Show percent instead of counts in charts of categorical variables

Question

I m plotting a categorical variable and instead of showing the counts for each category value   I m looking for a way to get ggplot to display the percentage of values in that category  Of course  it is possible to create another variable with the calculated percentage and plot that one  but I have to do it several dozens of times and I hope to achieve that in one command   I was experimenting with something like   qplot mydataf      stat bin aes n   nrow mydataf   y     count   n       scale y continuous formatter    percent     but I must be using it incorrectly  as I got errors   To easily reproduce the setup  here s a simplified example   mydata  lt - c   aa    bb   NULL   bb    cc    aa    aa    aa    ee   NULL   cc    mydataf  lt - factor mydata   qplot  mydataf    this shows the count  I m looking to see   displayed    In the real case  I ll probably use ggplot instead of qplot  but the right way to use stat bin still eludes me   I ve also tried these four approaches   ggplot mydataf  aes y      count    sum   count           scale y continuous formatter    percent     ggplot mydataf  aes y      count    sum   count           scale y continuous formatter    percent     geom bar     ggplot mydataf  aes x   levels mydataf   y      count    sum   count           scale y continuous formatter    percent     ggplot mydataf  aes x   levels mydataf   y      count    sum   count           scale y continuous formatter    percent     geom bar      but all 4 give    Error  ggplot2 doesn t know how to deal with data of class factor    The same error appears for the simple case of   ggplot  data mydataf  aes levels mydataf        geom bar     so it s clearly something about how ggplot interacts with a single vector  I m scratching my head  googling for that error gives a single result

User · Answer

With ggplot2 version 2 1 0 it is    scale y continuous labels   scales  percent

User · Answer

Since this was answered there have been some meaningful changes to the ggplot syntax   Summing up the discussion in the comments above    require ggplot2   require scales    p  lt - ggplot mydataf  aes x   foo               geom bar aes y      count    sum   count                    version 3 0 0         scale y continuous labels percent    Here s a reproducible example using mtcars    ggplot mtcars  aes x   factor hp                geom bar aes y      count    sum   count                 scale y continuous labels   percent     version 3 0 0     This question is currently the  1 hit on google for  ggplot count vs percentage histogram  so hopefully this helps distill all the information currently housed in comments on the accepted answer   Remark  If hp is not set as a factor  ggplot returns

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If you want percentages on the y-axis and labeled on the bars   library ggplot2  library scales  ggplot mtcars  aes x   as factor am        geom bar aes y      count    sum   count          geom text aes y       count    sum   count      label   scales  percent    count    sum   count       stat    count   vjust   -0 25      scale y continuous labels   percent      labs title    Manual vs  Automatic Frequency   y    Percent   x    Automatic Transmission       When adding the bar labels  you may wish to omit the y-axis for a cleaner chart  by adding to the end     theme          axis text y element blank    axis ticks element blank            axis title y element blank

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Note that if your variable is continuous  you will have to use geom histogram    as the function will group the variable by  quot bins quot   df  lt - data frame V1   rnorm 100    ggplot df  aes x   V1         geom histogram aes y   100    count    sum   count          if you use geom bar    with factor V1   each value of V1 will be treated as a   different category  In this case this does not make sense  as the variable is    really continuous  With the hp variable of the mtcars  see previous answer   it    worked well since hp was not really continuous  check unique mtcars hp    and one    can want to see each value of this variable  and not to group it in bins  ggplot df  aes x   factor V1          geom bar aes y      count    sum   count

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this modified code should work  p   ggplot mydataf  aes x   foo          geom bar aes y      count    sum   count             scale y continuous formatter    percent     if your data has NAs and you dont want them to be included in the plot  pass na omit mydataf  as the argument to ggplot   hope this helps

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Here is a workaround for faceted data   The accepted answer by  Andrew does not work in this case   The idea is to calculate the percentage value using dplyr and then to use geom col to create the plot    library ggplot2  library scales  library magrittr  library dplyr   binwidth  lt - 30  mtcars stats  lt - mtcars   gt     group by cyl    gt     mutate bin   cut hp  breaks seq 0 400  binwidth                   labels  seq 0 binwidth 400  binwidth - binwidth 2             n   n      gt     group by cyl  bin    gt     summarise p   n   n 1     gt     ungroup     gt     mutate bin   as numeric as character bin     ggplot mtcars stats  aes x   bin  y  p         geom col        scale y continuous labels   percent      facet grid cyl      This is the plot

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If you want percentage labels but actual Ns on the y axis  try this       library scales  perbar function xx         q ggplot data data frame xx  aes x xx          geom bar aes y      count     fill  orange          q q     geom text aes y      count    label   scales  percent    count    sum   count       stat  bin  colour  darkgreen          q           perbar mtcars disp

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As of March 2017  with ggplot2 2 2 1 I think the best solution is explained in Hadley Wickham s R for data science book   ggplot mydataf    stat count mapping   aes x foo  y   prop    group 1     stat count computes two variables  count is used by default  but you can choose to use prop which shows proportions

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Since version 3 3 of ggplot2  we have access to the convenient after stat   function  We can do something similar to  Andrew s answer  but without using the    syntax    original example data mydata  lt - c  quot aa quot    quot bb quot   NULL   quot bb quot    quot cc quot    quot aa quot    quot aa quot    quot aa quot    quot ee quot   NULL   quot cc quot      display percentages library ggplot2  ggplot mapping   aes x   mydata                       y   after stat count sum count         geom bar       scale y continuous labels   scales  percent    You can find all the  quot computed variables quot  available to use in the documentation of the geom  and stat  functions  For example  for geom bar    you can access the count and prop variables   See the documentation for computed variables   One comment about your NULL values  they are ignored when you create the vector  i e  you end up with a vector of length 9  not 11   If you really want to keep track of missing data  you will have to use NA instead  ggplot2 will put NAs at the right end of the plot     use NA instead of NULL mydata  lt - c  quot aa quot    quot bb quot   NA   quot bb quot    quot cc quot    quot aa quot    quot aa quot    quot aa quot    quot ee quot   NA   quot cc quot   length mydata    gt   1  11    display percentages library ggplot2  ggplot mapping   aes x   mydata                       y   after stat count sum count         geom bar       scale y continuous labels   scales  percent    Created on 2021-02-09 by the reprex package  v1 0 0   Note that using chr or fct data will not make a difference for your example

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