbl> 0, 0, 4, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 8, 8, 2, 0, 2, 3, 0, 0, 11, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 12, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 10, 10, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 11, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 2, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 10, 0, 0, 7, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, NA, 0, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 7, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 10, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 12, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 7, 0, 0, 0, 0, 0, 10, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 8, 0, 0, 9, 0, 0, 0, 0, 0, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 5, 0, 7, 0, 1, 0, 3, 0, 0, 0, NA, 0, 0, 2, 1, 1, 0, 1, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0…
$ hh_b11         <chr> "AGRICULTURE / LIVESTOCK", "AGRICULTURE / LIVESTOCK", "PRIVATE SECTOR", "student", "AGRICULTURE / LIVESTOCK", "EMPLOYED (NOT AG): WITHOUT EMPLOYEES", "UNPAID FAMILY WORK", "NO JOB", "TOO YOUNG", "TOO YOUNG", "student", "PRIVATE SECTOR", "PRIVATE SECTOR", "TOO YOUNG", "AGRICULTURE / LIVESTOCK", "AGRICULTURE / LIVESTOCK", "UNPAID FAMILY WORK", NA, "NO JOB", "NO JOB", "student", "TOO YOUNG", "AGRICULTURE / LIVESTOCK", "AGRICULTURE / LIVESTOCK", "AGRICULTURE / LIVESTOCK", "AGRICULTURE / LIVESTOCK", "AGRICULTURE / LIVESTOCK", "AGRICULTURE / LIVESTOCK", "AGRICULTURE / LIVESTOCK", "EMPLOYED (NOT AG): WITHOUT EMPLOYEES", "student", "student", "student", "TOO YOUNG", "AGRICULTURE / LIVESTOCK", "UNPAID FAMILY WORK", "student", "student", "PRIVATE SECTOR", "EMPLOYED (NOT AG): WITHOUT EMPLOYEES", "TOO YOUNG", "EMPLOYED (NOT AG): WITHOUT EMPLOYEES", "UNPAID FAMILY WORK", "TOO YOUNG", "TOO YOUNG", "PRIVATE SECTOR", "UNPAID FAMILY WORK", "TOO YOUNG", "AGRICULTURE / LIVESTOCK", "AGRICULTURE / LIVESTOCK", "student", "TOO YOUNG", "TOO YOUNG", "AGRICULTURE / LIVESTOCK", "AGRICULTURE / LIVESTOCK", "student", "student", "NO JOB", "student", "TOO YOUNG", "EMPLOYED (NOT AG): WITHOUT EMPLOYEES", "EMPLOYED (NOT AG): WITHOUT EMPLOYEES", "student", "EMPLOYED (NOT AG): WITH EMPLOYEES", "tourism", "EMPLOYED (NOT AG): WITHOUT EMPLOYEES", "student", "student", "TOO YOUNG", "TOO YOUNG", "EMPLOYED (NOT AG): WITHOUT EMPLOYEES", "NO JOB", "student", "TOO YOUNG", "PRIVATE SECTOR", "PRIV…
$ hh_b12_1       <chr> "dead", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "dead", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "dead", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", NA, "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "dead", "dead", "MEMBER OF THE HOUSEHOLD", "dead", "dead", "dead", "dead", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "dead", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "dead", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "dead", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "dead", "LIVING OUTSIDE THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "dead", "LIVING OUTSIDE THE HO…
$ hh_b12_2       <dbl> NA, 1, 1, 5, NA, NA, NA, NA, 1, 1, NA, NA, NA, 1, NA, NA, 1, NA, 1, 1, 1, 1, NA, NA, 1, NA, NA, NA, NA, NA, 1, 1, 1, 1, NA, NA, 1, 1, NA, NA, 1, NA, NA, 1, 1, NA, NA, 1, NA, NA, 1, 1, 1, NA, NA, 1, 1, NA, NA, NA, NA, NA, 1, NA, NA, NA, 1, 1, 1, 1, NA, NA, 1, 1, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, 1, 1, NA, NA, NA, NA, 1, NA, NA, NA, 1, 1, 1, 1, 1, 1, NA, 1, 1, NA, NA, NA, NA, 1, 1, 1, 1, 1, NA, NA, 1, NA, 6, NA, 6, 6, 1, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, 1, 1, 1, NA, NA, 1, NA, NA, 1, 1, NA, NA, NA, NA, NA, NA, 1, 1, 1, 1, 1, 1, NA, NA, 1, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, 1, NA, 1, 1, 1, NA, 1, NA, NA, 1, 1, 1, 1, 1, NA, NA, 1, 1, 1, 1, 1, NA, NA, 1, 1, 1, 1, 1, NA, NA, 1, 1, 1, NA, NA, NA, NA, NA, NA, 2, NA, NA, NA, NA, NA, NA, NA, NA, 1, 1, 1, 1, 1, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, 1, 1, 1, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 8, 12, 12, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 3, NA, NA, NA, NA, 1, NA, NA, 1, 1, NA, NA, 1, 1, NA, NA, NA, NA, NA, NA, NA, NA, 1, 1, NA, NA, 5, NA, NA, NA, 5, 5, NA, NA, NA, 1, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, 1, NA, NA, 3, NA, NA, NA, 1, 1, NA, NA, 1, 1, NA, NA, 1, 1, 1, 1, NA, N…
$ hh_b13         <dbl> 63, NA, NA, NA, NA, NA, 21, NA, NA, NA, NA, NA, NA, NA, 27, NA, NA, NA, NA, NA, NA, NA, 35, 30, NA, 10, 40, 20, 43, NA, NA, NA, NA, NA, 45, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 17, NA, NA, NA, NA, NA, 31, NA, NA, 6, NA, NA, 19, NA, NA, 26, 34, 9, NA, NA, NA, NA, 11, NA, NA, NA, 27, NA, NA, 32, 24, NA, NA, NA, NA, 28, NA, NA, NA, 57, NA, NA, NA, NA, 4, NA, NA, NA, NA, NA, NA, NA, 14, NA, NA, 30, NA, NA, 5, NA, NA, NA, NA, NA, 52, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 29, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 50, NA, NA, 15, NA, NA, NA, 36, 9, 7, 4, 40, NA, NA, NA, NA, NA, NA, NA, 47, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 27, NA, NA, NA, 25, NA, NA, 20, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 35, 26, NA, NA, NA, NA, NA, NA, 23, NA, NA, NA, NA, NA, 32, NA, NA, NA, NA, 42, 27, 22, 1, NA, NA, NA, NA, 18, 9, 6, 3, 0, 55, 1, NA, NA, NA, NA, NA, NA, NA, NA, 35, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 3, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 12, NA, NA, 5, 22, 31, NA, NA, NA, NA, 52, 3, 16, NA, NA, NA, NA, NA, 31, 47, 39, NA, NA, NA, 40, 22, NA, NA, 16, 12, 21, 31, 27, NA, NA, NA, NA, 10, NA, NA, 8, 28, NA, NA, 29, 27, NA, NA, NA, NA, NA, NA, 25, 12, NA, NA, 41, 47, NA, NA, NA, NA, NA, NA, NA, NA, NA, 30, NA, NA, NA, 6, 9, NA, NA, 45, 17, 5, NA, NA, 14, 18, 18, 58, NA, NA, 5, NA, NA, N…
$ hh_b14         <chr> "NO SCHOOL", NA, NA, NA, "SOME PRIMARY", "SOME PRIMARY", "SOME PRIMARY", "DOES NOT KNOW", NA, NA, "DOES NOT KNOW", "DOES NOT KNOW", "SOME PRIMARY", NA, "NO SCHOOL", "SOME PRIMARY", NA, NA, NA, NA, NA, NA, "DOES NOT KNOW", "NO SCHOOL", NA, "NO SCHOOL", "NO SCHOOL", "NO SCHOOL", "NO SCHOOL", "COMPLETED PRIMARY", NA, NA, NA, NA, "SOME PRIMARY", "COMPLETED PRIMARY", NA, NA, "DOES NOT KNOW", "COMPLETED PRIMARY", NA, "COMPLETED PRIMARY", "ADULT EDUCATION / ELIMU YA WATU WAZIMA", NA, NA, "NO SCHOOL", "COMPLETED PRIMARY", NA, "DOES NOT KNOW", "COMPLETED PRIMARY", NA, NA, NA, "COMPLETED PRIMARY", "DOES NOT KNOW", NA, NA, "COMPLETED PRIMARY", "COMPLETED PRIMARY", "COMPLETED PRIMARY", "COMPLETED PRIMARY", "COMPLETED PRIMARY", NA, "COMPLETED PRIMARY", "COMPLETED PRIMARY", "COMPLETED PRIMARY", NA, NA, NA, NA, "DOES NOT KNOW", "DOES NOT KNOW", NA, NA, "COMPLETED SECONDARY", "COMPLETED PRIMARY", NA, "COMPLETED PRIMARY", "COMPLETED PRIMARY", "COMPLETED PRIMARY", "COMPLETED PRIMARY", "COMPLETED PRIMARY", "COMPLETED PRIMARY", "COMPLETED PRIMARY", NA, NA, "DOES NOT KNOW", "COMPLETED PRIMARY", "COMPLETED PRIMARY", "SOME PRIMARY", NA, "COMPLETED PRIMARY", "DOES NOT KNOW", "NO SCHOOL", NA, NA, NA, NA, NA, NA, "SOME PRIMARY", NA, NA, "NO SCHOOL", "COMPLETED SECONDARY", "COMPLETED PRIMARY", "COMPLETED PRIMARY", NA, NA, NA, NA, NA, "NO SCHOOL", "SOME PRIMARY", NA, "NO SCHOOL", NA, "COMPLETED PRIMARY", NA, NA, NA, "COMPLETED PRIMARY", NA, "COMPLETED PRIMARY", "COMPLETED PRIMAR…
$ hh_b15_1       <chr> "dead", "dead", "dead", "LIVING OUTSIDE THE HOUSEHOLD", "dead", "dead", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "dead", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", NA, "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "dead", "dead", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "dead", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "dead", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHO…
$ hh_b15_2       <dbl> NA, NA, NA, NA, NA, NA, NA, 2, 2, 2, NA, NA, NA, 2, NA, NA, 2, NA, 2, 2, 2, 2, NA, NA, 2, NA, 1, 1, NA, NA, 2, 2, 2, 2, NA, NA, 2, 2, NA, NA, 2, NA, NA, 2, 2, NA, NA, 2, NA, NA, 2, 2, 2, NA, NA, 2, 2, NA, 1, 1, NA, NA, 2, NA, NA, NA, 2, 2, 2, 2, NA, NA, 2, 2, NA, NA, 2, NA, NA, 2, 2, 2, NA, NA, 2, 2, NA, NA, NA, NA, 3, NA, NA, NA, 2, 2, 2, 2, 2, 2, NA, NA, NA, NA, NA, NA, NA, 2, 2, 2, 2, 2, NA, NA, 2, NA, 7, NA, 7, 2, 2, NA, 2, 21, 21, 21, 21, NA, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 5, 5, 4, NA, NA, NA, 4, 4, 4, 4, NA, 2, 2, 2, 2, NA, NA, 2, NA, NA, 2, 2, NA, 5, 5, 5, NA, NA, 2, 2, 2, 2, 2, 2, NA, NA, 2, 3, 3, 3, 3, 2, 8, 8, 3, 3, NA, NA, 1, 1, NA, NA, 2, 2, NA, NA, NA, NA, NA, 6, NA, NA, 2, 2, 2, 2, 2, NA, NA, 2, 2, 2, 2, 2, NA, NA, 2, 2, 2, 2, 2, NA, NA, 2, 2, 2, NA, 1, 1, NA, 1, NA, 4, NA, 1, 1, 1, 1, 1, NA, NA, 2, 2, 2, 2, 2, NA, NA, 2, NA, 1, 1, 1, 1, 1, 1, 1, 1, NA, NA, 2, NA, NA, NA, 1, 1, 1, 1, 1, 1, NA, 1, 1, 1, NA, 1, 1, 1, 1, 1, 1, NA, 1, 1, 1, NA, 1, NA, NA, 2, NA, NA, NA, 2, 2, 2, 2, NA, NA, NA, 4, NA, NA, 6, 3, NA, NA, NA, NA, NA, NA, NA, NA, 2, 2, NA, 2, 2, NA, NA, NA, NA, NA, NA, NA, 9, 8, NA, NA, NA, 2, NA, NA, 2, 2, NA, NA, 2, 2, NA, NA, 2, 2, NA, NA, NA, NA, 2, 2, NA, NA, NA, 2, 2, NA, NA, NA, NA, NA, NA, 2, 2, NA, 1, 1, NA, NA, 1, NA, 2, NA, NA, NA, NA, 4, NA, 1, NA, 1, 7, NA, NA, NA, 2, 2, NA, NA, 4, NA, NA, 2, 2, 2, NA, NA, 2, 2, NA, NA, 2, 2, 2, 2, NA, NA, NA, 2, NA, NA, NA, 2, NA, 1, 1, NA, NA, 2, 2, 2, 2, 3, 3, NA, NA, NA, 2, 2, 2, …
$ hh_b16         <dbl> 56, 20, 12, NA, 20, 17, NA, NA, NA, NA, NA, NA, 13, NA, NA, NA, NA, NA, NA, NA, NA, NA, 43, 26, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 28, NA, NA, NA, NA, NA, NA, NA, 38, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 20, NA, NA, NA, NA, NA, NA, 36, 8, NA, NA, NA, NA, 39, NA, NA, 12, 2, 22, NA, NA, NA, 35, 38, NA, NA, NA, NA, NA, NA, NA, NA, NA, 55, 27, 26, 6, NA, NA, NA, NA, NA, NA, 47, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 29, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 59, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 16, 4, NA, NA, 18, 17, 13, 8, NA, NA, NA, NA, NA, NA, NA, NA, NA, 49, 37, NA, NA, NA, NA, NA, NA, 23, NA, NA, NA, NA, NA, NA, 30, NA, NA, NA, 55, NA, NA, 48, NA, NA, NA, NA, NA, NA, NA, NA, NA, 59, NA, NA, NA, NA, NA, NA, NA, NA, NA, 18, NA, NA, NA, NA, NA, NA, NA, NA, 34, NA, NA, NA, NA, 27, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 34, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 28, NA, NA, 18, NA, 37, NA, NA, NA, NA, 50, 69, 48, NA, NA, NA, NA, NA, 35, 51, 43, NA, NA, NA, 44, 17, NA, NA, 31, NA, NA, 30, 22, NA, NA, NA, NA, NA, NA, NA, NA, 38, 32, NA, 46, NA, NA, NA, NA, NA, NA, NA, NA, 14, NA, NA, NA, 55, NA, 19, NA, NA, NA, 42, 8, NA, NA, 60, 13, 15, NA, 35, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 54, 2, NA,…
$ hh_b17         <chr> "NO SCHOOL", "SOME PRIMARY", "SOME PRIMARY", "COMPLETED PRIMARY", "NO SCHOOL", "DON'T KNOW", "SOME PRIMARY", NA, NA, NA, "COMPLETED PRIMARY", "DON'T KNOW", "DON'T KNOW", NA, "NO SCHOOL", "COMPLETED PRIMARY", NA, NA, NA, NA, NA, NA, "NO SCHOOL", "NO SCHOOL", NA, "NO SCHOOL", NA, NA, "NO SCHOOL", "NO SCHOOL", NA, NA, NA, NA, "NO SCHOOL", "NO SCHOOL", NA, NA, "DON'T KNOW", "COMPLETED PRIMARY", NA, "COMPLETED PRIMARY", "COMPLETED PRIMARY", NA, NA, "ADULT EDUCATION / ELIMU YA WATU WAZIMA", "COMPLETED PRIMARY", NA, "ADULT EDUCATION / ELIMU YA WATU WAZIMA", "COMPLETED PRIMARY", NA, NA, NA, "COMPLETED PRIMARY", "SOME PRIMARY", NA, NA, "COMPLETED PRIMARY", NA, NA, "NO SCHOOL", "COMPLETED PRIMARY", NA, "COMPLETED PRIMARY", "COMPLETED PRIMARY", "COMPLETED SECONDARY", NA, NA, NA, NA, "DON'T KNOW", "DON'T KNOW", NA, NA, "COMPLETED PRIMARY", "COMPLETED PRIMARY", NA, "NO SCHOOL", "COMPLETED PRIMARY", NA, NA, NA, "COMPLETED PRIMARY", "COMPLETED PRIMARY", NA, NA, "DON'T KNOW", "NO SCHOOL", "COMPLETED PRIMARY", "COMPLETED PRIMARY", NA, "COMPLETED PRIMARY", "DON'T KNOW", "NO SCHOOL", NA, NA, NA, NA, NA, NA, "COMPLETED PRIMARY", "SOME PRIMARY", "SOME PRIMARY", "NO SCHOOL", "NO SCHOOL", "NO SCHOOL", "NO SCHOOL", NA, NA, NA, NA, NA, "NO SCHOOL", "NO SCHOOL", NA, "NO SCHOOL", NA, "COMPLETED PRIMARY", NA, NA, NA, "COMPLETED PRIMARY", NA, NA, NA, NA, NA, "NO SCHOOL", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "NO SCHOOL", "NO SCHOOL", "NO SCHOOL", NA, NA, NA, NA, "NO…
$ hh_b18         <chr> "yes", "yes", "yes", "no", "yes", "yes", "yes", "yes", "no", "no", "no", "yes", "yes", "no", "yes", "yes", "yes", NA, "yes", "yes", "no", "no", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "no", "no", "no", "yes", "yes", "yes", "yes", "yes", "yes", "no", "yes", "yes", "no", "no", "yes", "yes", "no", "yes", "yes", "no", "no", "no", "yes", "yes", "no", "no", "yes", "yes", "no", "yes", "yes", "no", "yes", "yes", "yes", "yes", "no", "no", "no", "yes", "yes", "no", "no", "yes", "yes", "no", "yes", "yes", "yes", "no", "no", "yes", "yes", "yes", "no", "yes", "yes", "yes", "yes", "no", "yes", "yes", "yes", "yes", "yes", "no", "no", "no", "no", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "no", "no", "no", "no", "no", "yes", "yes", "yes", "yes", "no", "yes", "no", "no", "no", "yes", "yes", "no", "no", "no", "no", "yes", "yes", "no", "yes", "yes", "no", "no", "no", "no", "no", "no", "no", "no", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "no", "no", "no", "no", "no", "yes", "yes", "yes", "yes", "yes", "no", "no", "yes", "no", "no", "no", "yes", "yes", "yes", "yes", "no", "no", "no", "no", "yes", "yes", "yes", "yes", "yes", "yes", "no", "yes", "no", "no", "no", "no", "no", "yes", "no", "no", "yes", "yes", "no", "no", "yes", "yes", "yes", "yes", "yes", "no", "yes", "yes", "yes", "yes", "no", "no", "no", "yes", "yes", "yes", "yes", "yes", "yes", "no", "yes", "yes", "no", "no", "no", "no", "no", "yes", "yes", "no", "no", "no", "yes…
$ hh_b19         <chr> "WIDOW(ER)", "divorced", "separated", NA, "NEVER MARRIED", "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", "NEVER MARRIED", NA, NA, NA, "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", NA, "POLYGAMOUS MARRIED", "MONOGAMOUS MARRIED", "NEVER MARRIED", NA, "NEVER MARRIED", "NEVER MARRIED", NA, NA, "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", "NEVER MARRIED", "WIDOW(ER)", "separated", "NEVER MARRIED", "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", "NEVER MARRIED", NA, NA, NA, "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", "NEVER MARRIED", "NEVER MARRIED", "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", NA, "LIVING TOGETHER", "LIVING TOGETHER", NA, NA, "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", NA, "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", NA, NA, NA, "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", NA, NA, "NEVER MARRIED", "NEVER MARRIED", NA, "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", NA, "separated", "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", "NEVER MARRIED", NA, NA, NA, "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", NA, NA, "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", NA, "WIDOW(ER)", "separated", "NEVER MARRIED", NA, NA, "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", "NEVER MARRIED", NA, "NEVER MARRIED", "WIDOW(ER)", "LIVING TOGETHER", "LIVING TOGETHER", NA, "divorced", "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", "NEVER MARRIED", "NEVER MARRIED", NA, NA, NA, NA, "separated", "NEVER MARRIED", "NEVER MARRIED", "MONOGAMOUS MARRIED", "NEVER MARRIED", "MONOGAMOUS MARRIED", "MONOGAMO…
$ hh_b20         <chr> NA, NA, NA, NA, NA, "NEVER MARRIED", "PREVIOUSLY DIVORCED", NA, NA, NA, NA, "NEVER MARRIED", "NEVER MARRIED", NA, "NEVER MARRIED", "NEVER MARRIED", NA, NA, NA, NA, NA, NA, "MULTIPLE PREVIOUS MARRIAGES", "PREVIOUSLY DIVORCED", NA, NA, NA, NA, "MULTIPLE PREVIOUS MARRIAGES", "PREVIOUSLY WIDOWED", NA, NA, NA, NA, "NEVER MARRIED", "NEVER MARRIED", NA, NA, "NEVER MARRIED", "NEVER MARRIED", NA, NA, NA, NA, NA, "NEVER MARRIED", "NEVER MARRIED", NA, "NEVER MARRIED", "NEVER MARRIED", NA, NA, NA, "NEVER MARRIED", "NEVER MARRIED", NA, NA, NA, NA, NA, "NEVER MARRIED", "NEVER MARRIED", NA, NA, "NEVER MARRIED", "NEVER MARRIED", NA, NA, NA, NA, "NEVER MARRIED", "NEVER MARRIED", NA, NA, "PREVIOUSLY DIVORCED", "NEVER MARRIED", NA, NA, NA, NA, NA, NA, "NEVER MARRIED", "NEVER MARRIED", NA, NA, NA, NA, NA, NA, NA, NA, "NEVER MARRIED", "NEVER MARRIED", NA, NA, NA, NA, NA, NA, NA, NA, NA, "NEVER MARRIED", NA, "NEVER MARRIED", "NEVER MARRIED", NA, NA, NA, NA, NA, "NEVER MARRIED", "NEVER MARRIED", "NEVER MARRIED", "NEVER MARRIED", NA, NA, NA, NA, NA, "NEVER MARRIED", NA, NA, NA, NA, NA, "PREVIOUSLY DIVORCED", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "MULTIPLE PREVIOUS MARRIAGES", "NEVER MARRIED", "NEVER MARRIED", "NEVER MARRIED", NA, NA, NA, NA, NA, NA, NA, NA, NA, "MULTIPLE PREVIOUS MARRIAGES", "NEVER MARRIED", NA, "NEVER MARRIED", "NEVER MARRIED", NA, NA, NA, NA, NA, NA, "MULTIPLE PREVIOUS MARRIAGES", "NEVER MARRIED", NA, NA, NA, NA, NA, NA, "NEVER MARRIED", "NEVER M…
