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We provide practical tutorials on data mining, visualization and statistics for decision making.

This article describes how to quickly display summary statistics using the R package skimr. skimr handles different data types and returns a skim_df object which can be included in a tidyverse pipeline or displayed nicely for the human reader. Key features of skimr: Provides...

25 Jan

Display a Beautiful Summary Statistics in R using Skimr Package

kassambara

Descriptive Statistics

This article presents the fs R package, which provides a cross-platform, uniform interface to file system operations. fs functions are divided into four main categories: path_ for manipulating and constructing paths file_ for files dir_ for directories link_ for links Contents: Prerequistes Some Key...

25 Jan

How to Easily Manipulate Files and Directories in R

kassambara

This article presents how to easily highlight a ggplot using the gghighlight package. Contents: Prerequisites Line plot Histogram Scatter plot Bar plot Prerequisites Load required packages and set the default ggplot2 theme to theme_bw(). library(tidyverse) library(gghighlight) theme_set(theme_bw()) Line plot Basic line plot p <-...

25 Jan

gghighlight: Easy Way to Highlight a GGPlot in R

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ggplot2 extensions

This article describes how to create animation in R using the gganimate R package. gganimate is an extension of the ggplot2 package for creating animated ggplots. It provides a range of new functionality that can be added to the plot object in order to...

25 Jan

gganimate: How to Create Plots with Beautiful Animation in R

kassambara

ggplot2 extensions

This article describes how create easily an interactive web framework for exploring data in R using the datadigest package. This tool provides a concise summary of every variable in a data frame and includes interactive features such as real-time filters, grouping, and highlighting. This...

16 Jan

Simple Interactive Framework for Exploring Data in R

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Interactive Visualization

This article shows how to visualize one numeric variable against multiple others. Prerequisites Load required R package and set the default theme to theme_bw() : library(tidyverse) theme_set( theme_bw() + theme(legend.position = "top") ) Data preparation Demo data: head(iris, 3) ## Sepal.Length Sepal.Width Petal.Length Petal.Width...

16 Jan

How to Plot One Variable against Multiple Others

kassambara

ggplot2 FAQ

You will learn how to plot all variables in a data frame using the ggplot2 R package. Prerequisites Load required R package and set the default theme to theme_minimal() : library(tidyverse) theme_set( theme_minimal() + theme(legend.position = "top") ) Data preparation Demo data: head(iris, 3)...

16 Jan

How to Plot All Variables in a Dataset

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This article describes how to plot a correlation network in R using the corrr package. Related article: Easy Correlation Matrix Analysis in R Using Corrr Package Contents: Load required R packages Data Compute correlation matrix Create a correlation network Cleaning up the correlation network...

16 Jan

Easily Create a Correlation Network in R using the Corrr Package

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Correlation Analysis

This article describes how to easily compute and explore correlation matrix in R using the corrr package. The corrr package makes it easy to ignore the diagonal, focusing on the correlations of certain variables against others, or reordering and visualizing the correlation matrix. It...

16 Jan

Easy Correlation Matrix Analysis in R Using Corrr Package

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Correlation Analysis

This article shows some R histogram examples. Demo data Weight data by sex: set.seed(1234) wdata = data.frame( sex = factor(rep(c("F", "M"), each=200)), weight = c(rnorm(200, 55), rnorm(200, 58)) ) head(wdata, 4) ## sex weight ## 1 F 53.8 ## 2 F 55.3 ## 3...

16 Jan

R Histogram Example Quick Reference

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