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sjPlot - Data Visualization for Statistics in Social Science

           

Collection of plotting and table output functions for data visualization. Results of various statistical analyses (that are commonly used in social sciences) can be visualized using this package, including simple and cross tabulated frequencies, histograms, box plots, (generalized) linear models, mixed effects models, PCA and correlation matrices, cluster analyses, scatter plots, Likert scales, effects plots of interaction terms in regression models, constructing index or score variables and much more.

Installation

Latest development build

To install the latest development snapshot (see latest changes below), type following commands into the R console:

library(devtools)
devtools::install_github("strengejacke/sjPlot")

Officiale, stable release

To install the latest stable release from CRAN, type following command into the R console:

install.packages("sjPlot")

Documentation and examples

Please visit https://strengejacke.github.io/sjPlot/ for documentation and vignettes.

Citation

In case you want / have to cite my package, please use citation('sjPlot') for citation information. Since core functionality of package depends on the ggplot-package, consider citing this package as well.

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Version

Install

install.packages('sjPlot')

Monthly Downloads

35,447

Version

2.7.2

License

GPL-3

Maintainer

Daniel Lüdecke

Last Published

September 29th, 2019

Functions in sjPlot (2.7.2)

plot_grid

Arrange list of plots as grid
efc

Sample dataset from the EUROFAMCARE project
plot_likert

Plot likert scales as centered stacked bars
set_theme

Set global theme options for sjp-functions
save_plot

Save ggplot-figure for print publication
plot_frq

Plot frequencies of variables
sjt.corr

Summary of correlations as HTML table
plot_model

Plot regression models
sjplot

Wrapper to create plots and tables within a pipe-workflow
dist_f

Plot F distributions
dist_chisq

Plot chi-squared distributions
plot_scatter

Plot (grouped) scatter plots
plot_models

Forest plot of multiple regression models
plot_stackfrq

Plot stacked proportional bars
dist_norm

Plot normal distributions
plot_grpfrq

Plot grouped or stacked frequencies
sjc.grpdisc

Compute a linear discriminant analysis on classified cluster groups
sjc.elbow

Compute elbow values of a k-means cluster analysis
plot_residuals

Plot predicted values and their residuals
sjPlot-package

Data Visualization for Statistics in Social Science
sjp.aov1

Plot One-Way-Anova tables
plot_kfold_cv

Plot model fit from k-fold cross-validation
sjc.cluster

Compute hierarchical or kmeans cluster analysis
sjc.dend

Compute hierarchical cluster analysis and visualize group classification
dist_t

Plot t-distributions
sjt.itemanalysis

Summary of item analysis of an item scale as HTML table
sjt.fa

Summary of factor analysis as HTML table
sjPlot-themes

Modify plot appearance
sjt.xtab

Summary of contingency tables as HTML table
sjt.pca

Summary of principal component analysis as HTML table
tab_stackfrq

Summary of stacked frequencies as HTML table
plot_xtab

Plot contingency tables
reexports

Objects exported from other packages
view_df

View structure of labelled data frames
sjc.qclus

Compute quick cluster analysis
sjc.kgap

Compute gap statistics for k-means-cluster
sjp.fa

Plot FA results
sjp.corr

Plot correlation matrix
sjp.pca

Plot PCA results
sjp.chi2

Plot Pearson's Chi2-Test of multiple contingency tables
tab_df

Print data frames as HTML table.
sjp.poly

Plot polynomials for (generalized) linear regression
tab_model

Print regression models as HTML table
plot_gpt

Plot grouped proportional tables