Override Matplotlib pie chart percentage labels to a specific value that doesn't sum to 100%-CodePudding

I have a pie chart given by the following code

import matplotlib.pyplot as plt

colorPalette=["#61412B","#DCC57D","#D57838","#FFCE33"]

fig, (ax1,ax2)=plt.subplots(1,2,figsize=(10,10))
labels=["Small","Mid","Large"]
values=[.258,.284,.458]
ax1.pie(values,labels=labels,explode=[0.01,0.01,0.01],colors=colorPalette,autopct='%1.1f%%')
labels=["Market Peg","Primary Peg (Passive)","Limit","MidPoint Peg"]
values=[.027,.09,.35,.534]
ax2.pie(values,labels=labels,explode=[0.01,0.01,0.01,0.01],colors=colorPalette,autopct='%1.1f%%')

I noticed that my input value of 53.4% on the second plot gets pushed to 53.3%. Is there a way to override this and still display 53.4, even though it adds to over 100%?

CodePudding user response：

You can actually redefine the label to whatever you want:

import matplotlib.pyplot as plt

colorPalette=["#61412B","#DCC57D","#D57838","#FFCE33"]

fig, (ax1,ax2)=plt.subplots(1,2,figsize=(10,10))
labels=["Small","Mid","Large"]
values=[.258,.284,.458]
ax1.pie(values,labels=labels,explode=[0.01,0.01,0.01],colors=colorPalette,autopct='%1.1f%%')
labels=["Market Peg","Primary Peg (Passive)","Limit","MidPoint Peg"]
values=[.027,.09,.35,.534]
l = ax2.pie(values,labels=labels,explode=[0.01,0.01,0.01,0.01],colors=colorPalette,autopct='%1.1f%%')

# get the Text object and change the text
l[2][-1].set_text('95.3%')

output:

how it works

pie returns a list with some elements of the graph: the wedges, the outside labels, and the inside labels (the ones we want).

>>> l
([<matplotlib.patches.Wedge at 0x7f709a12e130>,
  <matplotlib.patches.Wedge at 0x7f709a12e850>,
  <matplotlib.patches.Wedge at 0x7f709a12eee0>,
  <matplotlib.patches.Wedge at 0x7f709a13a5b0>],
 [Text(1.1060171651625381, 0.09394695506413589, 'Market Peg'),
  Text(0.9985589871945, 0.4847473043690852, 'Primary Peg (Passive)'),
  Text(-0.2875697258635596, 1.0721024450894407, 'Limit'),
  Text(-0.11648807636083792, -1.1038707026032315, 'MidPoint Peg')],
 [Text(0.6078112349091426, 0.051628506837047644, '2.7%'),
  Text(0.5487576416113918, 0.2663926627613891, '9.0%'),
  Text(-0.1580338133124066, 0.5891734157698728, '35.0%'),
  Text(-0.064015969891992, -0.6066316473765505, '53.4%')])

CodePudding user response：

As a good practice pie chart numbers should add upto 100%. Pie charts are designed to show parts of a whole, so any sum below or above 100% doesn’t represent the entire picture.

Actually, you can add the actual values beside the percentages by passing a fuction in autopct. This way there is no need to manupulate the percentage.

If you really want to change the percentage, you can modify the create_autopct function to do the same by changing pct value

import matplotlib.pyplot as plt

def autopct(values):
def create_autopct(pct):
    total = sum(values)
    val = pct*total/100.0
    # pct = 50.0  -> calculate and update your value
    # return f'{pct:.1f}%)'
    return f'{pct:.1f}%  ({val:g})'
return create_autopct

colorPalette=["#61412B","#DCC57D","#D57838","#FFCE33"]

fig, (ax1,ax2)=plt.subplots(1,2,figsize=(10,10))
labels=["Small","Mid","Large"]
values=[.258,.284,.458]
ax1.pie(values,labels=labels,explode=[0.01,0.01,0.01],colors=colorPalette,autopct='%1.1f%%')
labels=["Market Peg","Primary Peg (Passive)","Limit","MidPoint Peg"]
values=[.027,.09,.35,.534]
ax2.pie(values,labels=labels,explode=[0.01,0.01,0.01,0.01],colors=colorPalette,autopct=autopct(values))

output chart