$ hh_b21_1       <chr> NA, NA, NA, NA, NA, "religious", "religious", NA, NA, NA, NA, "religious", "traditional", NA, "religious", "religious", NA, NA, NA, NA, NA, NA, "traditional", "traditional", NA, NA, NA, NA, "religious", "religious", NA, NA, NA, NA, "religious", "religious", NA, NA, "religious", "religious", NA, NA, NA, NA, NA, "religious", "religious", NA, "traditional", "traditional", NA, NA, NA, "traditional", "traditional", NA, NA, NA, NA, NA, "religious", "religious", NA, NA, "religious", "religious", NA, NA, NA, NA, "religious", "religious", NA, NA, "religious", "religious", NA, NA, NA, NA, NA, NA, "religious", "religious", NA, NA, NA, NA, NA, NA, NA, NA, "religious", "religious", NA, NA, NA, NA, NA, NA, NA, NA, NA, "traditional", NA, "traditional", "traditional", NA, NA, NA, NA, NA, "traditional", "traditional", "traditional", "traditional", NA, NA, NA, NA, NA, "traditional", NA, NA, NA, NA, NA, "religious", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "traditional", "traditional", "traditional", "traditional", NA, NA, NA, NA, NA, NA, NA, NA, NA, "traditional", "traditional", NA, "traditional", "traditional", NA, NA, NA, NA, NA, NA, "traditional", "traditional", NA, NA, NA, NA, NA, NA, "traditional", "traditional", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "traditional", NA, NA, "traditional", "traditional", NA, NA, "religious", NA, NA, NA, "religious", NA, "religious", "religious", NA, NA, NA, NA, NA, "religious", "religious", NA, NA, NA, NA, NA, "religiou…
$ hh_b21_2       <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "traditional", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "traditional", NA, "traditional", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "traditional", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "traditional", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "traditional", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
$ hh_b21_3       <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
$ hh_b21_4       <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
$ hh_b22         <chr> NA, NA, NA, NA, NA, "yes", "yes", NA, NA, NA, NA, "yes", "yes", NA, "yes", "yes", NA, NA, NA, NA, NA, NA, "yes", "yes", NA, NA, NA, NA, "yes", "yes", NA, NA, NA, NA, "yes", "yes", NA, NA, "yes", "yes", NA, "yes", "yes", NA, NA, "yes", "yes", NA, "yes", "yes", NA, NA, NA, "yes", "yes", NA, NA, NA, NA, NA, "yes", "yes", NA, NA, "yes", "yes", NA, NA, NA, NA, "yes", "yes", NA, NA, "yes", "yes", NA, NA, NA, NA, NA, NA, "yes", "yes", NA, NA, NA, NA, "yes", "yes", NA, NA, "yes", "yes", NA, NA, NA, NA, NA, NA, NA, NA, NA, "no", NA, "yes", "yes", NA, NA, NA, NA, NA, "yes", "no", "yes", "yes", NA, NA, NA, NA, NA, "yes", NA, NA, NA, NA, NA, "no", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "yes", "yes", "yes", "no", NA, NA, NA, NA, NA, NA, NA, NA, NA, "yes", "yes", NA, "yes", "yes", NA, NA, NA, NA, NA, NA, "yes", "yes", NA, NA, NA, NA, NA, NA, "yes", "yes", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "no", NA, NA, "yes", "yes", NA, NA, "yes", NA, NA, NA, "yes", NA, "yes", "yes", NA, NA, NA, NA, NA, "yes", "yes", NA, NA, NA, NA, NA, "yes", "yes", NA, NA, NA, NA, NA, "yes", "yes", NA, NA, NA, NA, NA, NA, NA, "yes", "yes", NA, NA, NA, NA, NA, NA, NA, "yes", "yes", NA, NA, NA, NA, NA, "yes", "yes", NA, "no", NA, NA, NA, NA, NA, NA, NA, NA, "yes", "yes", NA, "yes", "yes", "no", NA, NA, NA, NA, NA, NA, "no", NA, NA, NA, "no", NA, NA, NA, NA, NA, NA, "no", NA, NA, NA, NA, NA, "yes", "yes", NA, NA, "yes", "yes", NA, NA, NA, NA, "yes", "yes", NA, NA, NA, NA, NA, NA, …
$ hh_b23_1       <dbl> NA, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, 2, 1, NA, 2, 1, NA, NA, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, 2, 1, NA, NA, 2, 1, NA, 2, 1, NA, NA, 2, 1, NA, 2, 1, NA, NA, NA, 2, 1, NA, NA, NA, NA, NA, 2, 1, NA, NA, 2, 1, NA, NA, NA, NA, 2, 1, NA, NA, 2, 1, NA, NA, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, 3, 1, NA, NA, 2, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, NA, 2, NA, 7, 6, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, 1, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, 1, NA, 2, 1, NA, NA, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, 1, NA, NA, 6, NA, NA, NA, 1, NA, 2, 1, NA, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, NA, NA, NA, 4, 2, NA, NA, NA, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, 1, NA, 2, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, 1, NA, NA, 2, 1, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, 1, 9, NA, NA, 3, NA, NA, NA, NA, 2, 1, NA, 2, 1, NA, NA, 2, 1, NA, NA, 2, NA, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, 1, NA, NA, NA, 2, 1, 4, 3, NA, NA, NA, 2, 1, NA, NA,…
$ hh_b23_2       <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 20, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 3, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
$ hh_b23_3       <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
$ hh_b23_4       <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
$ hh_b24         <chr> NA, NA, NA, NA, NA, "no", "no", NA, NA, NA, NA, "no", "no", NA, "yes", "no", NA, NA, NA, NA, NA, NA, "no", "no", NA, NA, NA, NA, "no", "no", NA, NA, NA, NA, "no", "no", NA, NA, "no", "no", NA, "no", "no", NA, NA, "no", "no", NA, "no", "no", NA, NA, NA, "no", "no", NA, NA, NA, NA, NA, "no", "no", NA, NA, "no", "no", NA, NA, NA, NA, "no", "no", NA, NA, "no", "no", NA, NA, NA, NA, NA, NA, "no", "no", NA, NA, NA, NA, "no", "no", NA, NA, "no", "no", NA, NA, NA, NA, NA, NA, NA, NA, NA, "yes", NA, "no", "no", NA, NA, NA, NA, NA, "no", "yes", "no", "no", NA, NA, NA, NA, NA, "no", NA, NA, NA, NA, NA, "yes", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "no", "no", "no", "yes", NA, NA, NA, NA, NA, NA, NA, NA, NA, "yes", "no", NA, "no", "no", NA, NA, NA, NA, NA, NA, "yes", "no", NA, NA, NA, NA, NA, NA, "no", "no", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "yes", NA, NA, "no", "no", NA, NA, "no", NA, NA, NA, "no", NA, "no", "no", NA, NA, NA, NA, NA, "no", "no", NA, NA, NA, NA, NA, "no", "no", NA, NA, NA, NA, NA, "no", "no", NA, NA, NA, NA, NA, NA, NA, "no", "no", NA, NA, NA, NA, NA, NA, NA, "no", "no", NA, NA, NA, NA, NA, "no", "no", NA, "yes", NA, NA, NA, NA, NA, NA, NA, NA, "no", "no", NA, "no", "no", "yes", NA, NA, NA, NA, NA, NA, "yes", NA, NA, NA, "yes", NA, NA, NA, NA, NA, NA, "yes", NA, NA, NA, NA, NA, "no", "no", NA, NA, "no", "no", NA, NA, NA, NA, "no", "no", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "no", "no", "no"…
$ hh_b25         <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
$ hh_b26         <chr> "60", "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", NA, "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", "2", "LIVED HERE SINCE BIRTH", NA, NA, NA, "1", "1", NA, "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", NA, "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", NA, NA, "64", "50", "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", NA, NA, NA, "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", "5", "5", NA, "LIVED HERE SINCE BIRTH", "6", NA, NA, "3", "3", NA, "LIVED HERE SINCE BIRTH", "8", NA, NA, NA, "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", NA, NA, "3", "3", NA, "2", "2", NA, "9", "11", "7", "7", NA, NA, NA, "5", "5", NA, NA, "6", "4", NA, "35", "3", "3", NA, NA, "LIVED HERE SINCE BIRTH", "15", "LIVED HERE SINCE BIRTH", NA, "3", "17", "LIVED HERE SINCE BIRTH", "4", NA, "LIVED HERE SINCE BIRTH", "14", "14", "6", "LIVED HERE SINCE BIRTH", NA, NA, NA, NA, "11", "12", "LIVED HERE SINCE BIRTH", "26", "1", "5", "5", NA, NA, NA, NA, NA, "12", "12", "12", "11", NA, "12", NA, NA, NA, "1", "2", NA, NA, NA, NA, "12", "2", NA, "3", "3", NA, NA, NA, NA, NA, NA, NA, NA, "13", "8", "0", "18", "13", "13", "13", "LIVED HERE SINCE BIRTH", NA, NA, NA, NA, NA, "24", "20", "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", "6", NA, NA, "…
$ hh_b27_2       <chr> "arusha", NA, NA, NA, NA, NA, "kilimanjaro", NA, NA, NA, NA, "arusha", "arusha", NA, NA, NA, NA, NA, NA, NA, NA, NA, "arusha", "kilimanjaro", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "arusha", "arusha", NA, NA, "kilimanjaro", NA, NA, "arusha", "arusha", NA, NA, "arusha", NA, NA, NA, NA, NA, NA, NA, "arusha", "arusha", NA, "manyara", "kilimanjaro", NA, "dodoma", "MJINI/MAGHARIBI UNGUJA", "MJINI/MAGHARIBI UNGUJA", "MJINI/MAGHARIBI UNGUJA", NA, NA, NA, "dodoma", "tanga", NA, NA, "arusha", "manyara", NA, "tanga", "singida", "singida", NA, NA, NA, "manyara", NA, NA, "manyara", "arusha", NA, "DAR ES SALAAM", NA, NA, "arusha", "arusha", "arusha", NA, NA, NA, NA, NA, "arusha", "arusha", NA, "arusha", "arusha", "arusha", "arusha", NA, NA, NA, NA, NA, "singida", "singida", "singida", "simiyu", NA, "singida", NA, NA, NA, "singida", "singida", NA, NA, NA, NA, "singida", "singida", NA, "singida", "singida", NA, NA, NA, NA, NA, NA, NA, NA, "simiyu", "arusha", "arusha", "simiyu", "simiyu", "simiyu", "simiyu", NA, NA, NA, NA, NA, NA, "simiyu", "simiyu", NA, NA, "arusha", NA, NA, "tabora", NA, NA, NA, "singida", "simiyu", NA, NA, NA, NA, NA, NA, "arusha", "arusha", "arusha", "arusha", "arusha", "arusha", NA, "singida", NA, NA, NA, NA, NA, "simiyu", NA, NA, NA, "arusha", NA, NA, NA, NA, NA, NA, "tanga", NA, NA, NA, NA, NA, NA, NA, NA, "arusha", NA, NA, NA, NA, NA, NA, "arusha", NA, NA, NA, NA, NA, NA, NA, "arusha", NA, NA, NA, NA, NA, NA, NA, NA, "arusha…
$ hh_b27_3       <chr> "meru", NA, NA, NA, NA, NA, "hai", NA, NA, NA, NA, "meru", "meru", NA, NA, NA, NA, NA, NA, NA, NA, NA, "meru", "siha", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "meru", "meru", NA, NA, "siha", NA, NA, "meru", "meru", NA, NA, "meru", NA, NA, NA, NA, NA, NA, NA, "meru", "meru", NA, "BABATI TOWN", "MOSHI RURAL", NA, "DODOMA URBAN", "mjini", "mjini", "mjini", NA, NA, NA, "chamwino", "mkinga", NA, NA, "meru", "BABATI TOWN", NA, "lushoto", "SINGIDA URBAN", "SINGIDA URBAN", NA, NA, NA, "MBULU TOWN", NA, NA, "MBULU TOWN", "ARUSHA URBAN", NA, "kigamboni", NA, NA, "ARUSHA URBAN", "ARUSHA URBAN", "ARUSHA URBAN", NA, NA, NA, NA, NA, "ARUSHA URBAN", "monduli", NA, "ARUSHA URBAN", "ARUSHA URBAN", "karatu", "karatu", NA, NA, NA, NA, NA, "mkalama", "mkalama", "mkalama", "meatu", NA, "mkalama", NA, NA, NA, "mkalama", "mkalama", NA, NA, NA, NA, "mkalama", "mkalama", NA, "mkalama", "mkalama", NA, NA, NA, NA, NA, NA, NA, NA, "meatu", "karatu", "karatu", "meatu", "meatu", "meatu", "meatu", NA, NA, NA, NA, NA, NA, "meatu", "meatu", NA, NA, "karatu", NA, NA, "nzega", NA, NA, NA, "iramba", "meatu", NA, NA, NA, NA, NA, NA, "karatu", "karatu", "karatu", "karatu", "karatu", "karatu", NA, "mkalama", NA, NA, NA, NA, NA, "meatu", NA, NA, NA, "meru", NA, NA, NA, NA, NA, NA, "handeni", NA, NA, NA, NA, NA, NA, NA, NA, "meru", NA, NA, NA, NA, NA, NA, "ARUSHA URBAN", NA, NA, NA, NA, NA, NA, NA, "ARUSHA RURAL", NA, NA, NA, NA, NA, NA, NA, NA, "ARUSHA RURAL", NA, NA, NA, NA…
$ hh_b28         <chr> "BETTER SERVICES/HOUSING", NA, NA, NA, NA, NA, "marriage", NA, NA, NA, NA, "BETTER SERVICES/HOUSING", "BETTER SERVICES/HOUSING", NA, NA, NA, NA, NA, NA, NA, NA, NA, "OTHER FAMILY REASONS", "marriage", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "BETTER SERVICES/HOUSING", "BETTER SERVICES/HOUSING", NA, NA, "marriage", NA, NA, "WORK RELATED", "marriage", NA, NA, "marriage", NA, NA, NA, NA, NA, NA, NA, "OTHER (SPECIFY)", "BETTER SERVICES/HOUSING", NA, "OTHER FAMILY REASONS", "WORK RELATED", NA, "WORK RELATED", "WORK RELATED", "OTHER FAMILY REASONS", "OTHER FAMILY REASONS", NA, NA, NA, "WORK RELATED", "marriage", NA, NA, "WORK RELATED", "marriage", NA, "SCHOOL/STUDIES", "OTHER FAMILY REASONS", "OTHER FAMILY REASONS", NA, NA, NA, "OTHER FAMILY REASONS", NA, NA, "OTHER FAMILY REASONS", "BETTER SERVICES/HOUSING", NA, "marriage", NA, NA, "BETTER SERVICES/HOUSING", "BETTER SERVICES/HOUSING", "OTHER FAMILY REASONS", NA, NA, NA, NA, NA, "BETTER SERVICES/HOUSING", "OTHER FAMILY REASONS", NA, "BETTER SERVICES/HOUSING", "BETTER SERVICES/HOUSING", "BETTER SERVICES/HOUSING", "BETTER SERVICES/HOUSING", NA, NA, NA, NA, NA, "BETTER SERVICES/HOUSING", "marriage", "OTHER FAMILY REASONS", "OTHER FAMILY REASONS", NA, "OTHER FAMILY REASONS", NA, NA, NA, "marriage", "OTHER (SPECIFY)", NA, NA, NA, NA, "marriage", "OTHER FAMILY REASONS", NA, "OTHER FAMILY REASONS", "BETTER SERVICES/HOUSING", NA, NA, NA, NA, NA, NA, NA, NA, "BETTER SERVICES/HOUSING", "marriage", "mar…
$ hh_b29_2       <chr> "arusha", NA, NA, NA, NA, NA, "kilimanjaro", NA, NA, NA, NA, "kilimanjaro", "arusha", NA, NA, NA, NA, NA, NA, NA, NA, NA, "arusha", "kilimanjaro", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "arusha", "dodoma", NA, NA, "kilimanjaro", NA, NA, "arusha", "arusha", NA, NA, "arusha", NA, NA, NA, NA, NA, NA, NA, "arusha", "arusha", NA, "manyara", "kilimanjaro", NA, "kagera", "morogoro", "mbeya", "DAR ES SALAAM", NA, NA, NA, "dodoma", "tanga", NA, NA, "iringa", "manyara", NA, "tanga", "manyara", "manyara", NA, NA, NA, "manyara", NA, NA, "manyara", "manyara", NA, "dodoma", NA, NA, "DAR ES SALAAM", "arusha", "arusha", NA, NA, NA, NA, NA, "arusha", "arusha", NA, "kilimanjaro", "kilimanjaro", "simiyu", "simiyu", NA, NA, NA, NA, NA, "simiyu", "simiyu", "simiyu", "simiyu", NA, "singida", NA, NA, NA, "singida", "simiyu", NA, NA, NA, NA, "singida", "singida", NA, "singida", "singida", NA, NA, NA, NA, NA, NA, NA, NA, "simiyu", "arusha", "arusha", "simiyu", "simiyu", "simiyu", "simiyu", NA, NA, NA, NA, NA, NA, "simiyu", "simiyu", NA, NA, "arusha", NA, NA, "tabora", NA, NA, NA, "simiyu", "simiyu", NA, NA, NA, NA, NA, NA, "simiyu", "simiyu", "simiyu", "arusha", "arusha", "arusha", NA, "simiyu", NA, NA, NA, NA, NA, "simiyu", NA, NA, NA, "arusha", NA, NA, NA, NA, NA, NA, "tanga", NA, NA, NA, NA, NA, NA, NA, NA, "arusha", NA, NA, NA, NA, NA, NA, "arusha", NA, NA, NA, NA, NA, NA, NA, "arusha", NA, NA, NA, NA, NA, NA, NA, NA, "arusha", NA, NA, NA, NA, NA, NA, NA,…
$ hh_b29_3       <chr> "meru", NA, NA, NA, NA, NA, "hai", NA, NA, NA, NA, "rombo", "meru", NA, NA, NA, NA, NA, NA, NA, NA, NA, "meru", "siha", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "meru", "kondoa", NA, NA, "siha", NA, NA, "meru", "meru", NA, NA, "meru", NA, NA, NA, NA, NA, NA, NA, "meru", "meru", NA, "BABATI TOWN", "MOSHI RURAL", NA, "BUKOBA RURAL", "MOROGORO RURAL", "chunya", "ilala", NA, NA, NA, "DODOMA URBAN", "muheza", NA, NA, "mufindi", "BABATI TOWN", NA, "lushoto", "BABATI RURAL", "BABATI TOWN", NA, NA, NA, "MBULU TOWN", NA, NA, "MBULU TOWN", "mbulu", NA, "DODOMA URBAN", NA, NA, "kinondoni", "ARUSHA URBAN", "ARUSHA URBAN", NA, NA, NA, NA, NA, "meru", "monduli", NA, "MOSHI RURAL", "MOSHI RURAL", "meatu", "meatu", NA, NA, NA, NA, NA, "meatu", "meatu", "meatu", "meatu", NA, "mkalama", NA, NA, NA, "mkalama", "meatu", NA, NA, NA, NA, "mkalama", "mkalama", NA, "mkalama", "mkalama", NA, NA, NA, NA, NA, NA, NA, NA, "meatu", "karatu", "karatu", "meatu", "meatu", "meatu", "meatu", NA, NA, NA, NA, NA, NA, "meatu", "meatu", NA, NA, "karatu", NA, NA, "nzega", NA, NA, NA, "maswa", "meatu", NA, NA, NA, NA, NA, NA, "maswa", "meatu", "meatu", "karatu", "karatu", "karatu", NA, "meatu", NA, NA, NA, NA, NA, "meatu", NA, NA, NA, "meru", NA, NA, NA, NA, NA, NA, "handeni", NA, NA, NA, NA, NA, NA, NA, NA, "meru", NA, NA, NA, NA, NA, NA, "ARUSHA URBAN", NA, NA, NA, NA, NA, NA, NA, "ARUSHA RURAL", NA, NA, NA, NA, NA, NA, NA, NA, "ARUSHA RURAL", NA, NA, NA, NA, NA, NA, NA, NA…

