Getting started with R LanguageData framesReading and writing tabular data in plain-text files (CSV, TSV, etc.)Pipe operators (%>% and others)Linear Models (Regression)data.tableboxplotFormulaSplit functionCreating vectorsFactorsPattern Matching and ReplacementRun-length encodingDate and TimeSpeeding up tough-to-vectorize codeggplot2ListsIntroduction to Geographical MapsBase PlottingSet operationstidyverseRcppRandom Numbers GeneratorString manipulation with stringi packageParallel processingSubsettingDebuggingInstalling packagesArima ModelsDistribution FunctionsShinyspatial analysissqldfCode profilingControl flow structuresColumn wise operationJSONRODBClubridateTime Series and Forecastingstrsplit functionWeb scraping and parsingGeneralized linear modelsReshaping data between long and wide formsRMarkdown and knitr presentationScope of variablesPerforming a Permutation TestxgboostR code vectorization best practicesMissing valuesHierarchical Linear ModelingClassesIntrospection*apply family of functions (functionals)Text miningANOVARaster and Image AnalysisSurvival analysisFault-tolerant/resilient codeReproducible RUpdating R and the package libraryFourier Series and Transformations.RprofiledplyrcaretExtracting and Listing Files in Compressed ArchivesProbability Distributions with RR in LaTeX with knitrWeb Crawling in RArithmetic OperatorsCreating reports with RMarkdownGPU-accelerated computingheatmap and heatmap.2Network analysis with the igraph packageFunctional programmingGet user inputroxygen2HashmapsSpark API (SparkR)Meta: Documentation GuidelinesI/O for foreign tables (Excel, SAS, SPSS, Stata)I/O for database tablesI/O for geographic data (shapefiles, etc.)I/O for raster imagesI/O for R's binary formatReading and writing stringsInput and outputRecyclingExpression: parse + evalRegular Expressions (regex)CombinatoricsPivot and unpivot with data.tableInspecting packagesSolving ODEs in RFeature Selection in R -- Removing Extraneous FeaturesBibliography in RMDWriting functions in RColor schemes for graphicsHierarchical clustering with hclustRandom Forest AlgorithmBar ChartCleaning dataRESTful R ServicesMachine learningVariablesThe Date classThe logical classThe character classNumeric classes and storage modesMatricesDate-time classes (POSIXct and POSIXlt)Using texreg to export models in a paper-ready wayPublishingImplement State Machine Pattern using S4 ClassReshape using tidyrModifying strings by substitutionNon-standard evaluation and standard evaluationRandomizationObject-Oriented Programming in RRegular Expression Syntax in RCoercionStandardize analyses by writing standalone R scriptsAnalyze tweets with RNatural language processingUsing pipe assignment in your own package %<>%: How to ?R Markdown Notebooks (from RStudio)Updating R versionAggregating data framesData acquisitionR memento by examplesCreating packages with devtools

Bar Chart

Other topics

barplot() function

In barplot, factor-levels are placed on the x-axis and frequencies (or proportions) of various factor-levels are considered on the y-axis. For each factor-level one bar of uniform width with heights being proportional to factor level frequency (or proportion) is constructed.

The barplot() function is in the graphics package of the R's System Library. The barplot() function must be supplied at least one argument. The R help calls this as heights, which must be either vector or a matrix. If it is vector, its members are the various factor-levels.

To illustrate barplot(), consider the following data preparation:

> grades<-c("A+","A-","B+","B","C")
> Marks<-sample(grades,40,replace=T,prob=c(.2,.3,.25,.15,.1))
> Marks
[1] "A+" "A-" "B+" "A-" "A+" "B"  "A+" "B+" "A-" "B"  "A+" "A-"
[13] "A-" "B+" "A-" "A-" "A-" "A-" "A+" "A-" "A+" "A+" "C"  "C" 
[25] "B"  "C"  "B+" "C"  "B+" "B+" "B+" "A+" "B+" "A-" "A+" "A-"
[37] "A-" "B"  "C"  "A+"
> 

A bar chart of the Marks vector is obtained from

> barplot(table(Marks),main="Mid-Marks in Algorithms")

enter image description here

Notice that, the barplot() function places the factor levels on the x-axis in the lexicographical order of the levels. Using the parameter names.arg, the bars in plot can be placed in the order as stated in the vector, grades.

# plot to the desired horizontal axis labels
> barplot(table(Marks),names.arg=grades ,main="Mid-Marks in Algorithms")

enter image description here

Colored bars can be drawn using the col= parameter.

> barplot(table(Marks),names.arg=grades,col = c("lightblue", 
        "lightcyan", "lavender", "mistyrose",  "cornsilk"),
         main="Mid-Marks in Algorithms")

enter image description here

A bar chart with horizontal bars can be obtained as follows:

> barplot(table(Marks),names.arg=grades,horiz=TRUE,col = c("lightblue",
          "lightcyan", "lavender", "mistyrose",  "cornsilk"),
           main="Mid-Marks in Algorithms")

enter image description here

A bar chart with proportions on the y-axis can be obtained as follows:

> barplot(prop.table(table(Marks)),names.arg=grades,col = c("lightblue",
           "lightcyan", "lavender", "mistyrose",  "cornsilk"),
            main="Mid-Marks in Algorithms")

enter image description here

The sizes of the factor-level names on the x-axis can be increased using cex.names parameter.

> barplot(prop.table(table(Marks)),names.arg=grades,col = c("lightblue",
          "lightcyan", "lavender", "mistyrose",  "cornsilk"),
           main="Mid-Marks in Algorithms",cex.names=2)

enter image description here

The heights parameter of the barplot() could be a matrix. For example it could be matrix, where the columns are the various subjects taken in a course, the rows could be the labels of the grades. Consider the following matrix:

> gradTab
     Algorithms Operating Systems Discrete Math
  A-         13                10             7
  A+         10                 7             2
  B           4                 2            14
  B+          8                19            12
  C           5                 2             5

To draw a stacked bar, simply use the command:

> barplot(gradTab,col = c("lightblue","lightcyan",
       "lavender", "mistyrose",  "cornsilk"),legend.text = grades,
        main="Mid-Marks in Algorithms")

enter image description here

To draw a juxtaposed bars, use the besides parameter, as given under:

 > barplot(gradTab,beside = T,col = c("lightblue","lightcyan",
       "lavender", "mistyrose",  "cornsilk"),legend.text = grades,
        main="Mid-Marks in Algorithms")

enter image description here

A horizontal bar chart can be obtained using horiz=T parameter:

> barplot(gradTab,beside = T,horiz=T,col = c("lightblue","lightcyan",
       "lavender", "mistyrose",  "cornsilk"),legend.text = grades,
        cex.names=.75,main="Mid-Marks in Algorithms")

enter image description here

Contributors

Topic Id: 8091

Example Ids: 26087

This site is not affiliated with any of the contributors.