• Ggplot2 Elegant Graphics For Data Analysis
• Ggplot Pdf

ggplot2 is a powerful and a flexible R package, implemented by Hadley Wickham, for producing elegant graphics.

The concept behind ggplot2 divides plot into three different fundamental parts: Plot = data + Aesthetics + Geometry.

The principal components of every plot can be defined as follow:

• data is a data frame
• Aesthetics is used to indicate x and y variables. It can also be used to control the color, the size or the shape of points, the height of bars, etc…..
• Geometry defines the type of graphics (histogram, box plot, line plot, density plot, dot plot, ….)

Rainbowhcl(4) '#E495A5' '#A065' '#39E 1' '#AA4E2“ However, all palettes are fully customizable: divergehcl(7, h = c(246, 40), c = 96, l = c(65, 90)). RStudio Cheat Sheets. Contribute to rstudio/cheatsheets development by creating an account on GitHub. Cheat Sheet RStudio® is a trademark of RStudio, Inc. CC BY RStudio. info@rstudio.com. 844-448-1212. rstudio.com Learn more at docs.ggplot2.org. ggplot2 0.9.3.1. Updated: 3/15 Geoms- Use a geom to represent data points, use the geom’s aesthetic properties to represent variables. Each function returns a layer.

There are two major functions in ggplot2 package: qplot() and ggplot() functions.

• qplot() stands for quick plot, which can be used to produce easily simple plots.
• ggplot() function is more flexible and robust than qplot for building a plot piece by piece.

This document provides R course material for producing different types of plots using ggplot2.

If you want be highly effective, download our book: Guide to Create Beautiful Graphics in R

The data should be a data.frame (columns are variables and rows are observations).

The data set mtcars is used in the examples below:

1. qplot(): Quick plot with ggplot2
   • Scatter plots
   • Bar plot
   • Box plot, violin plot and dot plot
   • Histogram and density plots
2. Box plots
   • Basic box plots
   • Box plot with dots
   • Change box plot colors by groups
     • Change box plot line colors
     • Change box plot fill colors
   • Change the legend position
   • Change the order of items in the legend
   • Box plot with multiple groups
   • Functions: geom_boxplot(), stat_boxplot(), stat_summary()

3. Violin plots
   • Basic violin plots
   • Add summary statistics on a violin plot
     • Add mean and median points
     • Add median and quartile
     • Add mean and standard deviation
   • Violin plot with dots
   • Change violin plot colors by groups
     • Change violin plot line colors
     • Change violin plot fill colors
   • Change the legend position
   • Change the order of items in the legend
   • Violin plot with multiple groups
   • Functions: geom_violin(), stat_ydensity()

4. Dot plots
   • Basic dot plots
   • Add summary statistics on a dot plot
     • Add mean and median points
     • Dot plot with box plot and violin plot
     • Add mean and standard deviation
   • Change dot plot colors by groups
   • Change the legend position
   • Change the order of items in the legend
   • Dot plot with multiple groups
   • Functions: geom_dotplot()

5. Stripcharts
   • Basic stripcharts
   • Add summary statistics on a stripchart
     • Add mean and median points
     • Stripchart with box blot and violin plot
     • Add mean and standard deviation
   • Change point shapes by groups
   • Change stripchart colors by groups
   • Change the legend position
   • Change the order of items in the legend
   • Stripchart with multiple groups
   • Functions: geom_jitter(), stat_summary()

6. Density plots
   • Basic density plots
   • Change density plot line types and colors
   • Change density plot colors by groups
     • Calculate the mean of each group :
     • Change line colors
     • Change fill colors
   • Change the legend position
   • Combine histogram and density plots
   • Use facets
   • Functions: geom_density(), stat_density()

7. Histogram plots
   • Basic histogram plots
   • Add mean line and density plot on the histogram
   • Change histogram plot line types and colors
   • Change histogram plot colors by groups
     • Calculate the mean of each group
     • Change line colors
     • Change fill colors
   • Change the legend position
   • Use facets
   • Functions: geom_histogram(), stat_bin(), position_identity(), position_stack(), position_dodge().

