Creating a series of pie charts from a dataframe with color linked to indexes's values

Question

This is an example dataframe:

import pandas as pd
import numpy as np

values = np.array([
        [0, 1, 2, 0, 0, 4],
        [1, 0, 0, 1, 1, 0 ],
        [0, 4, 0, 0, 2, 1],
        [2, 0, 2, 0, 4, 0],        
        ])

indexes= 'a','b','c','d'

columns='ab','bc','cd','de','ef','fg'

df = pd.DataFrame(index=indexes,columns=columns, data=values)

print(df)

from this dataframe I need to create a series of pie charts, one for every column, shown on the same figure, where the slices dimension is fixed (equal to 100/len(indexes)) and the color of the slices depends on the value of the index, in particular: white if 0, green if 1, yellow if 2, red if 4.

What suggestions can you give me?

I found that:

df.plot(kind='pie', subplots=True, figsize=(len(columns)*2, 2))   

it creates a series, but I can't control the input values...

I've created a pie for a column, but then I wasn't able to link the color to the value of index:

labels = indexes
sizes = np.linspace(100/len(labels),100/len(labels), num=len(labels))


fig1, ax1 = plt.subplots()
ax1.pie(sizes, labels=labels)
ax1.axis('equal')  

plt.show()

ImportanceOfBeingErnest answer has helped me giving to the piechart the wanted look:

fig1, ax1 = plt.subplots()

labels = indexes
sizes = np.linspace(100/len(labels),100/len(labels), num=len(labels))
coldic = {0 : "w", 1 : "g", 2 : "y", 4 : "r" } 
colors = [coldic[v] for v in values[:,0]]

ax1.pie(sizes, labels=labels, colors=colors,counterclock=False, startangle=90)
ax1.axis('equal') 

plt.show()

Now the colors a linked to the values, and the dimensions of the slices are fixed. I just need to have the same pie chart for all the columns and in the same image.

The importance of these charts is given by the colors, not the dimensions of the slices, which I want to be always equal.

Thanks for your time!

Answer 1

Not relying on pandas internal plotting functions (which are of course limited) one can use matplotlib' pie function to plot the diagrams.

The colors can be set as a list, which is generated from the values according to some mapping dictionary.

import numpy as np
import matplotlib.pyplot as plt
coldic = {0 : "w", 1 : "g", 2 : "y", 4 : "r" } 
values = np.array([
        [0, 1, 2, 0, 0, 4],
        [1, 0, 0, 1, 1, 0 ],
        [0, 4, 0, 0, 2, 1],
        [2, 0, 2, 0, 4, 0],        
        ])

labels= ['a','b','c','d']

fig1, axes = plt.subplots(ncols=values.shape[1], )

for i in range(values.shape[1]):
    colors = [coldic[v] for v in values[:,i]]
    labs = [l if values[j,i] > 0 else "" for j, l in enumerate(labels)]
    axes[i].pie(values[:,i], labels=labs, colors=colors) 
    axes[i].set_aspect("equal")

plt.show()

---

For fixed wedge sizes you just use a fixed array to supply to pie.

import numpy as np
import matplotlib.pyplot as plt
coldic = {0 : "w", 1 : "g", 2 : "y", 4 : "r" } 
values = np.array([
        [0, 1, 2, 0, 0, 4],
        [1, 0, 0, 1, 1, 0 ],
        [0, 4, 0, 0, 2, 1],
        [2, 0, 2, 0, 4, 0],        
        ])

labels= ['a','b','c','d']

fig1, axes = plt.subplots(ncols=values.shape[1], )

for i in range(values.shape[1]):
    colors = [coldic[v] for v in values[:,i]]
    axes[i].pie(np.ones(values.shape[0]), labels=labels, colors=colors, 
            wedgeprops=dict(linewidth=1, edgecolor="k")) 
    axes[i].set_aspect("equal")
    axes[i].set_title("".join(list(map(str,values[:,i]))))

plt.show()