Data is not always in .csv files

  • Sometimes files come in other formats

  • I have uploaded a Stata file, as well (tanzanialsms.dta), in the same folder

    • To read Stata files (common with survey data), we need a different package, called haven
    • After we install it, you can load it using read_dta()

  • Give it a try. Install the package and then load the data.

Code 
# I do not need to install it because I already have it! But if you need it:
# install.packages("haven")
# Load packages (libraries)
library(tidyverse)
library(haven)
# load data
df <- read_dta("day1data/tanzanialsms.dta")

But let’s use the .csv file for now

Code 
# Load packages (libraries)
library(tidyverse)
# load data
df <- read_csv("day1data/tanzanialsms.csv")
glimpse(df)
Rows: 23,592
Columns: 46
$ interview__key <chr> "39-26-37-98", "39-26-37-98", "39-26-37-98", "39-26-37-98", "04-06-65-04", "97-90-78-65", "97-90-78-65", "97-90-78-65", "97-90-78-65", "97-90-78-65", "97-90-78-65", "69-87-77-12", "69-87-77-12", "69-87-77-12", "48-07-72-07", "48-07-72-07", "48-07-72-07", "48-07-72-07", "48-07-72-07", "48-07-72-07", "48-07-72-07", "48-07-72-07", "87-35-70-53", "87-35-70-53", "87-35-70-53", "90-92-88-29", "90-92-88-29", "90-92-88-29", "16-34-22-80", "16-34-22-80", "16-34-22-80", "16-34-22-80", "16-34-22-80", "16-34-22-80", "66-03-93-27", "66-03-93-27", "66-03-93-27", "66-03-93-27", "71-71-16-36", "71-71-16-36", "71-71-16-36", "93-03-21-31", "93-03-21-31", "93-03-21-31", "93-03-21-31", "64-95-83-64", "64-95-83-64", "64-95-83-64", "54-26-09-51", "54-26-09-51", "54-26-09-51", "54-26-09-51", "54-26-09-51", "91-42-46-84", "91-42-46-84", "91-42-46-84", "91-42-46-84", "34-08-29-97", "34-08-29-97", "34-08-29-97", "25-94-08-50", "25-94-08-50", "25-94-08-50", "42-43-09-21", "88-63-59-87", "88-63-59-87", "88-63-59-87", "88-63-59-87", "88-63-59-87", "88-63-59-87", "67-34-56-15", "67-34-56-15", "67-34-56-15", "67-34-56-15", "61-09-84-51", "61-09-84-51", "61-09-84-51", "49-38-79-42", "36-53-30-05", "36-53-30-05", "36-53-30-05", "36-53-30-05", "06-31-99-33", "06-31-99-33", "06-31-99-33", "06-31-99-33", "06-31-99-33", "98-68-74-00", "86-53-32-92", "86-53-32-92", "86-53-32-92", "59-59-99-49", "68-38-43-94", "68-38-43-94", "68-38-43-94", "68-38-43-94", "68-38-43-94", "68-38-43-94", "68-3…
$ y5_hhid        <chr> "1000-001-01", "1000-001-01", "1000-001-01", "1000-001-01", "1000-001-02", "1000-001-03", "1000-001-03", "1000-001-03", "1000-001-03", "1000-001-03", "1000-001-03", "1000-001-06", "1000-001-06", "1000-001-06", "1001-001-01", "1001-001-01", "1001-001-01", "1001-001-01", "1001-001-01", "1001-001-01", "1001-001-01", "1001-001-01", "1002-001-01", "1002-001-01", "1002-001-01", "1003-001-01", "1003-001-01", "1003-001-01", "1005-001-01", "1005-001-01", "1005-001-01", "1005-001-01", "1005-001-01", "1005-001-01", "1006-001-01", "1006-001-01", "1006-001-01", "1006-001-01", "1006-001-03", "1006-001-03", "1006-001-03", "1006-001-04", "1006-001-04", "1006-001-04", "1006-001-04", "1006-001-05", "1006-001-05", "1006-001-05", "1007-001-01", "1007-001-01", "1007-001-01", "1007-001-01", "1007-001-01", "1009-001-01", "1009-001-01", "1009-001-01", "1009-001-01", "1019-001-01", "1019-001-01", "1019-001-01", "1020-001-01", "1020-001-01", "1020-001-01", "1021-001-01", "1022-001-01", "1022-001-01", "1022-001-01", "1022-001-01", "1022-001-01", "1022-001-01", "1023-001-01", "1023-001-01", "1023-001-01", "1023-001-01", "1024-001-01", "1024-001-01", "1024-001-01", "1025-001-02", "1038-001-02", "1038-001-02", "1038-001-02", "1038-001-02", "1039-001-01", "1039-001-01", "1039-001-01", "1039-001-01", "1039-001-01", "1041-001-01", "1042-001-01", "1042-001-01", "1042-001-01", "1042-001-02", "1043-001-01", "1043-001-01", "1043-001-01", "1043-001-01", "1043-001-01", "1043-001-01", "1043…
$ y4_hhid        <chr> "1000-001", "1000-001", "1000-001", "1000-001", "1000-001", "1000-001", "1000-001", "1000-001", "1000-001", "1000-001", "1000-001", "1000-001", "1000-001", "1000-001", "1001-001", "1001-001", "1001-001", "1001-001", "1001-001", "1001-001", "1001-001", "1001-001", "1002-001", "1002-001", "1002-001", "1003-001", "1003-001", "1003-001", "1005-001", "1005-001", "1005-001", "1005-001", "1005-001", "1005-001", "1006-001", "1006-001", "1006-001", "1006-001", "1006-001", "1006-001", "1006-001", "1006-001", "1006-001", "1006-001", "1006-001", "1006-001", "1006-001", "1006-001", "1007-001", "1007-001", "1007-001", "1007-001", "1007-001", "1009-001", "1009-001", "1009-001", "1009-001", "1019-001", "1019-001", "1019-001", "1020-001", "1020-001", "1020-001", "1021-001", "1022-001", "1022-001", "1022-001", "1022-001", "1022-001", "1022-001", "1023-001", "1023-001", "1023-001", "1023-001", "1024-001", "1024-001", "1024-001", "1025-001", "1038-001", "1038-001", "1038-001", "1038-001", "1039-001", "1039-001", "1039-001", "1039-001", "1039-001", "1041-001", "1042-001", "1042-001", "1042-001", "1042-001", "1043-001", "1043-001", "1043-001", "1043-001", "1043-001", "1043-001", "1043-001", "1043-001", "1044-001", "1044-001", "1044-001", "1045-001", "1045-001", "1058-001", "1058-001", "1058-001", "1058-001", "1058-001", "1058-001", "1058-001", "1059-001", "1059-001", "1059-001", "1059-001", "1059-001", "1059-001", "1059-001", "1059-001", "1059-001", "1059-001", "1059-001",…
$ indidy5        <dbl> 1, 3, 5, 7, 1, 1, 2, 4, 6, 7, 8, 1, 2, 4, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 1, 2, 3, 1, 2, 3, 4, 5, 6, 1, 2, 6, 7, 1, 2, 3, 1, 2, 3, 4, 1, 2, 3, 1, 2, 3, 4, 5, 1, 2, 3, 4, 1, 2, 3, 1, 2, 3, 1, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 1, 2, 3, 2, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 1, 3, 4, 1, 1, 2, 3, 4, 5, 6, 10, 11, 1, 4, 5, 1, 2, 1, 2, 3, 4, 5, 6, 7, 1, 2, 6, 7, 9, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 5, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 3, 4, 1, 2, 3, 4, 1, 3, 4, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 5, 1, 2, 4, 1, 2, 4, 5, 1, 2, 3, 4, 5, 6, 1, 2, 5, 6, 7, 8, 9, 1, 2, 3, 1, 3, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 1, 2, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 5, 6, 1, 2, 3, 2, 1, 2, 4, 5, 6, 7, 1, 2, 4, 5, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 2, 3, 5, 2, 3, 4, 1, 2, 3, 6, 8, 9, 10, 11, 12, 13, 1, 2, 3, 1, 2, 4, 5, 1, 2, 3, 4, 1, 2, 3, 4, 1, 1, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 6, 7, 1, 1, 2, 3, 4, 1, 2, 3, 3, 1, 2, 1, 1, 2, 4, 5, 6, 7, 1, 2, 1, 7, 8, 9, 1, 2, 3, 4, 1, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 1, 2, 3, 4, 5, 6, 1, 2, 3, 5, 6, 1, 2, 3, 1, 2, 3, 1, 2, 3, 5, 6, 7, 8, 9, 1, 1, 2, 3, 4, 5, 6, 1, 2, 5, 7, 8, 9, 1, 2, 3, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 5, 1, 4, 5, 6, 7, 1, 2, 1, 2, 3, 4, 1, 2, 3, 4, 9, 10, 11, 1, 2, 3, 4, 1, 2, 5, 6, 7, 8, 9, …
$ hh_b01         <chr> "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL…
$ hh_b02         <chr> "male", "female", "male", "male", "male", "male", "female", "female", "male", "female", "female", "male", "female", "male", "male", "female", "male", "female", "male", "male", "female", "male", "male", "female", "female", "female", "female", "male", "male", "female", "male", "female", "male", "male", "male", "female", "male", "female", "male", "female", "male", "male", "female", "male", "female", "male", "female", "male", "male", "female", "female", "female", "male", "male", "female", "male", "female", "female", "female", "female", "male", "female", "male", "male", "male", "female", "male", "female", "male", "male", "male", "female", "female", "male", "male", "female", "female", "female", "female", "male", "male", "female", "male", "female", "male", "male", "male", "male", "male", "female", "male", "female", "male", "female", "female", "female", "male", "male", "female", "female", "male", "female", "male", "male", "male", "male", "female", "male", "female", "female", "male", "male", "male", "female", "male", "female", "male", "female", "female", "female", "male", "female", "female", "male", "male", "female", "female", "female", "female", "male", "female", "female", "female", "female", "male", "male", "female", "female", "male", "male", "male", "female", "female", "female", "male", "female", "female", "male", "female", "male", "female", "female", "male", "male", "female", "male", "male", "female", "female", "male", "female", "male", "male", "male", "ma…
$ hh_b03_1       <chr> "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL…
$ hh_b03_2       <chr> "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL**", "**CONFIDENTIAL…
$ hh_b04         <dbl> 74, 44, 35, 9, 47, 36, 42, 21, 1, 1, 6, 32, 32, 2, 48, 45, 23, 21, 17, 14, 8, 2, 79, 71, 34, 63, 41, 22, 44, 35, 12, 10, 6, 3, 59, 52, 16, 14, 31, 27, 3, 28, 25, 6, 1, 42, 26, 2, 29, 28, 7, 4, 2, 42, 32, 11, 6, 37, 16, 3, 45, 36, 7, 33, 40, 34, 14, 11, 4, 0, 34, 29, 6, 3, 36, 28, 2, 43, 33, 14, 11, 8, 38, 40, 14, 7, 15, 76, 35, 29, 3, 27, 44, 44, 20, 18, 10, 9, 5, 3, 47, 15, 13, 57, 35, 33, 30, 7, 6, 4, 2, 0, 57, 53, 25, 25, 7, 14, 5, 3, 1, 18, 34, 10, 7, 5, 1, 42, 14, 11, 22, 19, 3, 1, 7, 5, 0, 3, 3, 4, 26, 25, 21, 55, 22, 17, 15, 13, 9, 7, 5, 3, 1, 55, 50, 14, 27, 21, 4, 1, 49, 10, 8, 5, 66, 35, 17, 13, 9, 7, 5, 2, 62, 59, 39, 17, 15, 12, 9, 35, 2, 6, 7, 5, 6, 39, 6, 2, 46, 29, 7, 5, 46, 22, 18, 13, 32, 3, 42, 36, 14, 17, 11, 6, 1, 54, 48, 22, 20, 17, 13, 9, 37, 26, 10, 8, 7, 4, 1, 42, 41, 10, 6, 2, 67, 38, 33, 52, 32, 21, 0, 46, 20, 12, 8, 6, 2, 61, 40, 12, 11, 8, 2, 0, 30, 20, 0, 38, 20, 15, 13, 10, 7, 10, 5, 2, 56, 22, 1, 25, 23, 32, 12, 8, 7, 5, 3, 1, 25, 6, 4, 2, 36, 13, 10, 7, 6, 4, 1, 31, 11, 9, 9, 7, 3, 30, 27, 7, 26, 47, 42, 13, 11, 8, 5, 71, 70, 50, 15, 28, 23, 18, 8, 36, 52, 44, 22, 9, 17, 45, 38, 14, 8, 41, 16, 25, 64, 57, 36, 24, 38, 28, 29, 3, 2, 35, 41, 38, 20, 48, 43, 19, 16, 28, 23, 6, 3, 54, 34, 15, 11, 63, 72, 38, 37, 8, 19, 5, 45, 36, 13, 9, 78, 40, 35, 47, 49, 37, 17, 9, 58, 31, 19, 31, 42, 15, 46, 55, 74, 28, 8, 16, 3, 32, 1, 66, 30, 4, 17, 34, 33, 4, 2, 32, 29, 35, 64, 53, 9, 4, 2, 48, 40, 18, 10, 51, 39, 21, 17, 14, 5, 44, 38…
$ hh_b05         <chr> "head", "SON/DAUGHTER", "SON/DAUGHTER", "grandchild", "head", "head", "spouse", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "grandchild", "head", "spouse", "SON/DAUGHTER", "head", "spouse", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "head", "spouse", "SON/DAUGHTER", "head", "SON/DAUGHTER", "SON/DAUGHTER", "head", "spouse", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "head", "spouse", "SON/DAUGHTER", "SON/DAUGHTER", "head", "spouse", "SON/DAUGHTER", "head", "spouse", "SON/DAUGHTER", "SON/DAUGHTER", "head", "spouse", "SON/DAUGHTER", "head", "spouse", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "head", "spouse", "SON/DAUGHTER", "SON/DAUGHTER", "head", "SON/DAUGHTER", "SON/DAUGHTER", "head", "spouse", "SON/DAUGHTER", "head", "head", "spouse", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "head", "spouse", "SON/DAUGHTER", "SON/DAUGHTER", "head", "spouse", "SON/DAUGHTER", "head", "head", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "head", "spouse", "SON/DAUGHTER", "SON/DAUGHTER", "OTHER RELATIVE (SPECIFY)", "head", "head", "spouse", "SON/DAUGHTER", "head", "head", "spouse", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "head", "SON/DAUGHTER", "SON/DAUGHTER", "head", "OTHER NON- RELATIVES (SPECIFY)", "head", "spouse", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "SON/DAUGHTER", "head", "sp…
$ hh_b06         <chr> "1", "3", "5", "NOT PREVIOUSLY PRESENT", "2", "4", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "6", "NOT PREVIOUSLY PRESENT", "1", "2", "3", "4", "5", "6", "7", "NOT PREVIOUSLY PRESENT", "1", "2", "3", "1", "2", "3", "1", "2", "3", "4", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "1", "2", "6", "7", "3", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "4", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "5", "NOT PREVIOUSLY PRESENT", "1", "2", "3", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "1", "2", "3", "NOT PREVIOUSLY PRESENT", "1", "2", "NOT PREVIOUSLY PRESENT", "1", "2", "3", "1", "1", "2", "3", "4", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "1", "2", "3", "NOT PREVIOUSLY PRESENT", "1", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "2", "2", "3", "4", "5", "1", "2", "3", "4", "NOT PREVIOUSLY PRESENT", "1", "1", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "2", "1", "2", "3", "4", "5", "6", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "1", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "1", "NOT PREVIOUSLY PRESENT", "1", "2", "6", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "1", "2", "6", "7", "8", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRESENT", "NOT PREVIOUSLY PRE…
$ hh_b07         <chr> "yes", "yes", "no", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "no", "yes", "yes", "yes", "yes", "yes", "yes", "no", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "no", "no", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "no", "yes", "yes", "yes", "yes", "yes", "yes", "no", "no", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "no", "yes", "no", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "no", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "no", "yes", "yes", "no", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "no", "no", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes",…
$ hh_b08         <dbl> 31, 31, 0, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 0, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 30, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 8, 31, 31, 14, 31, 31, 31, 31, 0, 31, 0, 0, 31, 31, 31, 20, 30, 30, 30, 30, 30, 30, 30, 30, 30, 28, 31, 31, 31, 31, 31, 31, 30, 30, 30, 30, 30, 27, 30, 30, 30, 30, 0, 30, 30, 30, 30, 30, 30, 0, 0, 30, 30, 30, 30, 27, 7, 30, 30, 30, 0, 30, 30, 30, 30, 30, 0, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 20, 30, 30, 30, 30, 30, 30, 30, 0, 30, 30, 14, 31, 31, 31, 31, 31, 31, 31, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 31, 31, 31, 31, 31, 31, 31, 31, 31, 0, 0, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 4, 31, 31, 31, 31, 31, 31, 31, 31, 0, 14, 14, 31, 31, 31, 31, 31, 31, 0, 31, 31, 31, 31, 31, 31, 10, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 3, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 30, 0, 30, 8, 30, 30, 30, 31, 31, 31, 31, 31, 31, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 0, 30, 30, 30, 2, 30, 30, 30, 30, 30, 30, 30, 30, 31, 30, 30, 24, 30, 30, 30, 30, 30, 0, 30, 30, 30, 31, 30, 18, 31, 31, 31, 18, 18, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 30, 30, 30, 31, 30, 30, 31, 25, 25, 25, 31, 31, 25, 31, 31,…
$ hh_b09_1       <chr> "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "no", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes",…
$ hh_b0a         <chr> "yes", "yes", "no", "no", "yes", "yes", "yes", "yes", "yes", "no", "yes", "no", "yes", "no", "yes", "yes", "no", NA, "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "no", "yes", "yes", "yes", "no", "no", "no", "no", "yes", "yes", "no", "no", "yes", "yes", "no", "yes", "yes", "no", "no", "yes", "yes", "no", "yes", "yes", "no", "no", "no", "yes", "yes", "no", "no", "yes", "yes", "no", "yes", "no", "no", "yes", "no", "yes", "yes", "no", "no", "no", "yes", "yes", "no", "no", "yes", "yes", "no", "yes", "yes", "no", "no", "no", "yes", "yes", "no", "no", "no", "yes", "yes", "yes", "no", "yes", "no", "yes", "no", "no", "no", "no", "no", "no", "yes", "no", "no", "yes", "yes", "no", "yes", "no", "no", "no", "no", "no", "yes", "yes", "yes", "yes", "yes", "no", "no", "no", "no", "yes", "yes", "no", "no", "no", "no", "yes", "no", "no", "yes", "no", "no", "no", "no", "no", "no", "no", "no", "no", "yes", "yes", "yes", "no", "yes", "no", "no", "no", "no", "no", "no", "no", "no", "no", "yes", "yes", "yes", "yes", "no", "no", "yes", "no", "no", "no", "no", "yes", "no", "no", "no", "no", "no", "no", "yes", "yes", "yes", "no", "no", "no", "no", "yes", "no", "no", "no", "no", "no", "yes", "no", "no", "yes", "yes", "no", "no", "yes", "yes", "no", "no", "yes", "no", "no", "yes", "yes", "yes", "no", "no", "no", "yes", "yes", "yes", "no", "no", "yes", "no", "no", "yes", "yes", "no", "no", "no", "no", "no", "yes", "no", "no", "no", "yes", "yes", "yes", "yes", "no", "ye…
