Tidiers for data.frame objects

Data frame tidiers are deprecated and will be removed from an upcoming release of broom.

Usage

# S3 method for class 'data.frame'
tidy(x, ..., na.rm = TRUE, trim = 0.1)

# S3 method for class 'data.frame'
augment(x, data, ...)

# S3 method for class 'data.frame'
glance(x, ...)

Source

Skew and Kurtosis functions are adapted from implementations in the moments package:
Lukasz Komsta and Frederick Novomestky (2015). moments: Moments, cumulants, skewness, kurtosis and related tests. R package version 0.14.
https://CRAN.R-project.org/package=moments

Arguments

x: A data.frame
...: Additional arguments for other methods.
na.rm: a logical value indicating whether NA values should be stripped before the computation proceeds.
trim: the fraction (0 to 0.5) of observations to be trimmed from each end of x before the mean is computed. Passed to the trim argument of mean
data: data, not used

Value

tidy.data.frame produces a data frame with one row per original column, containing summary statistics of each:

column: name of original column
n: Number of valid (non-NA) values
mean: mean
sd: standard deviation
median: median
trimmed: trimmed mean, with trim defaulting to .1
mad: median absolute deviation (from the median)
min: minimum value
max: maximum value
range: range
skew: skew
kurtosis: kurtosis
se: standard error

glance returns a one-row data.frame with

nrow: number of rows
ncol: number of columns
complete.obs: number of rows that have no missing values
na.fraction: fraction of values across all rows and columns that are missing

Details

These perform tidy summaries of data.frame objects. tidy produces summary statistics about each column, while glance simply reports the number of rows and columns. Note that augment.data.frame will throw an error.

Author

David Robinson, Benjamin Nutter

Examples


td <- tidy(mtcars)
#> Warning: Data frame tidiers are deprecated and will be removed in an upcoming release of broom.
td
#> # A tibble: 11 × 13
#>    column     n    mean      sd median trimmed    mad   min    max  range
#>    <chr>  <dbl>   <dbl>   <dbl>  <dbl>   <dbl>  <dbl> <dbl>  <dbl>  <dbl>
#>  1 mpg       32  20.1     6.03   19.2   19.7    3.65  10.4   33.9   23.5 
#>  2 cyl       32   6.19    1.79    6      6.23   2      4      8      4   
#>  3 disp      32 231.    124.    196.   223.    94.8   71.1  472    401.  
#>  4 hp        32 147.     68.6   123    141.    52     52    335    283   
#>  5 drat      32   3.60    0.535   3.70   3.58   0.475  2.76   4.93   2.17
#>  6 wt        32   3.22    0.978   3.32   3.15   0.517  1.51   5.42   3.91
#>  7 qsec      32  17.8     1.79   17.7   17.8    0.955 14.5   22.9    8.4 
#>  8 vs        32   0.438   0.504   0      0.423  0      0      1      1   
#>  9 am        32   0.406   0.499   0      0.385  0      0      1      1   
#> 10 gear      32   3.69    0.738   4      3.62   1      3      5      2   
#> 11 carb      32   2.81    1.62    2      2.65   1      1      8      7   
#> # ℹ 3 more variables: skew <dbl>, kurtosis <dbl>, se <dbl>

glance(mtcars)
#> Warning: Data frame tidiers are deprecated and will be removed in an upcoming release of broom.
#> # A tibble: 1 × 4
#>    nrow  ncol complete.obs na.fraction
#>   <int> <int>        <int>       <dbl>
#> 1    32    11           32           0

library(ggplot2)
# compare mean and standard deviation
ggplot(td, aes(mean, sd)) + geom_point() +
     geom_text(aes(label = column), hjust = 1, vjust = 1) +
     scale_x_log10() + scale_y_log10() + geom_abline()