clean_up: Clean up the dataframe and detect outliers

In UBC-MDS/reasyeda: Make Exploratory Data Analysis Easier

Description

Takes a dataframe object and returns a cleaned version with rows containing any NaN values dropped. Inspects the clean dataframe and prints a list of potential outliers for each explanatory variable.

Usage

clean_up(df)

Arguments

df	The dataframe on which the function will operate

Value

the same dataframe with all the NaN's removed along with a list of potential outliers

Examples

library(palmerpenguins)
results <- clean_up(penguins)
'**The following potential outliers are detected:**
$Variable X:
300, 301, 500, 1000
Variable Y:
6.42, 6.44, 58.52, 60.22'

UBC-MDS/reasyeda documentation built on Feb. 6, 2022, 7 a.m.