Converting long format flat file to wide in R - r

Question

I have a household and member dataset in one long flat format. There is a fixed number of members and each corresponds to a column. For simplicity, assume 2 members per household and assume 2 questions are asked for the members- age (Q1), gender(Q2).
The file format looks as given below:
HHID, MEM_ID_1, MEM_ID_2, AGE_1, AGE_2, GENDER_1, GENDER_2
1 1 2 50 45 M F
And I want to convert it to the following format:
HHID MEM_ID AGE GENDER
1 1 50 M
1 2 45 F

Answer 1

Let's say our data frame is test
dput(test)
structure(list(HHID = 1L, MEM_ID_1 = 1L, MEM_ID_2 = 2L, AGE_1 = 50L,
AGE_2 = 45L, GENDER_1 = structure(1L, .Label = "Male", class = "factor"),
GENDER_2 = structure(1L, .Label = "Female", class = "factor")), class = "data.frame", row.names = c(NA,
-1L))
You could try the reshape function on this data frame as below:
reshape(test, direction = "long",
varying = list(c("MEM_ID_1","MEM_ID_2"), c("AGE_1","AGE_2"), c( "GENDER_1","GENDER_2")),
v.names = c("MEM_ID","AGE","GENDER"),
idvar = 'HHID')
The reshape() function comes from the base R. Broadly speaking, it can simultaneously melt over multiple sets of variables, by using the varying parameter and setting the direction to long.
For example in your case we have a list of three vectors of variable names to the varying argument:
varying = list(c("MEM_ID_1","MEM_ID_2"), c("AGE_1","AGE_2"), c( "GENDER_1","GENDER_2"))
The output is below:
HHID time MEM_ID AGE GENDER
1.1 1 1 1 50 Male
1.2 1 2 2 45 Female

Answer 2

You can use tidyr::gather(), tidyr::separate(), and tidyr::spread() in order. Here household is the name of your data frame.
library(tidyverse)
1. gather
First, tidyr::gather(). Then you can get the below result.
household %>%
gather(-HHID, key = domestic, value = value)
#> HHID domestic value
#> 1 1 MEM_ID_1 1
#> 2 1 MEM_ID_2 2
#> 3 1 AGE_1 50
#> 4 1 AGE_2 45
#> 5 1 GENDER_1 M
#> 6 1 GENDER_2 F
Now all you have to do is
separate domestic column at _[0-9]: In regular expression, _(?=[0-9])
Changing the format into the wide format, you can see the output you want.
2. Conclusion: entire code
household %>%
gather(-HHID, key = domestic, value = value) %>% # long data
separate(domestic, into = c("domestic", "vals"), sep = "_(?=[0-9])") %>% # separate the digit
spread(domestic, value) %>% # wide format
select(HHID, MEM_ID, AGE, GENDER, -vals) # just arranging columns, and excluding needless column
#> HHID MEM_ID AGE GENDER
#> 1 1 1 50 M
#> 2 1 2 45 F