8. Scatter plots
   • Basic scatter plots
   • Label points in the scatter plot
     • Add regression lines
     • Change the appearance of points and lines
   • Scatter plots with multiple groups
     • Change the point color/shape/size automatically
     • Add regression lines
     • Change the point color/shape/size manually
   • Add marginal rugs to a scatter plot
   • Scatter plots with the 2d density estimation
   • Scatter plots with ellipses
   • Scatter plots with rectangular bins
   • Scatter plot with marginal density distribution plot
   • Functions: geom_point(), geom_smooth(), stat_smooth(), geom_rug(), geom_density_2d(), stat_density_2d(), stat_bin_2d(), geom_bin2d(), stat_summary_2d(), geom_hex() (see stat_bin_hex()), stat_summary_hex()

9. Bar plots
   • Basic bar plots
     • Bar plot with labels
     • Bar plot of counts
   • Change bar plot colors by groups
     • Change outline colors
     • Change fill colors
   • Change the legend position
   • Change the order of items in the legend
   • Bar plot with multiple groups
   • Bar plot with a numeric x-axis
   • Bar plot with error bars
   • Functions: geom_bar(), geom_errorbar()

10. Line plots
    • Line types in R
    • Basic line plots
    • Line plot with multiple groups
      • Change globally the appearance of lines
      • Change automatically the line types by groups
      • Change manually the appearance of lines
    • Functions: geom_line(), geom_step(), geom_path(), geom_errorbar()

11. Error bars
    • Add error bars to a bar and line plots
      • Bar plot with error bars
      • Line plot with error bars
    • Dot plot with mean point and error bars
    • Functions: geom_errorbarh(), geom_errorbar(), geom_linerange(), geom_pointrange(), geom_crossbar(), stat_summary()
12. Pie chart
    • Simple pie charts
    • Change the pie chart fill colors
    • Create a pie chart from a factor variable
    • Functions: coord_polar()

13. QQ plots
    • Basic qq plots
    • Change qq plot point shapes by groups
    • Change qq plot colors by groups
    • Change the legend position
    • Functions: stat_qq()

15. ggsave(): Save a ggplot
    • print(): print a ggplot to a file
    • ggsave: save the last ggplot
    • Functions: print(), ggsave()

16. Main title, axis labels and legend title
    • Change the main title and axis labels
    • Change the appearance of the main title and axis labels
    • Remove x and y axis labels
    • Functions: labs(), ggtitle(), xlab(), ylab(), update_labels()

17. Legend position and appearance
    • Change the legend position
    • Change the legend title and text font styles
    • Change the background color of the legend box
    • Change the order of legend items
    • Remove the plot legend
    • Remove slashes in the legend of a bar plot
    • guides() : set or remove the legend for a specific aesthetic
    • Functions: guides(), guide_legend(), guide_colourbar()

18. Change colors automatically and manually
    • Use a single color
    • Change colors by groups
      • Default colors
      • Change colors manually
      • Use RColorBrewer palettes
      • Use Wes Anderson color palettes
    • Use gray colors
    • Continuous colors: Gradient colors
    • Functions:
      • Brewer palettes: scale_colour_brewer(), scale_fill_brewer(), scale_color_brewer()
      • Gray scales: scale_color_grey(), scale_fill_grey()
      • Manual colors: scale_color_manual(), scale_fill_manual()
      • Hue colors: scale_colour_hue()
      • Gradient, continuous colors: scale_color_gradient(), scale_fill_gradient(), scale_fill_continuous(), scale_color_continuous()
      • Gradient, diverging colors: scale_color_gradient2(), scale_fill_gradient2(), scale_colour_gradientn()

19. Point shapes, colors and size
    • Change the point shapes, colors and sizes automatically
    • Change point shapes, colors and sizes manually
    • Functions: scale_shape_manual(), scale_color_manual(), scale_size_manual()

Points shapes available in R:

20. Add text annotations to a graph
    • Text annotations using the function geom_text
    • Change the text color and size by groups
    • Add a text annotation at a particular coordinate
    • annotation_custom : Add a static text annotation in the top-right, top-left, …
    • Functions: geom_text(), annotate(), annotation_custom()

21. Line types
    • Line types in R
    • Basic line plots
    • Line plot with multiple groups
      • Change globally the appearance of lines
      • Change automatically the line types by groups
      • Change manually the appearance of lines
    • Functions: scale_linetype(), scale_linetype_manual(), scale_color_manual(), scale_size_manual()

