spss_swap: Swaps labels and col names from a .sav (SPSS) matrix

In Buedenbender/datscience: Data and Science Utility Functions

Swaps labels and col names from a .sav (SPSS) matrix

Description

In many situations it can be useful to have the ability to replace the uninformative variable names (colnames) from a SPSS matrix (e.g. SD02, SD08_02) with their respective label attribute (e.g., "Gender/Sex" or "Age 15-25"). This function utilizes the utility function clean_names to convert the labels from SPSS to proper variable names (e.g.,"gender_sex" or "age_15_25") and sets them as new column names

Usage

spss_swap(
  df,
  repl_umlaut = TRUE,
  old_itemnames = c("remove", "prepend", "append")
)

Arguments

df	tibble read in the read_sav from haven
repl_umlaut	Default is TRUE. If provided True it replaces umlauts (vowel mutations) like ä, ö, ü and ß with respective ae, oe, ue, and ss
old_itemnames	Options are "prepend", "append" or, "remove". Default is "prepend" With "prepend" the new item names will be prepended by the old item names. E.g., the old item name was "q0003" and the description "Gender" the new item name will be "q0003_gender"

Value

A tibble with more human readable names (old labels as names)

Author(s)

Friedrich-Samuel Taubitz & Bjoern Buedenbender

Examples

## Not run: 
datscience::spss_swap(df_sav)

## End(Not run)

Buedenbender/datscience documentation built on Nov. 21, 2022, 11:14 a.m.