Matplotlib, Pandas, label errors on pie chart diagram

Question

I created a pie chart using both Pandas wrapper counts.plot(kind='pie')and Matplotlib straight `plt.pie (counts).

The problem is labeling. Using both pie charts seems to be correct in terms of = pie wedge values, however the shortcuts are disabled when I start introducing custom colors and legends.

Pie chart stickers are correct, but legend labels are drawn relative to their label order in group_name, not their value. Any ideas on how to fix this?

Code =

group_names = ['2-3 km', '3-5 km','5-7 km','7-10 km','10-20 km','20-50 km','50-75 km','75-100 km','>100 km']

df['bins'] = pd.cut(df['distkm'], bins)
df['categories'] = pd.cut(df['distkm'], bins, labels=group_names)

counts = df['categories'].value_counts()
plt.axis('equal')
explode = (0, 0, 0,0.1,0.1,0.2,0.3,0.4,0.6)
colors = ['#191970','#001CF0','#0038E2','#0055D4','#0071C6','#008DB8','#00AAAA','#00C69C','#00E28E','#00FF80',]
counts.plot(kind='pie', fontsize=17,colors=colors,explode=explode)
plt.legend(labels=group_names,loc="best")

plt.show()

Data look like

20-50 km     1109
50-75 km      696
10-20 km      353
75-100 km     192
3-5 km        168
7-10 km        86
5-7 km         74
>100 km        65
2-3 km         53
dtype: int64

Answer 1

group_names , counts.index.

plt.legend(labels=group_names,loc="best")

plt.legend(labels=counts.index, loc="best")

---

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

group_names = ['2-3 km', '3-5 km', '5-7 km', '7-10 km', '10-20 km', '20-50 km', 
               '50-75 km', '75-100 km', '>100 km']

counts = pd.Series([1109, 696, 353, 192, 168, 86, 74, 65, 53], 
                   index=['20-50 km', '50-75 km', '10-20 km', '75-100 km',
                          '3-5 km', '7-10 km', '5-7 km', '>100 km', '2-3 km'])

explode = (0, 0, 0, 0.1, 0.1, 0.2, 0.3, 0.4, 0.6)
colors = ['#191970', '#001CF0', '#0038E2', '#0055D4', '#0071C6', '#008DB8', '#00AAAA',
          '#00C69C', '#00E28E', '#00FF80', ]

counts.plot(kind='pie', fontsize=17, colors=colors, explode=explode)
plt.axis('equal')
plt.ylabel('')
plt.legend(labels=counts.index, loc="best")
plt.show()

Answer 2

, , .

counts = df['categories'].value_counts(sort=False)

Answer 3

You can convert the pandas DataFrame to a list and plot using matplotlib directly:

sizes = counts.values.tolist()
plt.axis('equal')
plt.pie(sizes,explode=explode,labels=group_names,colors=colors)
plt.legend(labels=group_names,loc="best")
plt.show()