I want to change the color of a bar in matplotlib's grouped barplot if it meets a certain condition. I'm plotting two bars for each species - one for today and one for avg, where avg contains yerr errorbars that show the 10th and 90th percentile values.

Now I want the avg bar to be green if today's length value > 10th percentile, and red if today's length value < 10th percentile.

I tried the solutions in these posts

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  CodePudding user response：

  One way is to overwrite the colors after creating the plot. First you need to change the line that initialize col with

  col = ['pink']*z['species'].nunique()
  

  to get the numbers of avg bars, then the same for loop to add g or r depending on your case. Finally, change this

  fig, ax = plt.subplots()
  z0.pivot(index='species', columns='type', values='length')\
    .plot(kind='bar', yerr=bars, ax=ax, 
          color=['pink','g'], capsize=0) # here use only pink and g
  # here overwrite the colors 
  for p, c in zip(ax.patches, col):
      p.set_color(c)
  ax.set_title...
  

  Note that the legend for today is green even if you have a red bar, could be confusing.

  Here is the full working example, adding the red entry in the legend thanks to