Learn R Programming

ezEDA (version 0.1.1)

Task Oriented Interface for Exploratory Data Analysis

Description

Enables users to create visualizations using functions based on the data analysis task rather than on plotting mechanics. It hides the details of the individual 'ggplot2' function calls and allows the user to focus on the end goal. Useful for quick preliminary explorations. Provides functions for common exploration patterns. Some of the ideas in this package are motivated by Fox (2015, ISBN:1938377052).

Copy Link

Version

Install

install.packages('ezEDA')

Monthly Downloads

225

Version

0.1.1

License

MIT + file LICENSE

Issues

0

Pull Requests

1

Stars

0

Forks

2

Maintainer

Viswa Viswanathan

Last Published

June 29th, 2021

Functions in ezEDA (0.1.1)

multi_measures_relationship

Plot the relationship between many measures
measure_distribution_over_time

Plot the change of distribution of a numeric (measure) column over time
measure_distribution_by_two_categories

Plot the distribution of a numeric (measure) column differentiated by two categories
two_category_tally

Plot counts of combinations of two category columns
two_measures_relationship

Plot the relationship between two measures and optionally highlight a category
category_tally

Plot counts of a category
category_contribution

Plot the contribution of different categories to a measure
ezeda

ezeda: A package for task oriented exploratory data analysis
col_to_factor

Private utility function: given a possibly non-factor column passed as a quosure, convert into a factor
measure_distribution

Plot the distribution of a numeric (measure) column
measure_distribution_by_category

Plot the distribution of a numeric (measure) column differentiated by a category
measure_change_over_time_long

Plot the change of a measure (or set of measures) over time where the data is in "long" format That is, all measures are in one column with another column labeling each measure value
measure_change_over_time_wide

Plot the change of a measure (or set of measures) over time where each measure is in a different column
two_category_contribution

Plot the contribution to a measure by combinations of two categories