R: Summary and comparison of memory usage of dataframe columns

inspect_mem {inspectdf} | R Documentation

## Summary and comparison of memory usage of dataframe columns

### Description

For a single dataframe, summarise the memory usage in each column. If two dataframes are supplied, compare memory usage for columns appearing in both dataframes. For grouped dataframes, summarise the memory usage separately for each group.

### Usage

    inspect_mem(df1, df2 = NULL)

### Arguments

`df1` | A data frame.
`df2` | An optional second data frame with which to comparing memory usage. Defaults to `NULL`.

### Details

For a single dataframe, the tibble returned contains the columns:

- `col_name`, a character vector containing column names of `df1`.

- `bytes`, integer vector containing the number of bytes in each column of `df1`.

- `size`, a character vector containing display-friendly memory usage of each column.

- `pcnt`, the percentage of the dataframe's total memory footprint used by each column.

For a pair of dataframes, the tibble returned contains the columns:

- `col_name`, a character vector containing column names of `df1` and `df2`.

- `size_1`, `size_2`, a character vector containing memory usage of each column in each of `df1` and `df2`.

- `pcnt_1`, `pcnt_2`, the percentage of total memory usage of each column within each of `df1` and `df2`.

For a grouped dataframe, the tibble returned is as for a single dataframe, but where the first `k` columns are the grouping columns. There will be as many rows in the result as there are unique combinations of the grouping variables.

### Value

A tibble summarising and comparing the columnwise memory usage for one or a pair of data frames.

### Author(s)

Alastair Rushworth

### See Also

`show_plot`

### Examples

    # Load dplyr for starwars data & pipe
    library(dplyr)

    # Single dataframe summary
    inspect_mem(starwars)

    # Paired dataframe comparison
    inspect_mem(starwars, starwars[1:20, ])

    # Grouped dataframe summary
    starwars %>% group_by(gender) %>% inspect_mem()

[Package inspectdf version 0.0.11 Index]