$ hh_b0b         <dbl> NA, NA, 3, 3, NA, NA, NA, NA, NA, 1, NA, 2, NA, 2, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, 3, NA, NA, NA, 1, 2, 2, 2, NA, NA, 1, 1, NA, NA, 2, NA, NA, 2, 2, NA, NA, 2, NA, NA, 2, 2, 2, NA, NA, 2, 2, NA, NA, 1, NA, 1, 1, NA, 2, NA, NA, 2, 2, 2, NA, NA, 2, 2, NA, NA, 2, NA, NA, 2, 2, 2, NA, NA, 1, 1, 1, NA, NA, NA, 3, NA, 2, NA, 1, 2, 2, 2, 2, 2, NA, 1, 1, NA, NA, 2, NA, 2, 2, 2, 2, 2, NA, NA, NA, NA, NA, 1, 1, 1, 1, NA, NA, 1, 1, 1, 6, NA, 1, 1, NA, 1, 1, 1, 1, 1, 1, 1, 1, 1, NA, NA, NA, 1, NA, 1, 1, 1, 1, 1, 1, 1, 1, 2, NA, NA, NA, NA, 2, 2, NA, 5, 5, 5, 2, NA, 2, 2, 2, 2, 2, 2, NA, NA, NA, 1, 1, 1, 1, NA, 8, 8, 8, 8, 1, NA, 1, 1, NA, NA, 1, 1, NA, NA, 6, 6, NA, 6, 2, NA, NA, NA, 2, 2, 2, NA, NA, NA, 1, 2, NA, 1, 2, NA, NA, 2, 2, 2, 2, 2, NA, 2, 2, 2, NA, NA, NA, NA, 1, NA, 2, NA, 1, 1, 1, 1, 1, 2, NA, 2, 2, 2, 2, 2, NA, NA, 2, NA, NA, 3, 3, 3, 3, 3, 3, 3, NA, NA, 1, NA, NA, NA, 1, 1, 1, 1, 1, 1, NA, 1, 1, 1, NA, 1, 1, 1, 1, 1, 1, NA, 1, 1, 1, NA, 1, 2, NA, 2, NA, NA, NA, 2, 2, 2, 2, NA, NA, NA, NA, 6, 6, NA, 6, NA, 6, 6, 6, 6, 6, 6, NA, 2, 2, NA, 2, 3, NA, NA, NA, NA, 6, 6, 6, 6, 6, NA, NA, NA, NA, 2, NA, 2, 2, NA, NA, 1, 1, NA, NA, 2, 2, NA, NA, 2, NA, 2, 2, 2, NA, NA, NA, 2, NA, 2, NA, NA, NA, NA, 1, 1, NA, 1, 1, NA, NA, 1, NA, NA, 1, NA, 1, 1, 4, NA, 1, NA, NA, 1, 1, NA, NA, 2, 2, NA, 2, NA, 2, 2, 2, 2, 2, NA, 1, 1, 1, NA, NA, 1, NA, NA, 1, 3, NA, NA, NA, NA, 2, NA, 2, NA, 1, 1, NA, NA, NA, 2, NA, NA, 3, 3, NA, NA, NA, NA, 1, 1, 1, 2, NA, 2…
$ hh_b10         <dbl> 0, 0, 4, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 8, 8, 2, 0, 2, 3, 0, 0, 11, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 12, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 8, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 10, 10, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 11, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 2, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 10, 0, 0, 7, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, NA, 0, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 7, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 5, 6, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 10, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 12, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 7, 0, 0, 0, 0, 0, 10, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 8, 0, 0, 9, 0, 0, 0, 0, 0, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 5, 0, 7, 0, 1, 0, 3, 0, 0, 0, NA, 0, 0, 2, 1, 1, 0, 1, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0…
$ hh_b11         <chr> "AGRICULTURE / LIVESTOCK", "AGRICULTURE / LIVESTOCK", "PRIVATE SECTOR", "student", "AGRICULTURE / LIVESTOCK", "EMPLOYED (NOT AG): WITHOUT EMPLOYEES", "UNPAID FAMILY WORK", "NO JOB", "TOO YOUNG", "TOO YOUNG", "student", "PRIVATE SECTOR", "PRIVATE SECTOR", "TOO YOUNG", "AGRICULTURE / LIVESTOCK", "AGRICULTURE / LIVESTOCK", "UNPAID FAMILY WORK", NA, "NO JOB", "NO JOB", "student", "TOO YOUNG", "AGRICULTURE / LIVESTOCK", "AGRICULTURE / LIVESTOCK", "AGRICULTURE / LIVESTOCK", "AGRICULTURE / LIVESTOCK", "AGRICULTURE / LIVESTOCK", "AGRICULTURE / LIVESTOCK", "AGRICULTURE / LIVESTOCK", "EMPLOYED (NOT AG): WITHOUT EMPLOYEES", "student", "student", "student", "TOO YOUNG", "AGRICULTURE / LIVESTOCK", "UNPAID FAMILY WORK", "student", "student", "PRIVATE SECTOR", "EMPLOYED (NOT AG): WITHOUT EMPLOYEES", "TOO YOUNG", "EMPLOYED (NOT AG): WITHOUT EMPLOYEES", "UNPAID FAMILY WORK", "TOO YOUNG", "TOO YOUNG", "PRIVATE SECTOR", "UNPAID FAMILY WORK", "TOO YOUNG", "AGRICULTURE / LIVESTOCK", "AGRICULTURE / LIVESTOCK", "student", "TOO YOUNG", "TOO YOUNG", "AGRICULTURE / LIVESTOCK", "AGRICULTURE / LIVESTOCK", "student", "student", "NO JOB", "student", "TOO YOUNG", "EMPLOYED (NOT AG): WITHOUT EMPLOYEES", "EMPLOYED (NOT AG): WITHOUT EMPLOYEES", "student", "EMPLOYED (NOT AG): WITH EMPLOYEES", "tourism", "EMPLOYED (NOT AG): WITHOUT EMPLOYEES", "student", "student", "TOO YOUNG", "TOO YOUNG", "EMPLOYED (NOT AG): WITHOUT EMPLOYEES", "NO JOB", "student", "TOO YOUNG", "PRIVATE SECTOR", "PRIV…
$ hh_b12_1       <chr> "dead", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "dead", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "dead", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", NA, "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "dead", "dead", "MEMBER OF THE HOUSEHOLD", "dead", "dead", "dead", "dead", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "dead", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "dead", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "dead", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "dead", "LIVING OUTSIDE THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "dead", "LIVING OUTSIDE THE HO…
$ hh_b12_2       <dbl> NA, 1, 1, 5, NA, NA, NA, NA, 1, 1, NA, NA, NA, 1, NA, NA, 1, NA, 1, 1, 1, 1, NA, NA, 1, NA, NA, NA, NA, NA, 1, 1, 1, 1, NA, NA, 1, 1, NA, NA, 1, NA, NA, 1, 1, NA, NA, 1, NA, NA, 1, 1, 1, NA, NA, 1, 1, NA, NA, NA, NA, NA, 1, NA, NA, NA, 1, 1, 1, 1, NA, NA, 1, 1, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, 1, 1, NA, NA, NA, NA, 1, NA, NA, NA, 1, 1, 1, 1, 1, 1, NA, 1, 1, NA, NA, NA, NA, 1, 1, 1, 1, 1, NA, NA, 1, NA, 6, NA, 6, 6, 1, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, 1, 1, 1, NA, NA, 1, NA, NA, 1, 1, NA, NA, NA, NA, NA, NA, 1, 1, 1, 1, 1, 1, NA, NA, 1, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, 1, NA, 1, 1, 1, NA, 1, NA, NA, 1, 1, 1, 1, 1, NA, NA, 1, 1, 1, 1, 1, NA, NA, 1, 1, 1, 1, 1, NA, NA, 1, 1, 1, NA, NA, NA, NA, NA, NA, 2, NA, NA, NA, NA, NA, NA, NA, NA, 1, 1, 1, 1, 1, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, 1, 1, 1, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 8, 12, 12, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 3, NA, NA, NA, NA, 1, NA, NA, 1, 1, NA, NA, 1, 1, NA, NA, NA, NA, NA, NA, NA, NA, 1, 1, NA, NA, 5, NA, NA, NA, 5, 5, NA, NA, NA, 1, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, 1, NA, NA, 3, NA, NA, NA, 1, 1, NA, NA, 1, 1, NA, NA, 1, 1, 1, 1, NA, N…
$ hh_b13         <dbl> 63, NA, NA, NA, NA, NA, 21, NA, NA, NA, NA, NA, NA, NA, 27, NA, NA, NA, NA, NA, NA, NA, 35, 30, NA, 10, 40, 20, 43, NA, NA, NA, NA, NA, 45, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 17, NA, NA, NA, NA, NA, 31, NA, NA, 6, NA, NA, 19, NA, NA, 26, 34, 9, NA, NA, NA, NA, 11, NA, NA, NA, 27, NA, NA, 32, 24, NA, NA, NA, NA, 28, NA, NA, NA, 57, NA, NA, NA, NA, 4, NA, NA, NA, NA, NA, NA, NA, 14, NA, NA, 30, NA, NA, 5, NA, NA, NA, NA, NA, 52, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 29, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 50, NA, NA, 15, NA, NA, NA, 36, 9, 7, 4, 40, NA, NA, NA, NA, NA, NA, NA, 47, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 27, NA, NA, NA, 25, NA, NA, 20, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 35, 26, NA, NA, NA, NA, NA, NA, 23, NA, NA, NA, NA, NA, 32, NA, NA, NA, NA, 42, 27, 22, 1, NA, NA, NA, NA, 18, 9, 6, 3, 0, 55, 1, NA, NA, NA, NA, NA, NA, NA, NA, 35, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 3, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 12, NA, NA, 5, 22, 31, NA, NA, NA, NA, 52, 3, 16, NA, NA, NA, NA, NA, 31, 47, 39, NA, NA, NA, 40, 22, NA, NA, 16, 12, 21, 31, 27, NA, NA, NA, NA, 10, NA, NA, 8, 28, NA, NA, 29, 27, NA, NA, NA, NA, NA, NA, 25, 12, NA, NA, 41, 47, NA, NA, NA, NA, NA, NA, NA, NA, NA, 30, NA, NA, NA, 6, 9, NA, NA, 45, 17, 5, NA, NA, 14, 18, 18, 58, NA, NA, 5, NA, NA, N…
$ hh_b14         <chr> "NO SCHOOL", NA, NA, NA, "SOME PRIMARY", "SOME PRIMARY", "SOME PRIMARY", "DOES NOT KNOW", NA, NA, "DOES NOT KNOW", "DOES NOT KNOW", "SOME PRIMARY", NA, "NO SCHOOL", "SOME PRIMARY", NA, NA, NA, NA, NA, NA, "DOES NOT KNOW", "NO SCHOOL", NA, "NO SCHOOL", "NO SCHOOL", "NO SCHOOL", "NO SCHOOL", "COMPLETED PRIMARY", NA, NA, NA, NA, "SOME PRIMARY", "COMPLETED PRIMARY", NA, NA, "DOES NOT KNOW", "COMPLETED PRIMARY", NA, "COMPLETED PRIMARY", "ADULT EDUCATION / ELIMU YA WATU WAZIMA", NA, NA, "NO SCHOOL", "COMPLETED PRIMARY", NA, "DOES NOT KNOW", "COMPLETED PRIMARY", NA, NA, NA, "COMPLETED PRIMARY", "DOES NOT KNOW", NA, NA, "COMPLETED PRIMARY", "COMPLETED PRIMARY", "COMPLETED PRIMARY", "COMPLETED PRIMARY", "COMPLETED PRIMARY", NA, "COMPLETED PRIMARY", "COMPLETED PRIMARY", "COMPLETED PRIMARY", NA, NA, NA, NA, "DOES NOT KNOW", "DOES NOT KNOW", NA, NA, "COMPLETED SECONDARY", "COMPLETED PRIMARY", NA, "COMPLETED PRIMARY", "COMPLETED PRIMARY", "COMPLETED PRIMARY", "COMPLETED PRIMARY", "COMPLETED PRIMARY", "COMPLETED PRIMARY", "COMPLETED PRIMARY", NA, NA, "DOES NOT KNOW", "COMPLETED PRIMARY", "COMPLETED PRIMARY", "SOME PRIMARY", NA, "COMPLETED PRIMARY", "DOES NOT KNOW", "NO SCHOOL", NA, NA, NA, NA, NA, NA, "SOME PRIMARY", NA, NA, "NO SCHOOL", "COMPLETED SECONDARY", "COMPLETED PRIMARY", "COMPLETED PRIMARY", NA, NA, NA, NA, NA, "NO SCHOOL", "SOME PRIMARY", NA, "NO SCHOOL", NA, "COMPLETED PRIMARY", NA, NA, NA, "COMPLETED PRIMARY", NA, "COMPLETED PRIMARY", "COMPLETED PRIMAR…
$ hh_b15_1       <chr> "dead", "dead", "dead", "LIVING OUTSIDE THE HOUSEHOLD", "dead", "dead", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "dead", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", NA, "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "dead", "dead", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "dead", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "dead", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "MEMBER OF THE HOUSEHOLD", "LIVING OUTSIDE THE HOUSEHOLD", "MEMBER OF THE HOUSEHO…
$ hh_b15_2       <dbl> NA, NA, NA, NA, NA, NA, NA, 2, 2, 2, NA, NA, NA, 2, NA, NA, 2, NA, 2, 2, 2, 2, NA, NA, 2, NA, 1, 1, NA, NA, 2, 2, 2, 2, NA, NA, 2, 2, NA, NA, 2, NA, NA, 2, 2, NA, NA, 2, NA, NA, 2, 2, 2, NA, NA, 2, 2, NA, 1, 1, NA, NA, 2, NA, NA, NA, 2, 2, 2, 2, NA, NA, 2, 2, NA, NA, 2, NA, NA, 2, 2, 2, NA, NA, 2, 2, NA, NA, NA, NA, 3, NA, NA, NA, 2, 2, 2, 2, 2, 2, NA, NA, NA, NA, NA, NA, NA, 2, 2, 2, 2, 2, NA, NA, 2, NA, 7, NA, 7, 2, 2, NA, 2, 21, 21, 21, 21, NA, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 5, 5, 4, NA, NA, NA, 4, 4, 4, 4, NA, 2, 2, 2, 2, NA, NA, 2, NA, NA, 2, 2, NA, 5, 5, 5, NA, NA, 2, 2, 2, 2, 2, 2, NA, NA, 2, 3, 3, 3, 3, 2, 8, 8, 3, 3, NA, NA, 1, 1, NA, NA, 2, 2, NA, NA, NA, NA, NA, 6, NA, NA, 2, 2, 2, 2, 2, NA, NA, 2, 2, 2, 2, 2, NA, NA, 2, 2, 2, 2, 2, NA, NA, 2, 2, 2, NA, 1, 1, NA, 1, NA, 4, NA, 1, 1, 1, 1, 1, NA, NA, 2, 2, 2, 2, 2, NA, NA, 2, NA, 1, 1, 1, 1, 1, 1, 1, 1, NA, NA, 2, NA, NA, NA, 1, 1, 1, 1, 1, 1, NA, 1, 1, 1, NA, 1, 1, 1, 1, 1, 1, NA, 1, 1, 1, NA, 1, NA, NA, 2, NA, NA, NA, 2, 2, 2, 2, NA, NA, NA, 4, NA, NA, 6, 3, NA, NA, NA, NA, NA, NA, NA, NA, 2, 2, NA, 2, 2, NA, NA, NA, NA, NA, NA, NA, 9, 8, NA, NA, NA, 2, NA, NA, 2, 2, NA, NA, 2, 2, NA, NA, 2, 2, NA, NA, NA, NA, 2, 2, NA, NA, NA, 2, 2, NA, NA, NA, NA, NA, NA, 2, 2, NA, 1, 1, NA, NA, 1, NA, 2, NA, NA, NA, NA, 4, NA, 1, NA, 1, 7, NA, NA, NA, 2, 2, NA, NA, 4, NA, NA, 2, 2, 2, NA, NA, 2, 2, NA, NA, 2, 2, 2, 2, NA, NA, NA, 2, NA, NA, NA, 2, NA, 1, 1, NA, NA, 2, 2, 2, 2, 3, 3, NA, NA, NA, 2, 2, 2, …
$ hh_b16         <dbl> 56, 20, 12, NA, 20, 17, NA, NA, NA, NA, NA, NA, 13, NA, NA, NA, NA, NA, NA, NA, NA, NA, 43, 26, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 28, NA, NA, NA, NA, NA, NA, NA, 38, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 20, NA, NA, NA, NA, NA, NA, 36, 8, NA, NA, NA, NA, 39, NA, NA, 12, 2, 22, NA, NA, NA, 35, 38, NA, NA, NA, NA, NA, NA, NA, NA, NA, 55, 27, 26, 6, NA, NA, NA, NA, NA, NA, 47, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 29, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 59, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 16, 4, NA, NA, 18, 17, 13, 8, NA, NA, NA, NA, NA, NA, NA, NA, NA, 49, 37, NA, NA, NA, NA, NA, NA, 23, NA, NA, NA, NA, NA, NA, 30, NA, NA, NA, 55, NA, NA, 48, NA, NA, NA, NA, NA, NA, NA, NA, NA, 59, NA, NA, NA, NA, NA, NA, NA, NA, NA, 18, NA, NA, NA, NA, NA, NA, NA, NA, 34, NA, NA, NA, NA, 27, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 34, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 28, NA, NA, 18, NA, 37, NA, NA, NA, NA, 50, 69, 48, NA, NA, NA, NA, NA, 35, 51, 43, NA, NA, NA, 44, 17, NA, NA, 31, NA, NA, 30, 22, NA, NA, NA, NA, NA, NA, NA, NA, 38, 32, NA, 46, NA, NA, NA, NA, NA, NA, NA, NA, 14, NA, NA, NA, 55, NA, 19, NA, NA, NA, 42, 8, NA, NA, 60, 13, 15, NA, 35, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 54, 2, NA,…
$ hh_b17         <chr> "NO SCHOOL", "SOME PRIMARY", "SOME PRIMARY", "COMPLETED PRIMARY", "NO SCHOOL", "DON'T KNOW", "SOME PRIMARY", NA, NA, NA, "COMPLETED PRIMARY", "DON'T KNOW", "DON'T KNOW", NA, "NO SCHOOL", "COMPLETED PRIMARY", NA, NA, NA, NA, NA, NA, "NO SCHOOL", "NO SCHOOL", NA, "NO SCHOOL", NA, NA, "NO SCHOOL", "NO SCHOOL", NA, NA, NA, NA, "NO SCHOOL", "NO SCHOOL", NA, NA, "DON'T KNOW", "COMPLETED PRIMARY", NA, "COMPLETED PRIMARY", "COMPLETED PRIMARY", NA, NA, "ADULT EDUCATION / ELIMU YA WATU WAZIMA", "COMPLETED PRIMARY", NA, "ADULT EDUCATION / ELIMU YA WATU WAZIMA", "COMPLETED PRIMARY", NA, NA, NA, "COMPLETED PRIMARY", "SOME PRIMARY", NA, NA, "COMPLETED PRIMARY", NA, NA, "NO SCHOOL", "COMPLETED PRIMARY", NA, "COMPLETED PRIMARY", "COMPLETED PRIMARY", "COMPLETED SECONDARY", NA, NA, NA, NA, "DON'T KNOW", "DON'T KNOW", NA, NA, "COMPLETED PRIMARY", "COMPLETED PRIMARY", NA, "NO SCHOOL", "COMPLETED PRIMARY", NA, NA, NA, "COMPLETED PRIMARY", "COMPLETED PRIMARY", NA, NA, "DON'T KNOW", "NO SCHOOL", "COMPLETED PRIMARY", "COMPLETED PRIMARY", NA, "COMPLETED PRIMARY", "DON'T KNOW", "NO SCHOOL", NA, NA, NA, NA, NA, NA, "COMPLETED PRIMARY", "SOME PRIMARY", "SOME PRIMARY", "NO SCHOOL", "NO SCHOOL", "NO SCHOOL", "NO SCHOOL", NA, NA, NA, NA, NA, "NO SCHOOL", "NO SCHOOL", NA, "NO SCHOOL", NA, "COMPLETED PRIMARY", NA, NA, NA, "COMPLETED PRIMARY", NA, NA, NA, NA, NA, "NO SCHOOL", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "NO SCHOOL", "NO SCHOOL", "NO SCHOOL", NA, NA, NA, NA, "NO…
$ hh_b18         <chr> "yes", "yes", "yes", "no", "yes", "yes", "yes", "yes", "no", "no", "no", "yes", "yes", "no", "yes", "yes", "yes", NA, "yes", "yes", "no", "no", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "no", "no", "no", "yes", "yes", "yes", "yes", "yes", "yes", "no", "yes", "yes", "no", "no", "yes", "yes", "no", "yes", "yes", "no", "no", "no", "yes", "yes", "no", "no", "yes", "yes", "no", "yes", "yes", "no", "yes", "yes", "yes", "yes", "no", "no", "no", "yes", "yes", "no", "no", "yes", "yes", "no", "yes", "yes", "yes", "no", "no", "yes", "yes", "yes", "no", "yes", "yes", "yes", "yes", "no", "yes", "yes", "yes", "yes", "yes", "no", "no", "no", "no", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "no", "no", "no", "no", "no", "yes", "yes", "yes", "yes", "no", "yes", "no", "no", "no", "yes", "yes", "no", "no", "no", "no", "yes", "yes", "no", "yes", "yes", "no", "no", "no", "no", "no", "no", "no", "no", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "yes", "no", "no", "no", "no", "no", "yes", "yes", "yes", "yes", "yes", "no", "no", "yes", "no", "no", "no", "yes", "yes", "yes", "yes", "no", "no", "no", "no", "yes", "yes", "yes", "yes", "yes", "yes", "no", "yes", "no", "no", "no", "no", "no", "yes", "no", "no", "yes", "yes", "no", "no", "yes", "yes", "yes", "yes", "yes", "no", "yes", "yes", "yes", "yes", "no", "no", "no", "yes", "yes", "yes", "yes", "yes", "yes", "no", "yes", "yes", "no", "no", "no", "no", "no", "yes", "yes", "no", "no", "no", "yes…
$ hh_b19         <chr> "WIDOW(ER)", "divorced", "separated", NA, "NEVER MARRIED", "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", "NEVER MARRIED", NA, NA, NA, "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", NA, "POLYGAMOUS MARRIED", "MONOGAMOUS MARRIED", "NEVER MARRIED", NA, "NEVER MARRIED", "NEVER MARRIED", NA, NA, "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", "NEVER MARRIED", "WIDOW(ER)", "separated", "NEVER MARRIED", "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", "NEVER MARRIED", NA, NA, NA, "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", "NEVER MARRIED", "NEVER MARRIED", "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", NA, "LIVING TOGETHER", "LIVING TOGETHER", NA, NA, "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", NA, "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", NA, NA, NA, "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", NA, NA, "NEVER MARRIED", "NEVER MARRIED", NA, "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", NA, "separated", "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", "NEVER MARRIED", NA, NA, NA, "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", NA, NA, "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", NA, "WIDOW(ER)", "separated", "NEVER MARRIED", NA, NA, "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", "NEVER MARRIED", NA, "NEVER MARRIED", "WIDOW(ER)", "LIVING TOGETHER", "LIVING TOGETHER", NA, "divorced", "MONOGAMOUS MARRIED", "MONOGAMOUS MARRIED", "NEVER MARRIED", "NEVER MARRIED", NA, NA, NA, NA, "separated", "NEVER MARRIED", "NEVER MARRIED", "MONOGAMOUS MARRIED", "NEVER MARRIED", "MONOGAMOUS MARRIED", "MONOGAMO…