22. Themes and background colors
    • Quick functions to change plot themes
    • Customize the appearance of the plot background
      • Change the colors of the plot panel background and the grid lines
      • Remove plot panel borders and grid lines
      • Change the plot background color (not the panel)
    • Use a custom theme
      • theme_tufte : a minimalist theme
      • theme_economist : theme based on the plots in the economist magazine
      • theme_stata: theme based on Stata graph schemes.
      • theme_wsj: theme based on plots in the Wall Street Journal
      • theme_calc : theme based on LibreOffice Calc
      • theme_hc : theme based on Highcharts JS
      • Functions: theme(), theme_bw(), theme_grey(), theme_update(), theme_blank(), theme_classic(), theme_minimal(), theme_void(), theme_dark(), element_blank(), element_line(), element_rect(), element_text(), rel()

23. Axis scales and transformations
    • Change x and y axis limits
      • Use xlim() and ylim() functions
      • Use expand_limts() function
      • Use scale_xx() functions
    • Axis transformations
      • Log and sqrt transformations
      • Format axis tick mark labels
      • Display log tick marks
    • Format date axes
      • Plot with dates
      • Format axis tick mark labels
      • Date axis limits
    • Functions:
      • xlim(), ylim(), expand_limits() : x, y axis limits
      • scale_x_continuous(), scale_y_continuous()
      • scale_x_log10(), scale_y_log10(): log10 transformation
      • scale_x_sqrt(), scale_y_sqrt(): sqrt transformation
      • coord_trans()
      • scale_x_reverse(), scale_y_reverse()
      • annotation_logticks()
      • scale_x_date(), scale_y_date()
      • scale_x_datetime(), scale_y_datetime()

24. Axis ticks: customize tick marks and labels, reorder and select items
    • Change the appearance of the axis tick mark labels
    • Hide x and y axis tick mark labels
    • Change axis lines
    • Set axis ticks for discrete and continuous axes
      • Customize a discrete axis
        • Change the order of items
        • Change tick mark labels
        • Choose which items to display
      • Customize a continuous axis
        • Set the position of tick marks
        • Format the text of tick mark labels
    • Functions: theme(), scale_x_discrete(), scale_y_discrete(), scale_x_continuous(), scale_y_continuous()

25. Add straight lines to a plot: horizontal, vertical and regression lines
    • geom_hline : Add horizontal lines
    • geom_vline : Add vertical lines
    • geom_abline : Add regression lines
    • geom_segment : Add a line segment
    • Functions: geom_hline(), geom_vline(), geom_abline(), geom_segment()

26. Rotate a plot: flip and reverse
    • Horizontal plot : coord_flip()
    • Reverse y axis
    • Functions: coord_flip(), scale_x_reverse(), scale_y_reverse()

27. Faceting: split a plot into a matrix of panels
    • Facet with one variable
    • Facet with two variables
    • Facet scales
    • Facet labels
    • facet_wrap
    • Functions: facet_grid(), facet_wrap(), label_both(), label_bquote(), label_parsed()

• factoextra - Extract and Visualize the outputs of a multivariate analysis: PCA (Principal Component Analysis), CA (Correspondence Analysis), MCA (Multiple Correspondence Analysis) and clustering analyses.

• easyggplot2: Perform and customize easily a plot with ggplot2: box plot, dot plot, strip chart, violin plot, histogram, density plot, scatter plot, bar plot, line plot, etc, …

• ggplot2: Correlation matrix heatmap. Functions: geom_raster() and geom_tile()

• ggfortify: Allow ggplot2 to handle some popular R packages. These include plotting 1) Matrix; 2) Linear Model and Generalized Linear Model; 3) Time Series; 4) PCA/Clustering; 5) Survival Curve; 6) Probability distribution

• GGally: GGally extends ggplot2 for visualizing correlation matrix, scatterplot plot matrix, survival plot and more.

• ggRandomForests: Graphical analysis of random forests with the randomForestSRC and ggplot2 packages.

• ggdendro: Create dendrograms and tree diagrams using ggplot2

• ggmcmc: Tools for Analyzing MCMC Simulations from Bayesian Inference

Cheat Sheets

• Thanks to Hadley Wickham for ggplot2 package: ggplot2 online documentation
• Thanks to RStudio for ggplot2 cheatseet

This analysis was performed using R (ver. 3.2.4) and ggplot2 (ver 2.1.0).

