Plotting histograms from grouped data in a pandas DataFrame

Question

I need some guidance in working out how to plot a block of histograms from grouped data in a pandas dataframe  Here s an example to illustrate my question   from pandas import DataFrame import numpy as np x     A   300     B   400     C   300 y   np random randn 1000  df   DataFrame   Letter  x   N  y   grouped   df groupby  Letter     In my ignorance I tried this code command   df groupby  Letter   hist     which failed with the error message  TypeError  cannot concatenate  str  and  float  objects   Any help most appreciated

User · Answer

Your function is failing because the groupby dataframe you end up with has a hierarchical index and two columns (Letter and N) so when you do .hist() it's trying to make a histogram of both columns hence the str error.

This is the default behavior of pandas plotting functions (one plot per column) so if you reshape your data frame so that each letter is a column you will get exactly what you want.

df.reset_index().pivot('index','Letter','N').hist()

The reset_index() is just to shove the current index into a column called index. Then pivot will take your data frame, collect all of the values N for each Letter and make them a column. The resulting data frame as 400 rows (fills missing values with NaN) and three columns (A, B, C). hist() will then produce one histogram per column and you get format the plots as needed.

User · Answer

I write this answer because I was looking for a way to plot together the histograms of different groups  What follows is not very smart  but it works fine for me  I use Numpy to compute the histogram and Bokeh for plotting  I think it is self-explanatory  but feel free to ask for clarifications and I ll be happy to add details  and write it better   figures          Transit   figure title  Transit   x axis label  speed  km h    y axis label  frequency         Driving   figure title  Driving   x axis label  speed  km h    y axis label  frequency      cols     Vienna    red    Turin    blue    Rome    Orange   for gr in df trips groupby   locality    means         locality   gr 0  0      means   gr 0  1      fig   figures means      h  b   np histogram pd DataFrame gr 1   speed values      fig vbar x b 1    top h  width  b 1 -b 0    legend label locality  fill color cols locality   alpha 0 5   show gridplot        figures  Transit          figures  Driving

User · Answer

With recent version of Pandas  you can do df N hist by df Letter   Just like with the solutions above  the axes will be different for each subplot   I have not solved that one yet

User · Answer

I m on a roll  just found an even simpler way to do it using the by keyword in the hist method   df  N   hist by df  Letter      That s a very handy little shortcut for quickly scanning your grouped data   For future visitors  the product of this call is the following chart

User · Answer

One solution is to use matplotlib histogram directly on each grouped data frame   You can loop through the groups obtained in a loop   Each group is a dataframe   And you can create a histogram for each one   from pandas import DataFrame import numpy as np x     A   300     B   400     C   300 y   np random randn 1000  df   DataFrame   Letter  x   N  y   grouped   df groupby  Letter    for group in grouped    figure     matplotlib pyplot hist group 1  N    show

[python] Plotting histograms from grouped data in a pandas DataFrame

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