$ hh_b20         <chr> NA, NA, NA, NA, NA, "NEVER MARRIED", "PREVIOUSLY DIVORCED", NA, NA, NA, NA, "NEVER MARRIED", "NEVER MARRIED", NA, "NEVER MARRIED", "NEVER MARRIED", NA, NA, NA, NA, NA, NA, "MULTIPLE PREVIOUS MARRIAGES", "PREVIOUSLY DIVORCED", NA, NA, NA, NA, "MULTIPLE PREVIOUS MARRIAGES", "PREVIOUSLY WIDOWED", NA, NA, NA, NA, "NEVER MARRIED", "NEVER MARRIED", NA, NA, "NEVER MARRIED", "NEVER MARRIED", NA, NA, NA, NA, NA, "NEVER MARRIED", "NEVER MARRIED", NA, "NEVER MARRIED", "NEVER MARRIED", NA, NA, NA, "NEVER MARRIED", "NEVER MARRIED", NA, NA, NA, NA, NA, "NEVER MARRIED", "NEVER MARRIED", NA, NA, "NEVER MARRIED", "NEVER MARRIED", NA, NA, NA, NA, "NEVER MARRIED", "NEVER MARRIED", NA, NA, "PREVIOUSLY DIVORCED", "NEVER MARRIED", NA, NA, NA, NA, NA, NA, "NEVER MARRIED", "NEVER MARRIED", NA, NA, NA, NA, NA, NA, NA, NA, "NEVER MARRIED", "NEVER MARRIED", NA, NA, NA, NA, NA, NA, NA, NA, NA, "NEVER MARRIED", NA, "NEVER MARRIED", "NEVER MARRIED", NA, NA, NA, NA, NA, "NEVER MARRIED", "NEVER MARRIED", "NEVER MARRIED", "NEVER MARRIED", NA, NA, NA, NA, NA, "NEVER MARRIED", NA, NA, NA, NA, NA, "PREVIOUSLY DIVORCED", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "MULTIPLE PREVIOUS MARRIAGES", "NEVER MARRIED", "NEVER MARRIED", "NEVER MARRIED", NA, NA, NA, NA, NA, NA, NA, NA, NA, "MULTIPLE PREVIOUS MARRIAGES", "NEVER MARRIED", NA, "NEVER MARRIED", "NEVER MARRIED", NA, NA, NA, NA, NA, NA, "MULTIPLE PREVIOUS MARRIAGES", "NEVER MARRIED", NA, NA, NA, NA, NA, NA, "NEVER MARRIED", "NEVER M…
$ hh_b21_1       <chr> NA, NA, NA, NA, NA, "religious", "religious", NA, NA, NA, NA, "religious", "traditional", NA, "religious", "religious", NA, NA, NA, NA, NA, NA, "traditional", "traditional", NA, NA, NA, NA, "religious", "religious", NA, NA, NA, NA, "religious", "religious", NA, NA, "religious", "religious", NA, NA, NA, NA, NA, "religious", "religious", NA, "traditional", "traditional", NA, NA, NA, "traditional", "traditional", NA, NA, NA, NA, NA, "religious", "religious", NA, NA, "religious", "religious", NA, NA, NA, NA, "religious", "religious", NA, NA, "religious", "religious", NA, NA, NA, NA, NA, NA, "religious", "religious", NA, NA, NA, NA, NA, NA, NA, NA, "religious", "religious", NA, NA, NA, NA, NA, NA, NA, NA, NA, "traditional", NA, "traditional", "traditional", NA, NA, NA, NA, NA, "traditional", "traditional", "traditional", "traditional", NA, NA, NA, NA, NA, "traditional", NA, NA, NA, NA, NA, "religious", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "traditional", "traditional", "traditional", "traditional", NA, NA, NA, NA, NA, NA, NA, NA, NA, "traditional", "traditional", NA, "traditional", "traditional", NA, NA, NA, NA, NA, NA, "traditional", "traditional", NA, NA, NA, NA, NA, NA, "traditional", "traditional", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "traditional", NA, NA, "traditional", "traditional", NA, NA, "religious", NA, NA, NA, "religious", NA, "religious", "religious", NA, NA, NA, NA, NA, "religious", "religious", NA, NA, NA, NA, NA, "religiou…
$ hh_b21_2       <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "traditional", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "traditional", NA, "traditional", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "traditional", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "traditional", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "traditional", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
$ hh_b21_3       <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
$ hh_b21_4       <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
$ hh_b22         <chr> NA, NA, NA, NA, NA, "yes", "yes", NA, NA, NA, NA, "yes", "yes", NA, "yes", "yes", NA, NA, NA, NA, NA, NA, "yes", "yes", NA, NA, NA, NA, "yes", "yes", NA, NA, NA, NA, "yes", "yes", NA, NA, "yes", "yes", NA, "yes", "yes", NA, NA, "yes", "yes", NA, "yes", "yes", NA, NA, NA, "yes", "yes", NA, NA, NA, NA, NA, "yes", "yes", NA, NA, "yes", "yes", NA, NA, NA, NA, "yes", "yes", NA, NA, "yes", "yes", NA, NA, NA, NA, NA, NA, "yes", "yes", NA, NA, NA, NA, "yes", "yes", NA, NA, "yes", "yes", NA, NA, NA, NA, NA, NA, NA, NA, NA, "no", NA, "yes", "yes", NA, NA, NA, NA, NA, "yes", "no", "yes", "yes", NA, NA, NA, NA, NA, "yes", NA, NA, NA, NA, NA, "no", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "yes", "yes", "yes", "no", NA, NA, NA, NA, NA, NA, NA, NA, NA, "yes", "yes", NA, "yes", "yes", NA, NA, NA, NA, NA, NA, "yes", "yes", NA, NA, NA, NA, NA, NA, "yes", "yes", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "no", NA, NA, "yes", "yes", NA, NA, "yes", NA, NA, NA, "yes", NA, "yes", "yes", NA, NA, NA, NA, NA, "yes", "yes", NA, NA, NA, NA, NA, "yes", "yes", NA, NA, NA, NA, NA, "yes", "yes", NA, NA, NA, NA, NA, NA, NA, "yes", "yes", NA, NA, NA, NA, NA, NA, NA, "yes", "yes", NA, NA, NA, NA, NA, "yes", "yes", NA, "no", NA, NA, NA, NA, NA, NA, NA, NA, "yes", "yes", NA, "yes", "yes", "no", NA, NA, NA, NA, NA, NA, "no", NA, NA, NA, "no", NA, NA, NA, NA, NA, NA, "no", NA, NA, NA, NA, NA, "yes", "yes", NA, NA, "yes", "yes", NA, NA, NA, NA, "yes", "yes", NA, NA, NA, NA, NA, NA, …
$ hh_b23_1       <dbl> NA, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, 2, 1, NA, 2, 1, NA, NA, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, 2, 1, NA, NA, 2, 1, NA, 2, 1, NA, NA, 2, 1, NA, 2, 1, NA, NA, NA, 2, 1, NA, NA, NA, NA, NA, 2, 1, NA, NA, 2, 1, NA, NA, NA, NA, 2, 1, NA, NA, 2, 1, NA, NA, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, 3, 1, NA, NA, 2, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, NA, 2, NA, 7, 6, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, 1, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, 1, NA, 2, 1, NA, NA, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, 1, NA, NA, 6, NA, NA, NA, 1, NA, 2, 1, NA, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, NA, NA, NA, 4, 2, NA, NA, NA, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, 1, NA, 2, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, 1, NA, NA, 2, 1, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, 1, 9, NA, NA, 3, NA, NA, NA, NA, 2, 1, NA, 2, 1, NA, NA, 2, 1, NA, NA, 2, NA, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, 1, NA, NA, NA, 2, 1, 4, 3, NA, NA, NA, 2, 1, NA, NA,…
$ hh_b23_2       <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 20, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 3, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
$ hh_b23_3       <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
$ hh_b23_4       <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
$ hh_b24         <chr> NA, NA, NA, NA, NA, "no", "no", NA, NA, NA, NA, "no", "no", NA, "yes", "no", NA, NA, NA, NA, NA, NA, "no", "no", NA, NA, NA, NA, "no", "no", NA, NA, NA, NA, "no", "no", NA, NA, "no", "no", NA, "no", "no", NA, NA, "no", "no", NA, "no", "no", NA, NA, NA, "no", "no", NA, NA, NA, NA, NA, "no", "no", NA, NA, "no", "no", NA, NA, NA, NA, "no", "no", NA, NA, "no", "no", NA, NA, NA, NA, NA, NA, "no", "no", NA, NA, NA, NA, "no", "no", NA, NA, "no", "no", NA, NA, NA, NA, NA, NA, NA, NA, NA, "yes", NA, "no", "no", NA, NA, NA, NA, NA, "no", "yes", "no", "no", NA, NA, NA, NA, NA, "no", NA, NA, NA, NA, NA, "yes", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "no", "no", "no", "yes", NA, NA, NA, NA, NA, NA, NA, NA, NA, "yes", "no", NA, "no", "no", NA, NA, NA, NA, NA, NA, "yes", "no", NA, NA, NA, NA, NA, NA, "no", "no", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "yes", NA, NA, "no", "no", NA, NA, "no", NA, NA, NA, "no", NA, "no", "no", NA, NA, NA, NA, NA, "no", "no", NA, NA, NA, NA, NA, "no", "no", NA, NA, NA, NA, NA, "no", "no", NA, NA, NA, NA, NA, NA, NA, "no", "no", NA, NA, NA, NA, NA, NA, NA, "no", "no", NA, NA, NA, NA, NA, "no", "no", NA, "yes", NA, NA, NA, NA, NA, NA, NA, NA, "no", "no", NA, "no", "no", "yes", NA, NA, NA, NA, NA, NA, "yes", NA, NA, NA, "yes", NA, NA, NA, NA, NA, NA, "yes", NA, NA, NA, NA, NA, "no", "no", NA, NA, "no", "no", NA, NA, NA, NA, "no", "no", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "no", "no", "no"…
$ hh_b25         <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
$ hh_b26         <chr> "60", "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", NA, "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", "2", "LIVED HERE SINCE BIRTH", NA, NA, NA, "1", "1", NA, "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", NA, "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", NA, NA, "64", "50", "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", NA, NA, NA, "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", "5", "5", NA, "LIVED HERE SINCE BIRTH", "6", NA, NA, "3", "3", NA, "LIVED HERE SINCE BIRTH", "8", NA, NA, NA, "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", NA, NA, "3", "3", NA, "2", "2", NA, "9", "11", "7", "7", NA, NA, NA, "5", "5", NA, NA, "6", "4", NA, "35", "3", "3", NA, NA, "LIVED HERE SINCE BIRTH", "15", "LIVED HERE SINCE BIRTH", NA, "3", "17", "LIVED HERE SINCE BIRTH", "4", NA, "LIVED HERE SINCE BIRTH", "14", "14", "6", "LIVED HERE SINCE BIRTH", NA, NA, NA, NA, "11", "12", "LIVED HERE SINCE BIRTH", "26", "1", "5", "5", NA, NA, NA, NA, NA, "12", "12", "12", "11", NA, "12", NA, NA, NA, "1", "2", NA, NA, NA, NA, "12", "2", NA, "3", "3", NA, NA, NA, NA, NA, NA, NA, NA, "13", "8", "0", "18", "13", "13", "13", "LIVED HERE SINCE BIRTH", NA, NA, NA, NA, NA, "24", "20", "LIVED HERE SINCE BIRTH", "LIVED HERE SINCE BIRTH", "6", NA, NA, "…
$ hh_b27_2       <chr> "arusha", NA, NA, NA, NA, NA, "kilimanjaro", NA, NA, NA, NA, "arusha", "arusha", NA, NA, NA, NA, NA, NA, NA, NA, NA, "arusha", "kilimanjaro", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "arusha", "arusha", NA, NA, "kilimanjaro", NA, NA, "arusha", "arusha", NA, NA, "arusha", NA, NA, NA, NA, NA, NA, NA, "arusha", "arusha", NA, "manyara", "kilimanjaro", NA, "dodoma", "MJINI/MAGHARIBI UNGUJA", "MJINI/MAGHARIBI UNGUJA", "MJINI/MAGHARIBI UNGUJA", NA, NA, NA, "dodoma", "tanga", NA, NA, "arusha", "manyara", NA, "tanga", "singida", "singida", NA, NA, NA, "manyara", NA, NA, "manyara", "arusha", NA, "DAR ES SALAAM", NA, NA, "arusha", "arusha", "arusha", NA, NA, NA, NA, NA, "arusha", "arusha", NA, "arusha", "arusha", "arusha", "arusha", NA, NA, NA, NA, NA, "singida", "singida", "singida", "simiyu", NA, "singida", NA, NA, NA, "singida", "singida", NA, NA, NA, NA, "singida", "singida", NA, "singida", "singida", NA, NA, NA, NA, NA, NA, NA, NA, "simiyu", "arusha", "arusha", "simiyu", "simiyu", "simiyu", "simiyu", NA, NA, NA, NA, NA, NA, "simiyu", "simiyu", NA, NA, "arusha", NA, NA, "tabora", NA, NA, NA, "singida", "simiyu", NA, NA, NA, NA, NA, NA, "arusha", "arusha", "arusha", "arusha", "arusha", "arusha", NA, "singida", NA, NA, NA, NA, NA, "simiyu", NA, NA, NA, "arusha", NA, NA, NA, NA, NA, NA, "tanga", NA, NA, NA, NA, NA, NA, NA, NA, "arusha", NA, NA, NA, NA, NA, NA, "arusha", NA, NA, NA, NA, NA, NA, NA, "arusha", NA, NA, NA, NA, NA, NA, NA, NA, "arusha…
$ hh_b27_3       <chr> "meru", NA, NA, NA, NA, NA, "hai", NA, NA, NA, NA, "meru", "meru", NA, NA, NA, NA, NA, NA, NA, NA, NA, "meru", "siha", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "meru", "meru", NA, NA, "siha", NA, NA, "meru", "meru", NA, NA, "meru", NA, NA, NA, NA, NA, NA, NA, "meru", "meru", NA, "BABATI TOWN", "MOSHI RURAL", NA, "DODOMA URBAN", "mjini", "mjini", "mjini", NA, NA, NA, "chamwino", "mkinga", NA, NA, "meru", "BABATI TOWN", NA, "lushoto", "SINGIDA URBAN", "SINGIDA URBAN", NA, NA, NA, "MBULU TOWN", NA, NA, "MBULU TOWN", "ARUSHA URBAN", NA, "kigamboni", NA, NA, "ARUSHA URBAN", "ARUSHA URBAN", "ARUSHA URBAN", NA, NA, NA, NA, NA, "ARUSHA URBAN", "monduli", NA, "ARUSHA URBAN", "ARUSHA URBAN", "karatu", "karatu", NA, NA, NA, NA, NA, "mkalama", "mkalama", "mkalama", "meatu", NA, "mkalama", NA, NA, NA, "mkalama", "mkalama", NA, NA, NA, NA, "mkalama", "mkalama", NA, "mkalama", "mkalama", NA, NA, NA, NA, NA, NA, NA, NA, "meatu", "karatu", "karatu", "meatu", "meatu", "meatu", "meatu", NA, NA, NA, NA, NA, NA, "meatu", "meatu", NA, NA, "karatu", NA, NA, "nzega", NA, NA, NA, "iramba", "meatu", NA, NA, NA, NA, NA, NA, "karatu", "karatu", "karatu", "karatu", "karatu", "karatu", NA, "mkalama", NA, NA, NA, NA, NA, "meatu", NA, NA, NA, "meru", NA, NA, NA, NA, NA, NA, "handeni", NA, NA, NA, NA, NA, NA, NA, NA, "meru", NA, NA, NA, NA, NA, NA, "ARUSHA URBAN", NA, NA, NA, NA, NA, NA, NA, "ARUSHA RURAL", NA, NA, NA, NA, NA, NA, NA, NA, "ARUSHA RURAL", NA, NA, NA, NA…
$ hh_b28         <chr> "BETTER SERVICES/HOUSING", NA, NA, NA, NA, NA, "marriage", NA, NA, NA, NA, "BETTER SERVICES/HOUSING", "BETTER SERVICES/HOUSING", NA, NA, NA, NA, NA, NA, NA, NA, NA, "OTHER FAMILY REASONS", "marriage", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "BETTER SERVICES/HOUSING", "BETTER SERVICES/HOUSING", NA, NA, "marriage", NA, NA, "WORK RELATED", "marriage", NA, NA, "marriage", NA, NA, NA, NA, NA, NA, NA, "OTHER (SPECIFY)", "BETTER SERVICES/HOUSING", NA, "OTHER FAMILY REASONS", "WORK RELATED", NA, "WORK RELATED", "WORK RELATED", "OTHER FAMILY REASONS", "OTHER FAMILY REASONS", NA, NA, NA, "WORK RELATED", "marriage", NA, NA, "WORK RELATED", "marriage", NA, "SCHOOL/STUDIES", "OTHER FAMILY REASONS", "OTHER FAMILY REASONS", NA, NA, NA, "OTHER FAMILY REASONS", NA, NA, "OTHER FAMILY REASONS", "BETTER SERVICES/HOUSING", NA, "marriage", NA, NA, "BETTER SERVICES/HOUSING", "BETTER SERVICES/HOUSING", "OTHER FAMILY REASONS", NA, NA, NA, NA, NA, "BETTER SERVICES/HOUSING", "OTHER FAMILY REASONS", NA, "BETTER SERVICES/HOUSING", "BETTER SERVICES/HOUSING", "BETTER SERVICES/HOUSING", "BETTER SERVICES/HOUSING", NA, NA, NA, NA, NA, "BETTER SERVICES/HOUSING", "marriage", "OTHER FAMILY REASONS", "OTHER FAMILY REASONS", NA, "OTHER FAMILY REASONS", NA, NA, NA, "marriage", "OTHER (SPECIFY)", NA, NA, NA, NA, "marriage", "OTHER FAMILY REASONS", NA, "OTHER FAMILY REASONS", "BETTER SERVICES/HOUSING", NA, NA, NA, NA, NA, NA, NA, NA, "BETTER SERVICES/HOUSING", "marriage", "mar…
$ hh_b29_2       <chr> "arusha", NA, NA, NA, NA, NA, "kilimanjaro", NA, NA, NA, NA, "kilimanjaro", "arusha", NA, NA, NA, NA, NA, NA, NA, NA, NA, "arusha", "kilimanjaro", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "arusha", "dodoma", NA, NA, "kilimanjaro", NA, NA, "arusha", "arusha", NA, NA, "arusha", NA, NA, NA, NA, NA, NA, NA, "arusha", "arusha", NA, "manyara", "kilimanjaro", NA, "kagera", "morogoro", "mbeya", "DAR ES SALAAM", NA, NA, NA, "dodoma", "tanga", NA, NA, "iringa", "manyara", NA, "tanga", "manyara", "manyara", NA, NA, NA, "manyara", NA, NA, "manyara", "manyara", NA, "dodoma", NA, NA, "DAR ES SALAAM", "arusha", "arusha", NA, NA, NA, NA, NA, "arusha", "arusha", NA, "kilimanjaro", "kilimanjaro", "simiyu", "simiyu", NA, NA, NA, NA, NA, "simiyu", "simiyu", "simiyu", "simiyu", NA, "singida", NA, NA, NA, "singida", "simiyu", NA, NA, NA, NA, "singida", "singida", NA, "singida", "singida", NA, NA, NA, NA, NA, NA, NA, NA, "simiyu", "arusha", "arusha", "simiyu", "simiyu", "simiyu", "simiyu", NA, NA, NA, NA, NA, NA, "simiyu", "simiyu", NA, NA, "arusha", NA, NA, "tabora", NA, NA, NA, "simiyu", "simiyu", NA, NA, NA, NA, NA, NA, "simiyu", "simiyu", "simiyu", "arusha", "arusha", "arusha", NA, "simiyu", NA, NA, NA, NA, NA, "simiyu", NA, NA, NA, "arusha", NA, NA, NA, NA, NA, NA, "tanga", NA, NA, NA, NA, NA, NA, NA, NA, "arusha", NA, NA, NA, NA, NA, NA, "arusha", NA, NA, NA, NA, NA, NA, NA, "arusha", NA, NA, NA, NA, NA, NA, NA, NA, "arusha", NA, NA, NA, NA, NA, NA, NA,…
$ hh_b29_3       <chr> "meru", NA, NA, NA, NA, NA, "hai", NA, NA, NA, NA, "rombo", "meru", NA, NA, NA, NA, NA, NA, NA, NA, NA, "meru", "siha", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "meru", "kondoa", NA, NA, "siha", NA, NA, "meru", "meru", NA, NA, "meru", NA, NA, NA, NA, NA, NA, NA, "meru", "meru", NA, "BABATI TOWN", "MOSHI RURAL", NA, "BUKOBA RURAL", "MOROGORO RURAL", "chunya", "ilala", NA, NA, NA, "DODOMA URBAN", "muheza", NA, NA, "mufindi", "BABATI TOWN", NA, "lushoto", "BABATI RURAL", "BABATI TOWN", NA, NA, NA, "MBULU TOWN", NA, NA, "MBULU TOWN", "mbulu", NA, "DODOMA URBAN", NA, NA, "kinondoni", "ARUSHA URBAN", "ARUSHA URBAN", NA, NA, NA, NA, NA, "meru", "monduli", NA, "MOSHI RURAL", "MOSHI RURAL", "meatu", "meatu", NA, NA, NA, NA, NA, "meatu", "meatu", "meatu", "meatu", NA, "mkalama", NA, NA, NA, "mkalama", "meatu", NA, NA, NA, NA, "mkalama", "mkalama", NA, "mkalama", "mkalama", NA, NA, NA, NA, NA, NA, NA, NA, "meatu", "karatu", "karatu", "meatu", "meatu", "meatu", "meatu", NA, NA, NA, NA, NA, NA, "meatu", "meatu", NA, NA, "karatu", NA, NA, "nzega", NA, NA, NA, "maswa", "meatu", NA, NA, NA, NA, NA, NA, "maswa", "meatu", "meatu", "karatu", "karatu", "karatu", NA, "meatu", NA, NA, NA, NA, NA, "meatu", NA, NA, NA, "meru", NA, NA, NA, NA, NA, NA, "handeni", NA, NA, NA, NA, NA, NA, NA, NA, "meru", NA, NA, NA, NA, NA, NA, "ARUSHA URBAN", NA, NA, NA, NA, NA, NA, NA, "ARUSHA RURAL", NA, NA, NA, NA, NA, NA, NA, NA, "ARUSHA RURAL", NA, NA, NA, NA, NA, NA, NA, NA…

