# Summary statistics

Summary statistics of data tables.

## Summary statistics

Mean, median, SD, and count are often data summaries we need to calculate, usually after grouping data based on another column. `grafify` has a simple function `table_summary` that gives these values for one (or more) quantitative parameters (columns) of a data table after grouping by one (or more columns).

This function uses the base R function `aggregate`.

### One grouping factor

``````table_summary(data = data_t_pratio,   #data table
Ycol = "Cytokine",      #quantitative variable
ByGroup = "Genotype")   #grouping variable``````
``````#>   Genotype Cytokine.Mean Cytokine.Median Cytokine.SD Cytokine.Count
#> 1       KO      5.913191        4.513057    6.325244             33
#> 2       WT      2.985028        2.130989    2.690373             33``````

### More than one grouping factor

This example uses two grouping variables.

``````table_summary(data = data_2w_Festing, #data table
Ycol = "GST",           #quantitative variable
ByGroup = c("Strain",
"Treatment"))   #grouping variables``````
``````#>    Strain Treatment GST.Mean GST.Median    GST.SD GST.Count
#> 1 129/Ola   Control    526.5      526.5 112.42998         2
#> 2     A/J   Control    508.5      508.5 142.12846         2
#> 3  BALB/C   Control    504.5      504.5 115.25841         2
#> 4     NIH   Control    604.0      604.0 226.27417         2
#> 5 129/Ola   Treated    742.5      742.5  33.23402         2
#> 6     A/J   Treated    929.0      929.0 103.23759         2
#> 7  BALB/C   Treated    703.5      703.5 111.01576         2
#> 8     NIH   Treated    722.5      722.5 153.44217         2``````

### More than one quantitative variable

This example uses `mtcars` data.

``````table_summary(data = mtcars,      #data table
Ycol = c("mpg",
"disp"),   #quantitative variables
ByGroup = c("gear", #grouping variables
"am")) ``````
``````#>   gear am mpg.Mean mpg.Median   mpg.SD mpg.Count disp.Mean
#> 1    3  0 16.10667      15.50 3.371618        15  326.3000
#> 2    4  0 21.05000      21.00 3.069745         4  155.6750
#> 3    4  1 26.27500      25.05 5.414465         8  106.6875
#> 4    5  1 21.38000      19.70 6.658979         5  202.4800
#>   disp.Median   disp.SD disp.Count
#> 1      318.00  94.85274         15
#> 2      157.15  13.97888          4
#> 3       93.50  37.16298          8
#> 4      145.00 115.49064          5``````