In sachserf/datawoman: There is no DATA W/O MANipulation

library(datawoman)

Example 1:

• check classes and frequency of slightly different dataframes before conducting a merge/join/combine

df1 <- df2 <- df3 <- df4 <- iris[1:4]
df1$Petal.Width <- as.character(df1$Sepal.Width)
df2$Sepal.Width <- NULL
df3 <- df4[1:5,]
comcomcol(df1, df2, df3, df4)

Example 2

• compare consistency of mean for all numeric variables of iris data by increasing sample size

df1 <- df2 <- df3 <- df4 <- iris[1:4]
n <- 1:nrow(iris)
df1 <- df1[sample(n, 10),]
df2 <- df2[sample(n, 50),]
df3 <- df3[sample(n, 100),]
comcomcol(df1, df2, df3, df4, custom_fun = mean)

Example 4:

• Specify your own function for comparison

df1 <- df2 <- df3 <- df4 <- mtcars
df3$mpg <- NULL
df2$hp <- NULL
comcomcol(df1, df2, df3, df4, custom_fun = function(x) round(median(x^3)))

Example 4

• Quickly check the classes of your dataframe with a clean look.

comcomcol(iris)

Example 5

• Quickly check mean (or any other function) of all possible columns of your dataframe. Warning message appears in case of impossible call (e.g. mean of a character variable). Even if your custom function will fail in some cases all other columns will behave as expected.

comcomcol(iris, custom_fun = mean)

sachserf/datawoman documentation built on May 7, 2019, 11:15 a.m.