Inspection, Comparison and Visualisation of Data Frames

tidy corrrelation

library(inspectdf)


inspect_cor(iris)

## # A tibble: 6 × 7
##   col_1        col_2          corr  p_value  lower   upper pcnt_nna
##   <chr>        <chr>         <dbl>    <dbl>  <dbl>   <dbl>    <dbl>
## 1 Petal.Width  Petal.Length  0.963 1.73e-31  0.949  0.973       100
## 2 Petal.Length Sepal.Length  0.872 4.13e-26  0.827  0.906       100
## 3 Petal.Width  Sepal.Length  0.818 3.51e-23  0.757  0.865       100
## 4 Petal.Length Sepal.Width  -0.428 2.05e- 7 -0.551 -0.288       100
## 5 Petal.Width  Sepal.Width  -0.366 9.04e- 6 -0.497 -0.219       100
## 6 Sepal.Width  Sepal.Length -0.118 1.54e- 1 -0.273  0.0435      100

Summary and comparison of memory usage of dataframe columns

inspect_imb(iris)

## # A tibble: 1 × 4
##   col_name value   pcnt   cnt
##   <chr>    <chr>  <dbl> <int>
## 1 Species  setosa  33.3    50

inspect_cat(iris)

## # A tibble: 1 × 5
##   col_name   cnt common common_pcnt levels          
##   <chr>    <int> <chr>        <dbl> <named list>    
## 1 Species      3 setosa        33.3 <tibble [3 × 3]>

inspect_mem(iris)

## # A tibble: 5 × 4
##   col_name     bytes size     pcnt
##   <chr>        <int> <chr>   <dbl>
## 1 Sepal.Length  1248 1.22 Kb    20
## 2 Sepal.Width   1248 1.22 Kb    20
## 3 Petal.Length  1248 1.22 Kb    20
## 4 Petal.Width   1248 1.22 Kb    20
## 5 Species       1248 1.22 Kb    20

summary missing value

inspect_na(iris)

## # A tibble: 5 × 3
##   col_name       cnt  pcnt
##   <chr>        <int> <dbl>
## 1 Sepal.Length     0     0
## 2 Sepal.Width      0     0
## 3 Petal.Length     0     0
## 4 Petal.Width      0     0
## 5 Species          0     0

summary numeric columns

inspect_num(iris)

## # A tibble: 4 × 10
##   col_name       min    q1 median  mean    q3   max    sd pcnt_na hist        
##   <chr>        <dbl> <dbl>  <dbl> <dbl> <dbl> <dbl> <dbl>   <dbl> <named list>
## 1 Sepal.Length   4.3   5.1   5.8   5.84   6.4   7.9 0.828       0 <tibble>    
## 2 Sepal.Width    2     2.8   3     3.06   3.3   4.4 0.436       0 <tibble>    
## 3 Petal.Length   1     1.6   4.35  3.76   5.1   6.9 1.77        0 <tibble>    
## 4 Petal.Width    0.1   0.3   1.3   1.20   1.8   2.5 0.762       0 <tibble>

summary type

inspect_types(iris)

## # A tibble: 2 × 4
##   type      cnt  pcnt col_name    
##   <chr>   <int> <dbl> <named list>
## 1 numeric     4    80 <chr [4]>   
## 2 factor      1    20 <chr [1]>

graphical inspection of dataframe

show_plot(inspect_cor(iris))