Objects in memory

  • The data frame is a matrix
    • Each row is an observation and each column is a variables
    • You can see it in the “environment” pane of RStudio
  • We can also see the names of the columns like this:
Code 
colnames(df)
 [1] "interview__key" "y5_hhid"        "y4_hhid"        "indidy5"        "hh_b01"         "hh_b02"         "hh_b03_1"       "hh_b03_2"       "hh_b04"         "hh_b05"         "hh_b06"         "hh_b07"         "hh_b08"         "hh_b09_1"       "hh_b0a"         "hh_b0b"         "hh_b10"         "hh_b11"         "hh_b12_1"       "hh_b12_2"       "hh_b13"         "hh_b14"         "hh_b15_1"       "hh_b15_2"       "hh_b16"         "hh_b17"         "hh_b18"         "hh_b19"         "hh_b20"         "hh_b21_1"       "hh_b21_2"       "hh_b21_3"       "hh_b21_4"       "hh_b22"         "hh_b23_1"       "hh_b23_2"       "hh_b23_3"       "hh_b23_4"       "hh_b24"         "hh_b25"         "hh_b26"         "hh_b27_2"       "hh_b27_3"       "hh_b28"         "hh_b29_2"       "hh_b29_3"

Calling variables in R

  • Some of you might be used to Stata

  • One big difference between the two is that Stata generally only has one data frame in memory at a time

    • This means that you can call a variable without referencing the data frame

  • In R, if you want to look at a variable, you have to tell R which data frame it is in

    • This is done with the $ operator
    • For example, if I want to look at the variable “age” in the data frame “data”, I would write data$age
    • In our dataset, the age variable is hh_b04

Summary stats for hh_b04 (age)

  • There are two common ways to quickly look at a variable:
    • summary(): gives you mean/median, and a few more
    • table(): gives you a frequency table
Code 
summary(df$hh_b04)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
   0.00    8.00   18.00   22.78   33.00   95.00

Summary stats for hh_b04 (age)

  • There are two common ways to quickly look at a variable:
    • summary(): gives you mean/median, and a few more
    • table(): gives you a frequency table
Code 
table(df$hh_b04)

  0   1   2   3   4   5   6   7   8   9  10  11  12  13  14  15  16  17  18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54  55  56  57  58  59  60  61  62  63  64  65  66  67  68  69  70  71  72  73  74  75  76  77  78  79  80  81  82  83  84  85  86  87  88  89  90  91  92  94  95 
695 750 721 716 723 597 738 717 623 647 627 619 574 582 571 559 592 546 518 438 519 500 403 397 384 425 379 352 358 323 277 299 285 278 219 263 304 222 247 212 197 243 179 182 179 193 203 181 196 169 114 146 100 157 100 111 140 121  94 106 102  84  81  65  58  58 104  63  56  56  47  70  36  30  23  33  49  22  36  20  25  24   7  13  14  11  21   7  12  10   9  16   5   4  11

