explore_outliers: Explores outliers in each feature of dataset based on...

In UBC-MDS/xplrrr: This package makes exploratory data analysis (EDA) simple and seamless. EDA is a crucial phase in the data science workflow as it allows us get a fist glimpse of the data. It is important to identify statistical characteristics of the data so that we can properly set up the rest of the analysis

Description

Explores outliers in each feature of dataset based on standard deviation range. Before calculation, NA rows are dropped and only numeric columns are

Usage

explore_outliers(df, std_range)

Arguments

df	A data.frame: The target dataframe to explore
std_range	A integer: The range of standard deviation

Value

data.frame: Dataframe with details on the outliers

Examples

df <- data.frame('col1'= c(1, 2, 1.00, 3, -1, 100),
                 'col2'= c(3, 1 ,3, -2, 3, -1))
explore_outliers(df, 2)

UBC-MDS/xplrrr documentation built on April 2, 2020, 4 a.m.