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