Summary stats for everything

  • If you don’t specify a variable, it will give you information for the ENTIRE dataframe!
Code 
summary(df)
 interview__key       y5_hhid            y4_hhid             indidy5          hh_b01             hh_b02            hh_b03_1           hh_b03_2             hh_b04         hh_b05             hh_b06             hh_b07              hh_b08       hh_b09_1            hh_b0a              hh_b0b           hh_b10           hh_b11            hh_b12_1            hh_b12_2          hh_b13         hh_b14            hh_b15_1            hh_b15_2          hh_b16         hh_b17             hh_b18             hh_b19             hh_b20            hh_b21_1           hh_b21_2           hh_b21_3         hh_b21_4          hh_b22             hh_b23_1         hh_b23_2      hh_b23_3       hh_b23_4          hh_b24              hh_b25         hh_b26            hh_b27_2           hh_b27_3            hh_b28            hh_b29_2           hh_b29_3        
 Length:23592       Length:23592       Length:23592       Min.   : 1.000   Length:23592       Length:23592       Length:23592       Length:23592       Min.   : 0.00   Length:23592       Length:23592       Length:23592       Min.   : 0.0   Length:23592       Length:23592       Min.   : 0.000   Min.   : 0.0000   Length:23592       Length:23592       Min.   : 0.000   Min.   : 0.00   Length:23592       Length:23592       Min.   : 0.000   Min.   : 0.00   Length:23592       Length:23592       Length:23592       Length:23592       Length:23592       Length:23592       Length:23592       Mode:logical   Length:23592       Min.   : 0.000   Min.   : 3.000   Mode:logical   Mode:logical   Length:23592       Min.   :0.000   Length:23592       Length:23592       Length:23592       Length:23592       Length:23592       Length:23592      
 Class :character   Class :character   Class :character   1st Qu.: 2.000   Class :character   Class :character   Class :character   Class :character   1st Qu.: 8.00   Class :character   Class :character   Class :character   1st Qu.:30.0   Class :character   Class :character   1st Qu.: 1.000   1st Qu.: 0.0000   Class :character   Class :character   1st Qu.: 1.000   1st Qu.:10.00   Class :character   Class :character   1st Qu.: 2.000   1st Qu.:13.00   Class :character   Class :character   Class :character   Class :character   Class :character   Class :character   Class :character   NA's:23592     Class :character   1st Qu.: 1.000   1st Qu.: 3.000   NA's:23592     NA's:23592     Class :character   1st Qu.:1.000   Class :character   Class :character   Class :character   Class :character   Class :character   Class :character  
 Mode  :character   Mode  :character   Mode  :character   Median : 4.000   Mode  :character   Mode  :character   Mode  :character   Mode  :character   Median :18.00   Mode  :character   Mode  :character   Mode  :character   Median :30.0   Mode  :character   Mode  :character   Median : 2.000   Median : 0.0000   Mode  :character   Mode  :character   Median : 1.000   Median :20.00   Mode  :character   Mode  :character   Median : 2.000   Median :28.00   Mode  :character   Mode  :character   Mode  :character   Mode  :character   Mode  :character   Mode  :character   Mode  :character                  Mode  :character   Median : 2.000   Median : 5.500                                 Mode  :character   Median :1.000   Mode  :character   Mode  :character   Mode  :character   Mode  :character   Mode  :character   Mode  :character  
                                                          Mean   : 4.493                                                                               Mean   :22.78                                                            Mean   :27.9                                         Mean   : 2.169   Mean   : 0.5844                                         Mean   : 1.426   Mean   :22.69                                         Mean   : 2.533   Mean   :28.25                                                                                                                                                                          Mean   : 2.259   Mean   : 7.482                                                    Mean   :1.138                                                                                                                    
                                                          3rd Qu.: 6.000                                                                               3rd Qu.:33.00                                                            3rd Qu.:31.0                                         3rd Qu.: 2.000   3rd Qu.: 0.0000                                         3rd Qu.: 1.000   3rd Qu.:34.00                                         3rd Qu.: 2.000   3rd Qu.:42.00                                                                                                                                                                          3rd Qu.: 2.000   3rd Qu.:10.000                                                    3rd Qu.:1.000                                                                                                                    
                                                          Max.   :42.000                                                                               Max.   :95.00                                                            Max.   :31.0                                         Max.   :29.000   Max.   :12.0000                                         Max.   :42.000   Max.   :76.00                                         Max.   :41.000   Max.   :87.00                                                                                                                                                                          Max.   :42.000   Max.   :27.000                                                    Max.   :3.000                                                                                                                    
                                                                                                                                                                                                                                                                                     NA's   :10146    NA's   :662                                             NA's   :14698    NA's   :17439                                         NA's   :12092    NA's   :19792                                                                                                                                                                          NA's   :16816    NA's   :23536                                                     NA's   :23230

Variable types

  • The most common are numeric, character, and logical
    • Numeric variables are numbers
      • For example, the variable hh_b04 is a numeric variable
      • Missing value: NA
    • Character variables are text
      • For example, the variable y5_hhid is a character variable
      • Missing value: ""
    • Logical variables are TRUE/FALSE
      • We don’t have any examples here (at least not yet)
      • Missing value: NA

Pipes

  • One of the most useful things in R is the pipe operator (|> or %>%)
    • This is part of the tidyverse package
    • It allows you to chain commands together
    • It makes your code much easier to read
    • It makes your code much easier to write

  • Let’s use it to clean some variables

Pipes example

  • I’m going to create some new variables.
    • Going to use two columns: hh_b02 and hh_b04
Code 
glimpse(df[,c("hh_b02", "hh_b04")])
Rows: 23,592
Columns: 2
$ hh_b02 <chr> "male", "female", "male", "male", "male", "male", "female", "female", "male", "female", "female", "male", "female", "male", "male", "female", "male", "female", "male", "male", "female", "male", "male", "female", "female", "female", "female", "male", "male", "female", "male", "female", "male", "male", "male", "female", "male", "female", "male", "female", "male", "male", "female", "male", "female", "male", "female", "male", "male", "female", "female", "female", "male", "male", "female", "male", "female", "female", "female", "female", "male", "female", "male", "male", "male", "female", "male", "female", "male", "male", "male", "female", "female", "male", "male", "female", "female", "female", "female", "male", "male", "female", "male", "female", "male", "male", "male", "male", "male", "female", "male", "female", "male", "female", "female", "female", "male", "male", "female", "female", "male", "female", "male", "male", "male", "male", "female", "male", "female", "female", "male", "male", "male", "female", "male", "female", "male", "female", "female", "female", "male", "female", "female", "male", "male", "female", "female", "female", "female", "male", "female", "female", "female", "female", "male", "male", "female", "female", "male", "male", "male", "female", "female", "female", "male", "female", "female", "male", "female", "male", "female", "female", "male", "male", "female", "male", "male", "female", "female", "male", "female", "male", "male", "male", "male", "fe…
$ hh_b04 <dbl> 74, 44, 35, 9, 47, 36, 42, 21, 1, 1, 6, 32, 32, 2, 48, 45, 23, 21, 17, 14, 8, 2, 79, 71, 34, 63, 41, 22, 44, 35, 12, 10, 6, 3, 59, 52, 16, 14, 31, 27, 3, 28, 25, 6, 1, 42, 26, 2, 29, 28, 7, 4, 2, 42, 32, 11, 6, 37, 16, 3, 45, 36, 7, 33, 40, 34, 14, 11, 4, 0, 34, 29, 6, 3, 36, 28, 2, 43, 33, 14, 11, 8, 38, 40, 14, 7, 15, 76, 35, 29, 3, 27, 44, 44, 20, 18, 10, 9, 5, 3, 47, 15, 13, 57, 35, 33, 30, 7, 6, 4, 2, 0, 57, 53, 25, 25, 7, 14, 5, 3, 1, 18, 34, 10, 7, 5, 1, 42, 14, 11, 22, 19, 3, 1, 7, 5, 0, 3, 3, 4, 26, 25, 21, 55, 22, 17, 15, 13, 9, 7, 5, 3, 1, 55, 50, 14, 27, 21, 4, 1, 49, 10, 8, 5, 66, 35, 17, 13, 9, 7, 5, 2, 62, 59, 39, 17, 15, 12, 9, 35, 2, 6, 7, 5, 6, 39, 6, 2, 46, 29, 7, 5, 46, 22, 18, 13, 32, 3, 42, 36, 14, 17, 11, 6, 1, 54, 48, 22, 20, 17, 13, 9, 37, 26, 10, 8, 7, 4, 1, 42, 41, 10, 6, 2, 67, 38, 33, 52, 32, 21, 0, 46, 20, 12, 8, 6, 2, 61, 40, 12, 11, 8, 2, 0, 30, 20, 0, 38, 20, 15, 13, 10, 7, 10, 5, 2, 56, 22, 1, 25, 23, 32, 12, 8, 7, 5, 3, 1, 25, 6, 4, 2, 36, 13, 10, 7, 6, 4, 1, 31, 11, 9, 9, 7, 3, 30, 27, 7, 26, 47, 42, 13, 11, 8, 5, 71, 70, 50, 15, 28, 23, 18, 8, 36, 52, 44, 22, 9, 17, 45, 38, 14, 8, 41, 16, 25, 64, 57, 36, 24, 38, 28, 29, 3, 2, 35, 41, 38, 20, 48, 43, 19, 16, 28, 23, 6, 3, 54, 34, 15, 11, 63, 72, 38, 37, 8, 19, 5, 45, 36, 13, 9, 78, 40, 35, 47, 49, 37, 17, 9, 58, 31, 19, 31, 42, 15, 46, 55, 74, 28, 8, 16, 3, 32, 1, 66, 30, 4, 17, 34, 33, 4, 2, 32, 29, 35, 64, 53, 9, 4, 2, 48, 40, 18, 10, 51, 39, 21, 17, 14, 5, 44, 38, 32, 12…

Pipes example

  • What do you think this does?
Code 
df <- df |>
  rename(gender = hh_b02, age = hh_b04) |>
  mutate(boy = gender=="male" & age<15,
    girl = gender=="female" & age<15,
    prime_aged_male = gender=="male" & age>=15 & age<=64,
    prime_aged_female = gender=="female" & age>=15 & age<=64,
    older_male = gender=="male" & age>64,
    older_female = gender=="female" & age>64)

Pipes example

  • What do you think this does?
Code 
df <- df |>
1  rename(gender = hh_b02, age = hh_b04) |>
2  mutate(boy = gender=="male" & age<15,
    girl = gender=="female" & age<15,
    prime_aged_male = gender=="male" & age>=15 & age<=64,
    prime_aged_female = gender=="female" & age>=15 & age<=64,
    older_male = gender=="male" & age>64,
    older_female = gender=="female" & age>64)
1
Renames the variables hh_b02 and hh_b04 to gender and age, respectively (line 2)
2
Creates new variables based on the conditions given (lines 3-8)

Pipes example

  • Let’s look at the resulting variables:
Code 
summary(df[,c("boy", "girl", "prime_aged_male", "prime_aged_female", "older_male", "older_female")])
    boy             girl         prime_aged_male prime_aged_female older_male      older_female   
 Mode :logical   Mode :logical   Mode :logical   Mode :logical     Mode :logical   Mode :logical  
 FALSE:18687     FALSE:18597     FALSE:17396     FALSE:16988       FALSE:23211     FALSE:23081    
 TRUE :4905      TRUE :4995      TRUE :6196      TRUE :6604        TRUE :381       TRUE :511
  • What did I do here?
    • I summarized df based on the names of COLUMNS (variables)
      • I did this by creating a vector of column names (as characters)
    • The resulting variables are logical, or True/False
      • Why?

Pipes example

  • It is TRUE/FALSE because it is evaluating the expression
    • TRUE if the expression is true, FALSE otherwise
  • If we want it to be 0/1, instead, we can simply wrap it in as.numeric()
Code 
df <- df |>
  rename(gender = hh_b02, age = hh_b04) |>
  mutate(boy = as.numeric(gender=="male" & age<15),
    girl = as.numeric(gender=="female" & age<15),
    prime_aged_male = as.numeric(gender=="male" & age>=15 & age<=64),
    prime_aged_female = as.numeric(gender=="female" & age>=15 & age<=64),
    older_male = as.numeric(gender=="male" & age>64),
    older_female = as.numeric(gender=="female" & age>64))

Let’s do some more cleaning

  • What are some other common data cleaning tasks?
  • Some common things:
    • Renaming variables
    • Creating new variables based on existing variables
      • Doing this based on groups
    • Replace values (e.g. replacing missings)
      • i.e. recoding variables

Let’s do some more cleaning

  • What are some other common data cleaning tasks?
  • Some common things:
    • Renaming variables
    • Creating new variables based on existing variables
      • Doing this based on groups
    • Replace values (e.g. replacing missings)
      • i.e. recoding variables

What do we want to do?

  • To do more, we need to look at the survey questionnaire!
    • The data I have uploaded is from Section B
    • You can find the survey questionnaire in the data folder for day 1
  • Here’s the data:
# A tibble: 23,592 × 46
   interview__key y5_hhid     y4_hhid  indidy5 hh_b01           hh_b02 hh_b03_1         hh_b03_2         hh_b04 hh_b05       hh_b06                 hh_b07 hh_b08 hh_b09_1 hh_b0a hh_b0b hh_b10 hh_b11                               hh_b12_1                     hh_b12_2 hh_b13 hh_b14        hh_b15_1                     hh_b15_2 hh_b16 hh_b17            hh_b18 hh_b19             hh_b20              hh_b21_1  hh_b21_2 hh_b21_3 hh_b21_4 hh_b22 hh_b23_1 hh_b23_2 hh_b23_3 hh_b23_4 hh_b24 hh_b25 hh_b26                 hh_b27_2    hh_b27_3 hh_b28                  hh_b29_2    hh_b29_3
   <chr>          <chr>       <chr>      <dbl> <chr>            <chr>  <chr>            <chr>             <dbl> <chr>        <chr>                  <chr>   <dbl> <chr>    <chr>   <dbl>  <dbl> <chr>                                <chr>                           <dbl>  <dbl> <chr>         <chr>                           <dbl>  <dbl> <chr>             <chr>  <chr>              <chr>               <chr>     <chr>    <chr>    <lgl>    <chr>     <dbl>    <dbl> <lgl>    <lgl>    <chr>   <dbl> <chr>                  <chr>       <chr>    <chr>                   <chr>       <chr>   
 1 39-26-37-98    1000-001-01 1000-001       1 **CONFIDENTIAL** male   **CONFIDENTIAL** **CONFIDENTIAL**     74 head         1                      yes        31 yes      yes        NA      0 AGRICULTURE / LIVESTOCK              dead                               NA     63 NO SCHOOL     dead                               NA     56 NO SCHOOL         yes    WIDOW(ER)          <NA>                <NA>      <NA>     <NA>     NA       <NA>         NA       NA NA       NA       <NA>       NA 60                     arusha      meru     BETTER SERVICES/HOUSING arusha      meru    
 2 39-26-37-98    1000-001-01 1000-001       3 **CONFIDENTIAL** female **CONFIDENTIAL** **CONFIDENTIAL**     44 SON/DAUGHTER 3                      yes        31 yes      yes        NA      0 AGRICULTURE / LIVESTOCK              MEMBER OF THE HOUSEHOLD             1     NA <NA>          dead                               NA     20 SOME PRIMARY      yes    divorced           <NA>                <NA>      <NA>     <NA>     NA       <NA>         NA       NA NA       NA       <NA>       NA LIVED HERE SINCE BIRTH <NA>        <NA>     <NA>                    <NA>        <NA>    
 3 39-26-37-98    1000-001-01 1000-001       5 **CONFIDENTIAL** male   **CONFIDENTIAL** **CONFIDENTIAL**     35 SON/DAUGHTER 5                      no          0 yes      no          3      4 PRIVATE SECTOR                       MEMBER OF THE HOUSEHOLD             1     NA <NA>          dead                               NA     12 SOME PRIMARY      yes    separated          <NA>                <NA>      <NA>     <NA>     NA       <NA>         NA       NA NA       NA       <NA>       NA LIVED HERE SINCE BIRTH <NA>        <NA>     <NA>                    <NA>        <NA>    
 4 39-26-37-98    1000-001-01 1000-001       7 **CONFIDENTIAL** male   **CONFIDENTIAL** **CONFIDENTIAL**      9 grandchild   NOT PREVIOUSLY PRESENT yes        31 yes      no          3      0 student                              MEMBER OF THE HOUSEHOLD             5     NA <NA>          LIVING OUTSIDE THE HOUSEHOLD       NA     NA COMPLETED PRIMARY no     <NA>               <NA>                <NA>      <NA>     <NA>     NA       <NA>         NA       NA NA       NA       <NA>       NA <NA>                   <NA>        <NA>     <NA>                    <NA>        <NA>    
 5 04-06-65-04    1000-001-02 1000-001       1 **CONFIDENTIAL** male   **CONFIDENTIAL** **CONFIDENTIAL**     47 head         2                      yes        31 yes      yes        NA      0 AGRICULTURE / LIVESTOCK              LIVING OUTSIDE THE HOUSEHOLD       NA     NA SOME PRIMARY  dead                               NA     20 NO SCHOOL         yes    NEVER MARRIED      <NA>                <NA>      <NA>     <NA>     NA       <NA>         NA       NA NA       NA       <NA>       NA LIVED HERE SINCE BIRTH <NA>        <NA>     <NA>                    <NA>        <NA>    
 6 97-90-78-65    1000-001-03 1000-001       1 **CONFIDENTIAL** male   **CONFIDENTIAL** **CONFIDENTIAL**     36 head         4                      yes        31 yes      yes        NA      1 EMPLOYED (NOT AG): WITHOUT EMPLOYEES LIVING OUTSIDE THE HOUSEHOLD       NA     NA SOME PRIMARY  dead                               NA     17 DON'T KNOW        yes    MONOGAMOUS MARRIED NEVER MARRIED       religious <NA>     <NA>     NA       yes           2       NA NA       NA       no         NA LIVED HERE SINCE BIRTH <NA>        <NA>     <NA>                    <NA>        <NA>    
 7 97-90-78-65    1000-001-03 1000-001       2 **CONFIDENTIAL** female **CONFIDENTIAL** **CONFIDENTIAL**     42 spouse       NOT PREVIOUSLY PRESENT yes        31 yes      yes        NA      0 UNPAID FAMILY WORK                   dead                               NA     21 SOME PRIMARY  LIVING OUTSIDE THE HOUSEHOLD       NA     NA SOME PRIMARY      yes    MONOGAMOUS MARRIED PREVIOUSLY DIVORCED religious <NA>     <NA>     NA       yes           1       NA NA       NA       no         NA 2                      kilimanjaro hai      marriage                kilimanjaro hai     
 8 97-90-78-65    1000-001-03 1000-001       4 **CONFIDENTIAL** female **CONFIDENTIAL** **CONFIDENTIAL**     21 SON/DAUGHTER NOT PREVIOUSLY PRESENT yes        31 yes      yes        NA      0 NO JOB                               LIVING OUTSIDE THE HOUSEHOLD       NA     NA DOES NOT KNOW MEMBER OF THE HOUSEHOLD             2     NA <NA>              yes    NEVER MARRIED      <NA>                <NA>      <NA>     <NA>     NA       <NA>         NA       NA NA       NA       <NA>       NA LIVED HERE SINCE BIRTH <NA>        <NA>     <NA>                    <NA>        <NA>    
 9 97-90-78-65    1000-001-03 1000-001       6 **CONFIDENTIAL** male   **CONFIDENTIAL** **CONFIDENTIAL**      1 SON/DAUGHTER NOT PREVIOUSLY PRESENT yes        31 yes      yes        NA      0 TOO YOUNG                            MEMBER OF THE HOUSEHOLD             1     NA <NA>          MEMBER OF THE HOUSEHOLD             2     NA <NA>              no     <NA>               <NA>                <NA>      <NA>     <NA>     NA       <NA>         NA       NA NA       NA       <NA>       NA <NA>                   <NA>        <NA>     <NA>                    <NA>        <NA>    
10 97-90-78-65    1000-001-03 1000-001       7 **CONFIDENTIAL** female **CONFIDENTIAL** **CONFIDENTIAL**      1 SON/DAUGHTER NOT PREVIOUSLY PRESENT yes        31 yes      no          1      0 TOO YOUNG                            MEMBER OF THE HOUSEHOLD             1     NA <NA>          MEMBER OF THE HOUSEHOLD             2     NA <NA>              no     <NA>               <NA>                <NA>      <NA>     <NA>     NA       <NA>         NA       NA NA       NA       <NA>       NA <NA>                   <NA>        <NA>     <NA>                    <NA>        <NA>    
# ℹ 23,582 more rows

Let’s do some cleaning

  • Two things:
    • Calculate the age of the head
    • Collapse the data to the HOUSEHOLD level, with the following variables:
      • Number of boys/girls
      • Number of prime-aged males/females
      • Number of older males/females
      • The head’s gender

  • How do we do this?

