Memory usage of dataframe columns

Illustrative data: starwars

The examples below make use of the starwars and storms data from the dplyr package

# some example data
data(starwars, package = "dplyr")
data(storms, package = "dplyr")

For illustrating comparisons of dataframes, use the starwars data and produce two new dataframes star_1 and star_2 that randomly sample the rows of the original and drop a couple of columns.

library(dplyr)
star_1 <- starwars %>% sample_n(50)
star_2 <- starwars %>% sample_n(50) %>% select(-1, -2)

Illustrative data: starwars

The examples below make use of the starwars and storms data from the dplyr package

# some example data
data(starwars, package = "dplyr")
data(storms, package = "dplyr")

For illustrating comparisons of dataframes, use the starwars data and produce two new dataframes star_1 and star_2 that randomly sample the rows of the original and drop a couple of columns.

library(dplyr)
star_1 <- starwars %>% sample_n(50)
star_2 <- starwars %>% sample_n(50) %>% select(-1, -2)

inspect_mem() for a single dataframe

To explore the memory usage of the columns in a data frame, use inspect_mem(). The command returns a tibble containing the size of each column in the dataframe.

library(inspectdf)
inspect_mem(starwars)

## # A tibble: 14 × 4
##    col_name   bytes size        pcnt
##    <chr>      <int> <chr>      <dbl>
##  1 films      20008 19.54 Kb  36.0  
##  2 starships   7424 7.25 Kb   13.4  
##  3 name        6280 6.13 Kb   11.3  
##  4 vehicles    5944 5.8 Kb    10.7  
##  5 homeworld   3608 3.52 Kb    6.49 
##  6 species     2952 2.88 Kb    5.31 
##  7 skin_color  2656 2.59 Kb    4.78 
##  8 eye_color   1608 1.57 Kb    2.89 
##  9 hair_color  1384 1.35 Kb    2.49 
## 10 sex          976 976 bytes  1.76 
## 11 gender       872 872 bytes  1.57 
## 12 mass         744 744 bytes  1.34 
## 13 birth_year   744 744 bytes  1.34 
## 14 height       400 400 bytes  0.719

A barplot can be produced by passing the result to show_plot():

inspect_mem(starwars) %>% show_plot()

inspect_mem() for two dataframes

When a second dataframe is provided, inspect_mem() will create a dataframe comparing the size of each column for both input dataframes. The summaries for the first and second dataframes are show in columns with names appended with _1 and _2, respectively.

inspect_mem(star_1, star_2)

## # A tibble: 14 × 5
##    col_name   size_1    size_2    pcnt_1 pcnt_2
##    <chr>      <chr>     <chr>      <dbl>  <dbl>
##  1 films      12.21 Kb  11.27 Kb  36.2    39.2 
##  2 starships  4.7 Kb    4.12 Kb   13.9    14.3 
##  3 name       3.54 Kb   NA        10.5    NA   
##  4 vehicles   3.47 Kb   3.32 Kb   10.3    11.5 
##  5 homeworld  2.24 Kb   2.36 Kb    6.65    8.21
##  6 species    1.7 Kb    1.71 Kb    5.05    5.95
##  7 skin_color 1.65 Kb   1.88 Kb    4.89    6.52
##  8 eye_color  1.11 Kb   1 Kb       3.29    3.48
##  9 hair_color 856 bytes 1 Kb       2.48    3.48
## 10 sex        616 bytes 680 bytes  1.78    2.31
## 11 gender     576 bytes 576 bytes  1.67    1.96
## 12 mass       448 bytes 448 bytes  1.30    1.52
## 13 birth_year 448 bytes 448 bytes  1.30    1.52
## 14 height     248 bytes NA         0.718  NA

inspect_mem(star_1, star_2) %>% show_plot()