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Categories contained by this category :
easyGgplot2
Articles contained by this category :
Be Awesome in ggplot2: A Practical Guide to be Highly Effective - R software and data visualization
GGally R package: Extension to ggplot2 for correlation matrix and survival plots - R software and data visualization
ggcorrplot: Visualization of a correlation matrix using ggplot2
ggfortify : Extension to ggplot2 to handle some popular packages - R software and data visualization
ggplot2 - Easy way to mix multiple graphs on the same page
ggplot2 : Quick correlation matrix heatmap - R software and data visualization
ggplot2 add straight lines to a plot : horizontal, vertical and regression lines
ggplot2 area plot : Quick start guide - R software and data visualization
ggplot2 axis scales and transformations
ggplot2 axis ticks : A guide to customize tick marks and labels
ggplot2 barplots : Quick start guide - R software and data visualization
ggplot2 box plot : Quick start guide - R software and data visualization
ggplot2 colors : How to change colors automatically and manually?
ggplot2 density plot : Quick start guide - R software and data visualization
ggplot2 dot plot : Quick start guide - R software and data visualization
ggplot2 ECDF plot : Quick start guide for Empirical Cumulative Density Function - R software and data visualization
ggplot2 error bars : Quick start guide - R software and data visualization
ggplot2 facet : split a plot into a matrix of panels

Ggplot2 Elegant Graphics For Data Analysis

ggplot2 histogram plot : Quick start guide - R software and data visualization
ggplot2 legend : Easy steps to change the position and the appearance of a graph legend in R software
ggplot2 line plot : Quick start guide - R software and data visualization
ggplot2 line types : How to change line types of a graph in R software?
ggplot2 pie chart : Quick start guide - R software and data visualization
ggplot2 point shapes
ggplot2 qq plot (quantile - quantile graph) : Quick start guide - R software and data visualization
ggplot2 rotate a graph : reverse and flip the plot
ggplot2 scatter plots : Quick start guide - R software and data visualization
ggplot2 stripchart (jitter) : Quick start guide - R software and data visualization
ggplot2 texts : Add text annotations to a graph in R software
ggplot2 themes and background colors : The 3 elements

Ggplot Pdf

ggplot2 title : main, axis and legend titles
ggplot2 violin plot : Quick start guide - R software and data visualization
ggsave : Save a ggplot - R software and data visualization
qplot: Quick plot with ggplot2 - R software and data visualization
Saving High-Resolution ggplots: How to Preserve Semi-Transparency

I reproduce some of the plots from Rstudio’s ggplot2 cheat sheet using Base R graphics. I didn’t try to pretty up these plots, but you should.

I use this dataset

The main functions that I generally use for plotting are

• Plotting Functions
  • plot: Makes scatterplots, line plots, among other plots.
  • lines: Adds lines to an already-made plot.
  • par: Change plotting options.
  • hist: Makes a histogram.
  • boxplot: Makes a boxplot.
  • text: Adds text to an already-made plot.
  • legend: Adds a legend to an already-made plot.
  • mosaicplot: Makes a mosaic plot.
  • barplot: Makes a bar plot.
  • jitter: Adds a small value to data (so points don’t overlap on a plot).
  • rug: Adds a rugplot to an already-made plot.
  • polygon: Adds a shape to an already-made plot.
  • points: Adds a scatterplot to an already-made plot.
  • mtext: Adds text on the edges of an already-made plot.
• Sometimes needed to transform data (or make new data) to make appropriate plots:
  • table: Builds frequency and two-way tables.
  • density: Calculates the density.
  • loess: Calculates a smooth line.
  • predict: Predicts new values based on a model.

All of the plotting functions have arguments that control the way the plot looks. You should read about these arguments. In particular, read carefully the help page ?plot.default. Useful ones are:

• main: This controls the title.
• xlab, ylab: These control the x and y axis labels.
• col: This will control the color of the lines/points/areas.
• cex: This will control the size of points.
• pch: The type of point (circle, dot, triangle, etc…)
• lwd: Line width.
• lty: Line type (solid, dashed, dotted, etc…).

Discrete

Barplot

Different type of bar plot

Continuous X, Continuous Y

Scatterplot

Jitter points to account for overlaying points.

Add a rug plot

Add a Loess Smoother

Loess smoother with upper and lower 95% confidence bands

Loess smoother with upper and lower 95% confidence bands and that fancy shading from ggplot2.

Add text to a plot

Discrete X, Discrete Y

Mosaic Plot

Color code a scatterplot by a categorical variable and add a legend.

par sets the graphics options, where mfrow is the parameter controling the facets.

The first line sets the new options and saves the old options in the list old_options. The last line reinstates the old options.

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