Let’s do some cleaning

  • Let’s start by loading the data again
    • You might want to try this in a new script so you have a self-contained example of data cleaning
    • Go ahead and load libraries and read the .csv (not .dta) data:
Code 
library(tidyverse)
df <- read_csv("day1data/tanzanialsms.csv") #if it's in your WD, you will just have "tanzanialsms.csv"

Back to our task

  • Calculate the age of the head

  • Collapse the data to the HOUSEHOLD level, with the following variables:

    • Number of boys/girls
    • Number of prime-aged males/females
    • Number of older males/females
    • The head’s gender

  • What are the variables we need? (look at the questionnaire)

    • hh_b02 (gender)
    • hh_b04 (age)
    • hh_b05 (relationship to head)
    • y5_hhid (household identifier)

How are we going to do this?

  • Create the new variables
    • Boys, girls, prime-aged males, prime-aged females, older males, older females
    • The head’s gender

  • Collapse the data to the household level
    • We will want to sum the count variables
    • We will want to take the highest value for the head’s gender (since there is only one)

First, rename some variables

Code 
dfhh <- df |>
1  rename(gender = hh_b02, age = hh_b04, relationship = hh_b05) |>
2  select(y5_hhid, gender, age, relationship)
3head(dfhh)
4unique(dfhh$relationship)
1
Renames the variables hh_b02 and hh_b04 to gender and age, respectively, as well as relationship to the head
2
Just keep the variables we want
3
Shows us the first few lines
4
Unique values for relationship 
# A tibble: 6 × 4
  y5_hhid     gender   age relationship
  <chr>       <chr>  <dbl> <chr>       
1 1000-001-01 male      74 head        
2 1000-001-01 female    44 SON/DAUGHTER
3 1000-001-01 male      35 SON/DAUGHTER
4 1000-001-01 male       9 grandchild  
5 1000-001-02 male      47 head        
6 1000-001-03 male      36 head        
 [1] "head"                           "SON/DAUGHTER"                   "grandchild"                     "spouse"                         "OTHER RELATIVE (SPECIFY)"       "OTHER NON- RELATIVES (SPECIFY)" "FATHER/MOTHER"                  "SISTER/BROTHER"                 "STEP SON / DAUGHTER"            "LIVE-IN SERVANT"

Now, create new variables (with new dfhh object)

Code 
dfhh <- dfhh |>
1  mutate(boy = (gender=="male" & age<15),
    girl = (gender=="female" & age<15),
    prime_aged_male = (gender=="male" & age>=15 & age<=64),
    prime_aged_female = (gender=="female" & age>=15 & age<=64),
    older_male = (gender=="male" & age>64),
    older_female = (gender=="female" & age>64),
2    head_male = ifelse(relationship=="head", gender=="male", NA)) |>
3  select(y5_hhid, boy, girl, prime_aged_male, prime_aged_female, older_male, older_female, head_male)
1
Creates new variables based on the conditions given (lines 3-8)
2
Creates head’s mother’s education variable based on the condition given (line 9)
3
Just keep the variables we want

Finally, aggregate to household

Code 
dfhh <- dfhh |>
  group_by(y5_hhid) |>
  summarize(boy = sum(boy, na.rm = TRUE),
    girl = sum(girl, na.rm = TRUE),
    prime_aged_male = sum(prime_aged_male, na.rm = TRUE),
    prime_aged_female = sum(prime_aged_female, na.rm = TRUE),
    older_male = sum(older_male, na.rm = TRUE),
    older_female = sum(older_female, na.rm = TRUE),
    head_male = max(head_male, na.rm = TRUE))
summary(dfhh)
   y5_hhid               boy              girl        prime_aged_male prime_aged_female   older_male       older_female      head_male     
 Length:4709        Min.   : 0.000   Min.   : 0.000   Min.   :0.000   Min.   :0.000     Min.   :0.00000   Min.   :0.0000   Min.   :0.0000  
 Class :character   1st Qu.: 0.000   1st Qu.: 0.000   1st Qu.:1.000   1st Qu.:1.000     1st Qu.:0.00000   1st Qu.:0.0000   1st Qu.:0.0000  
 Mode  :character   Median : 1.000   Median : 1.000   Median :1.000   Median :1.000     Median :0.00000   Median :0.0000   Median :1.0000  
                    Mean   : 1.042   Mean   : 1.061   Mean   :1.316   Mean   :1.402     Mean   :0.08091   Mean   :0.1085   Mean   :0.7297  
                    3rd Qu.: 2.000   3rd Qu.: 2.000   3rd Qu.:2.000   3rd Qu.:2.000     3rd Qu.:0.00000   3rd Qu.:0.0000   3rd Qu.:1.0000  
                    Max.   :10.000   Max.   :11.000   Max.   :8.000   Max.   :8.000     Max.   :2.00000   Max.   :2.0000   Max.   :1.0000

Why is this important for SAE?

  • You will use this type of aggregation all the time in SAE.

  • We often model at an aggregate level

    • Could be the household
    • Could be the district
    • Could be the county
    • Etc.

  • So bookmark this code!

Now it’s your turn!

  • Select some variables from the dataset

  • Create the following household-level dataset:

    • Total household size
    • Proportion of CHILDREN (<15) who are male
    • Proportion of ADULTS (15+) who are female

My code for this

Code 
# create new variables from the clean df data
dfhh <- df |>
  rename(gender = hh_b02, age = hh_b04, relationship = hh_b05) |>
  mutate(male_child = ifelse(age<15, gender=="male", NA),
    female_adult = ifelse(age>=15, gender=="female", NA)) |>
  select(y5_hhid, male_child, female_adult)
# now collapse
dfhh <- dfhh |>
  group_by(y5_hhid) |>
  summarize(prop_children_male = mean(male_child, na.rm = TRUE),
    prop_adult_female = mean(female_adult, na.rm = TRUE),
    hhsize = n()) |>
  ungroup()
summary(dfhh) # note the NAs for prop_children_male! Why is it missing?
   y5_hhid          prop_children_male prop_adult_female     hhsize     
 Length:4709        Min.   :0.0000     Min.   :0.0000    Min.   : 1.00  
 Class :character   1st Qu.:0.0000     1st Qu.:0.5000    1st Qu.: 3.00  
 Mode  :character   Median :0.5000     Median :0.5000    Median : 4.00  
                    Mean   :0.4914     Mean   :0.5313    Mean   : 5.01  
                    3rd Qu.:0.8000     3rd Qu.:0.6667    3rd Qu.: 6.00  
                    Max.   :1.0000     Max.   :1.0000    Max.   :29.00  
                    NA's   :1105

Time dependent: Now it’s your turn, part II!

  • Use your own country data
    • If you don’t have any, use the data I have uploaded!
  • Choose some variables and aggregate them to whatever level you want
    • Raise your hand if you have questions

Visualization with ggplot2

What is ggplot2?

  • ggplot2 is included in the tidyverse package
    • It is a package for creating beautiful graphics
    • Let’s look at some of the basics

  • Let’s start over with our .csv file

Code 
library(tidyverse)
df <- read_csv("day1data/tanzanialsms.csv") # if it's in your folder, you will just have "tanzanialsms.csv"

Basic syntax for ggplot2?

  • The basic syntax is as follows:

ggplot() + geom_point(data = df, aes(x = xvar, y = yvar))

  • Note the use of + and not |>
  • geom_point can be replaced with all sorts of “geoms”!
    • geom_line
    • geom_bar
    • geom_density (this will have no y variable)
    • geom_histogram (same)

Let’s look at an example

  • Let’s start with one that is simple to understand
    • How about the distribution of age in the dataset?
Code 
ggplot() +
  geom_histogram(data = df, aes(x = hh_b04))

Cleaning it up a bit

Code 
ggplot() +
  geom_histogram(data = df, aes(x = hh_b04)) +
  labs(x = "Age", y = "Count")

Cleaning it up even more (my favorite “theme”)

Code 
ggplot() +
  geom_histogram(data = df, aes(x = hh_b04)) +
  labs(x = "Age", y = "Count") +
  theme_bw()
  • You can look at all the built-in themes here1

What if we want to add by gender?

Code 
ggplot() +
  geom_histogram(data = df, aes(x = hh_b04)) +
  labs(x = "Age", y = "Count") +
  theme_bw() +
  facet_wrap(~hh_b02, ncol = 1)

What if we want to add by gender?

Code 
ggplot() +
  geom_histogram(data = df, aes(x = hh_b04)) +
  labs(x = "Age", y = "Count") +
  theme_bw() +
  facet_wrap(~hh_b02, ncol = 2)

Putting them on one plot is simple, too!

Code 
ggplot() +
  geom_histogram(data = df, 
    aes(x = hh_b04, color = hh_b02)) +
  labs(x = "Age", y = "Count") +
  theme_bw()
  • This is a stacked histogram, which I don’t like (hard to see the differences)

Putting them on one plot is simple, too!

Code 
ggplot() +
  geom_histogram(data = df, 
    aes(x = hh_b04, color = hh_b02), 
    position = "identity") +
  labs(x = "Age", y = "Count") +
  theme_bw()
  • This “unstacks” the histogram
  • But now it’s hard to see in a different way!

Fill instead of color?

Code 
ggplot() +
  geom_histogram(data = df, 
    aes(x = hh_b04, fill = hh_b02), 
    position = "identity") +
  labs(x = "Age", y = "Count") +
  theme_bw()
  • Still hard to see both!
Code 
ggplot() +
  geom_histogram(data = df, 
    aes(x = hh_b04, fill = hh_b02), 
    position = "identity",
    alpha = 0.5) +
  labs(x = "Age", y = "Count") +
  theme_bw()
  1. Change opacity with alpha (OUTSIDE the aes())

Cleaning up the legend with scale_fill_brewer

Code 
# Let's use the `scale_fill_brewer` function to clean up the legend (title and fill colors)
ggplot() +
  geom_histogram(data = df, 
    aes(x = hh_b04, fill = hh_b02), 
    position = "identity",
    alpha = 0.5) +
  scale_fill_brewer("Gender", palette = "Accent") +
  labs(x = "Age", y = "Count") +
  theme_bw()
Code 
# Note that difference with `color`
ggplot() +
  geom_histogram(data = df, 
    aes(x = hh_b04, color = hh_b02), 
    position = "identity",
    alpha = 0.5) +
  scale_color_brewer("Gender", palette = "Accent") +
  labs(x = "Age", y = "Count") +
  theme_bw()
  • scale_color_brewer vs. scale_fill_brewer

Finally, changing the location of the legend!

Code 
ggplot() +
  geom_histogram(data = df, 
    aes(x = hh_b04, fill = hh_b02), 
    position = "identity",
    alpha = 0.5) +
  scale_fill_brewer("Gender", palette = "Accent") +
  labs(x = "Age", y = "Count", title = "A. Bottom legend") +
  theme_bw() +
  theme(legend.position = "bottom")


Code 
ggplot() +
  geom_histogram(data = df, 
    aes(x = hh_b04, fill = hh_b02), 
    position = "identity",
    alpha = 0.5) +
  scale_fill_brewer("Gender", palette = "Accent") +
  labs(x = "Age", y = "Count", title = "B. Legend in plot") +
  theme_bw() +
  theme(legend.position = c(0.9, 0.8))

Just FYI, the R Color Brewer palettes

  • Here you can see all the color palettes

  • Some of these are for continuous variables

  • The middle section is mostly for categorical variables (like gender)

  • Choose color by changing the PALETTE NAME:

Code 
ggplot() +
  geom_density(data = df, 
    aes(x = hh_b04, fill = hh_b02),
    alpha = 0.5) +
  scale_fill_brewer("Gender", palette = "PALETTE NAME") +
  labs(x = "Age", y = "Density") +
  theme_bw() +
  theme(legend.position = "bottom")

Let’s look at another example

  • In this example, we’ll also practice aggregating to higher levels (again!)
    • Let’s look at the proportion of people in agriculture and in education BY AGE GROUP
    • We are going to use the following variables:
      • hh_b04 (age)
      • hh_b11 (main occupation)
Code 
unique(df$hh_b11)
 [1] "AGRICULTURE / LIVESTOCK"              "PRIVATE SECTOR"                       "student"                              "EMPLOYED (NOT AG): WITHOUT EMPLOYEES" "UNPAID FAMILY WORK"                   "NO JOB"                               "TOO YOUNG"                            NA                                     "EMPLOYED (NOT AG): WITH EMPLOYEES"    "tourism"                              "JOB SEEKERS"                          "disabled"                             "PAID FAMILY WORK"                     "goverment"                            "NGO/RELIGIOUS"                        "parastatal"                           "mining"                               "fishing"


- The relevant two values are “AGRICULTURE / LIVESTOCK” and “student”

First, we need to create age groups

  • Let’s create age groups using the cut function
    • This will create a factor variable
Code 
df <- df |>
1  mutate(age_groups = cut(hh_b04, breaks = seq(from = 0, to = max(df$hh_b04), by = 5)))
head(df$age_groups)
1
Creates a new variable age_groups based on the conditions given (line 3) 
[1] (70,75] (40,45] (30,35] (5,10]  (45,50] (35,40]
Levels: (0,5] (5,10] (10,15] (15,20] (20,25] (25,30] (30,35] (35,40] (40,45] (45,50] (50,55] (55,60] (60,65] (65,70] (70,75] (75,80] (80,85] (85,90] (90,95]
  • The seq function creates a sequence of numbers from 0 to the maximum age in the dataset, in increments of 5

Now, let’s create the occupation variables

Code 
df <- df |>
  mutate(ag = ifelse(hh_b11 == "AGRICULTURE / LIVESTOCK", 1, 0),
    ed = ifelse(hh_b11 == "student", 1, 0))
  • Now aggregate to age_groups
Code 
dfgroups <- df |>
1  filter(!is.na(age_groups)) |>
2  group_by(age_groups) |>
3  summarize(ag = mean(ag, na.rm = TRUE),
    ed = mean(ed, na.rm = TRUE)) |>
4  ungroup()
1
Removes missing values
2
Groups by age_groups
3
Calculates the mean of ag and ed (removing missing values)
4
Ungroups the data frame

Now we can plot them

Code 
ggplot() +
  geom_point(data = dfgroups, 
    aes(x = age_groups, y = ag)) +
  labs(x = "Age group", 
    y = "Proportion of respondents in category",
    title = "Agriculture") +
  theme_bw()



Code 
ggplot() +
  geom_point(data = dfgroups, 
    aes(x = age_groups, y = ed)) +
  labs(x = "Age group", 
    y = "Proportion of respondents in category",
    title = "Student") +
  theme_bw()

But what if we want to plot them on the same graph?


  • This is a little more complicated!
  • Look what happens here:
Code 
ggplot() +
  geom_point(data = dfgroups, 
    aes(x = age_groups, y = ag)) +
  geom_point(data = dfgroups, 
    aes(x = age_groups, y = ed)) +
  labs(x = "Age group", 
    y = "Proportion of respondents in category") +
  theme_bw()
  • Do you see the problem?




But what if we want to plot them on the same graph?


  • We can specify individual colors, OUTSIDE the aes().
Code 
ggplot() +
  geom_point(data = dfgroups, 
    aes(x = age_groups, y = ag), color = "navy") +
  geom_point(data = dfgroups, 
    aes(x = age_groups, y = ed), color = "orange") +
  labs(x = "Age group", 
    y = "Proportion of respondents in category") +
  theme_bw()
  • Still a problem! What is it?




Here’s the code. Let’s discuss!

Code 
library(RColorBrewer)
colors <- brewer.pal(3, "Set2")
colors
[1] "#66C2A5" "#FC8D62" "#8DA0CB"


Code 
ggplot() +
  geom_point(data = dfgroups, 
    aes(x = age_groups, y = ag, color = "Ag")) +
  geom_point(data = dfgroups, 
    aes(x = age_groups, y = ed, color = "Educ.")) +
  labs(x = "Age group", 
    y = "Proportion of respondents in category") +
  scale_color_manual("Occupation:", 
    values = c("Ag" = colors[1], "Educ." = colors[2])) +
  theme_bw()

How does it look?

Code 
ggplot() +
  geom_point(data = dfgroups, 
    aes(x = age_groups, y = ag, color = "Ag")) +
  geom_point(data = dfgroups, 
    aes(x = age_groups, y = ed, color = "Educ.")) +
  labs(x = "Age group", 
    y = "Proportion of respondents in category") +
  scale_color_manual("Occupation:", 
    values = c("Ag" = colors[1], "Educ." = colors[2])) +
  theme_bw()
Code 
ggplot() +
  geom_point(data = dfgroups, 
    aes(x = age_groups, y = ag, color = "Ag")) +
  geom_point(data = dfgroups, 
    aes(x = age_groups, y = ed, color = "Educ.")) +
  labs(x = "Age group", 
    y = "Proportion of respondents in category") +
  scale_color_manual("Occupation:", 
    values = c("Ag" = colors[1], "Educ." = colors[2])) +
  theme_bw() +
  theme(legend.position = c(0.9, 0.8))

What about doing line graphs?

  • We have to make a change! We cannot do a line graph with a factor variable!
Code 
ggplot() +
1  geom_line(data = dfgroups, aes(x = as.numeric(age_groups), y = ag, color = "Ag")) +
  geom_line(data = dfgroups, aes(x = as.numeric(age_groups), y = ed, color = "Educ.")) +
2  scale_x_continuous(breaks = as.numeric(unique(dfgroups$age_groups)), labels = unique(dfgroups$age_groups)) +
  labs(x = "Age group", y = "Proportion of respondents in category") +
  scale_color_manual("Occupation:", values = c("Ag" = colors[1], "Educ." = colors[2])) +
  theme_bw() +
  theme(legend.position = c(0.9, 0.8))
1
Turn it into a numeric variable.
2
Change the x-axis to the numeric values and label it with the original values.

What about doing line graphs?

Finally, the points and lines together

Code 
ggplot() +
  geom_point(data = dfgroups, aes(x = as.numeric(age_groups), y = ag, color = "Ag")) +
  geom_line(data = dfgroups, aes(x = as.numeric(age_groups), y = ag, color = "Ag")) +
  geom_point(data = dfgroups, aes(x = as.numeric(age_groups), y = ed, color = "Educ.")) +
  geom_line(data = dfgroups, aes(x = as.numeric(age_groups), y = ed, color = "Educ.")) +
  scale_x_continuous(breaks = as.numeric(unique(dfgroups$age_groups)), labels = unique(dfgroups$age_groups)) +
  labs(x = "Age group", y = "Proportion of respondents in category") +
  scale_color_manual("Occupation:", values = c("Ag" = colors[1], "Educ." = colors[2])) +
  theme_bw() +
  theme(legend.position = c(0.9, 0.8))

Finally, the points and lines together

Now it’s your turn!

  • Select some variables from the dataset

  • You need to create the following:

    • A graph with only one variable (e.g. density/histogram)
    • A graph with two variables (e.g. point or line)

Time dependent: Now it’s your turn, part II!

  • Use your own country data
    • If you don’t have any, use the data I have uploaded!
  • Create two nice visualizations using your country data