In Rkabacoff/qacr: Functions to Facilitate Data Science Projects

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
library(knitr)
library(kableExtra)

library(qacr)
df <- data.frame(sex=c(1,2,1,2,2,2),

                 race=c("b", "w", "a", "b", "w", "h"),
                 outcome=c("better", "worse", "same", "same", "better", "worse"),
                 Q1=c(20, 30, 44, 15, 50, 99),
                 Q2=c(15, 23, 18, 86, 99, 35),
                 age=c(12, 20, 33, 55, 30, 100),
                 rating =c(1,2,5,3,4,5))

The recodes() functions makes it very easy to recode one or more variables in the your data frame. The format is

newdata <- recodes(olddata, variables, from values, to values)

Original dataset

Consider the following data set (below). Lets make the following changes.

kbl(df) %>% kable_styling(bootstrap_options = "striped", full_width = F, position = "left")

sex

For sex, set 1 to "Male" and 2 to "Female".

df <- recodes(data=df, vars="sex", 
               from=c(1,2), to=c("Male", "Female"))

kbl(df) %>% kable_styling(bootstrap_options = "striped", full_width = F, position = "left")

race

Recode race to "White" vs. "Other".

df <- recodes(data=df, vars="race", 
              from=c("w", "b", "a", "h"), 
              to=c("White", "Other", "Other", "Other"))

kbl(df) %>% kable_styling(bootstrap_options = "striped", full_width = F, position = "left")

outcome

Recode outcome to 1 (better) vs. 0 (not better).

df <- recodes(data=df, vars="outcome", 
              from=c("better", "same", "worse"), 
              to=c(1, 0, 0))

kbl(df) %>% kable_styling(bootstrap_options = "striped", full_width = F, position = "left")

Q1 and Q2

For Q1 and Q2 set values of 86 and 99 to missing.

df <- recodes(data=df, vars=c("Q1", "Q2"), 
              from=c(86, 99), to=NA)

kbl(df) %>% kable_styling(bootstrap_options = "striped", full_width = F, position = "left")

age

For age, set values

• less than 20 or greater than 90 to missing,
• 20 <= age <= 30 to "Younger",
• 30 < age <= 50 to "Middle Aged", and
• 50 < age <= 90 to "Older".

You can use expressions in your from fields. When they are TRUE, the corresponding to values will be applied. We will use the dollar sign (\$) to represent the variable (age in this case). The symbols ( \|, \& ) mean OR and AND respectively.

df <- recodes(data=df, vars="age", 
              from=c("$ <   20 | $ >  90", 
                     "$ >=  20 & $ <= 30",
                     "$ >   30 & $ <= 50",
                     "$ >   50 & $ <= 90"), 
              to=c(NA, "Younger", "Middle Aged", "Older"))

We can also write this as

df <- recodes(data=df, vars="age", 
              from=c("$ < 20", "$ <= 30", "$ <= 50", "$ <= 90", "$ > 90"), 
              to=  c(NA, "Younger", "Middle Aged", "Older", "NA"))

This works because once the age value for an observations meets a criteria that is TRUE (working left to right), it is recoded. It isn't changed again by later criteria in the same recodes statement.

kbl(df) %>% kable_styling(bootstrap_options = "striped", full_width = F, position = "left")

rating

Finally, for the rating variable, reverse the scoring so that 1 to 5 becomes 5 to 1.

df <- recodes(data=df, vars="rating", from=1:5, to=5:1)

kbl(df) %>% kable_styling(bootstrap_options = "striped", full_width = F, position = "left")

Note

Remember that recodes returns a data frame, not a variable.

• df <- recodes(data=df, vars="rating", from=1:5, to=5:1) is correct.

• df$rating <- recodes(data=df, vars="rating", from=1:5, to=5:1) is not.

This allows you to apply the same recoding scheme to more than one variable at a time (e.g., Q1 and Q2 above).

And that's it (APPLAUSE, APPLAUSE)!

Rkabacoff/qacr documentation built on March 20, 2021, 3:03 p.m.