Learning how to create a data codebook

Load Packages

Import and Export SPSS, STATA, and SAS files

if(!require(haven)){
  install.packages("haven", dependencies = TRUE)
  library(haven)}

Loading required package: haven

A collection of packages that makes it easy to tidy, clean, and work with data.

if(!require(tidyverse)){
  install.packages("tidyverse", dependencies = TRUE)
  library(tidyverse)}

Loading required package: tidyverse

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.2     ✔ readr     2.1.4
✔ forcats   1.0.0     ✔ stringr   1.5.0
✔ ggplot2   3.4.2     ✔ tibble    3.2.1
✔ lubridate 1.9.2     ✔ tidyr     1.3.0
✔ purrr     1.0.1     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

A collection of tools to quickly and neatly summarize the data.

if(!require(summarytools)){
  install.packages("summarytools", dependencies = TRUE)
  library(summarytools)}

Loading required package: summarytools

Warning in fun(libname, pkgname): couldn't connect to display ":0"

system might not have X11 capabilities; in case of errors when using dfSummary(), set st_options(use.x11 = FALSE)


Attaching package: 'summarytools'

The following object is masked from 'package:tibble':

    view

Import Data

dataset <- read_sav ("Harry Potter Data.sav")

Selecting Key Variables

(dataset %>%
  select(CoinFlip, FFM_44, Potter28) -> newVariable)

# A tibble: 122 × 3
   CoinFlip  FFM_44                         Potter28    
   <dbl+lbl> <dbl+lbl>                      <dbl+lbl>   
 1 1 [Heads] 2 [Disagree a little]          2 [Imitated]
 2 2 [Tails] 4 [Agree a little]             5 [Liked]   
 3 1 [Heads] 5 [Agree Strongly]             5 [Liked]   
 4 2 [Tails] 5 [Agree Strongly]             3 [Trusted] 
 5 1 [Heads] 5 [Agree Strongly]             3 [Trusted] 
 6 2 [Tails] 2 [Disagree a little]          3 [Trusted] 
 7 2 [Tails] 3 [Neither agree nor diasgree] 3 [Trusted] 
 8 1 [Heads] 2 [Disagree a little]          3 [Trusted] 
 9 1 [Heads] 4 [Agree a little]             3 [Trusted] 
10 1 [Heads] 2 [Disagree a little]          3 [Trusted] 
# ℹ 112 more rows

Create Codebook

print(dfSummary(newVariable, graph.magnif = .75), method = 'render')

Warning in png(png_loc <- tempfile(fileext = ".png"), width = 150 *
graph.magnif, : unable to open connection to X11 display ''

Warning in png(png_loc <- tempfile(fileext = ".png"), width = 150 *
graph.magnif, : unable to open connection to X11 display ''

Warning in png(png_loc <- tempfile(fileext = ".png"), width = 150 *
graph.magnif, : unable to open connection to X11 display ''

Data Frame Summary

newVariable

Dimensions: 122 x 3
Duplicates: 82

CoinFlip [haven_labelled, vctrs_vctr, double]

Flip a coin. Is it heads or tails?

Min : 1
Mean : 1.3
Max : 2

1	:	83	(	70.3%	)
2	:	35	(	29.7%	)

118 (96.7%)

4 (3.3%)

FFM_44 [haven_labelled, vctrs_vctr, double]

I see Myself as Someone Who..... - Is sophisticated in art, music, or literature

Mean (sd) : 3.3 (1.2)
min ≤ med ≤ max:
1 ≤ 3 ≤ 5
IQR (CV) : 2 (0.4)

1	:	7	(	7.2%	)
2	:	22	(	22.7%	)
3	:	20	(	20.6%	)
4	:	27	(	27.8%	)
5	:	21	(	21.6%	)

97 (79.5%)

25 (20.5%)

Potter28 [haven_labelled, vctrs_vctr, double]

Which would you rather be:

Mean (sd) : 3.3 (1)
min ≤ med ≤ max:
1 ≤ 3 ≤ 6
IQR (CV) : 0 (0.3)

1	:	5	(	5.0%	)
2	:	3	(	3.0%	)
3	:	69	(	68.3%	)
4	:	9	(	8.9%	)
5	:	10	(	9.9%	)
6	:	5	(	5.0%	)

101 (82.8%)

21 (17.2%)

Generated by summarytools 1.0.1 (R version 4.3.0)
2023-07-09