Matplotlib pie chart by n values or threshold

draw_pie.py

import matplotlib.pyplot as plt
import pandas as pd


def pie_by_first_n(df, label_col, size_col, other_name='others', n=5):
    df_sum = df.groupby(label_col)[size_col].sum().reset_index()
    df_sum = df_sum.sort_values(by=size_col, ascending=False)
    
    df2 = df_sum[:n].copy()
    
    data = {
        label_col: [other_name],
        size_col: [df_sum[size_col][n:].sum()],
    }
    
    new_row = pd.DataFrame(data)
    df2 = pd.concat([df2, new_row])
    
    sizes = df2[size_col]
    labels = df2[label_col]
    
    plt.figure(figsize=(15, 10))
    plt.pie(sizes, labels=labels, autopct='%1.1f%%', shadow=True, startangle=140, rotatelabels=90)
    plt.show()
    
    
def pie_by_threshold(df, label_col, size_col, other_name='others', threshold=5.0):
    df_sum = df.groupby(label_col).agg({size_col: 'sum'}).apply(lambda x: 100 * x / float(x.sum()))
    df_sum = df_sum.reset_index()
    
    df1 = df_sum[df_sum[size_col] >= threshold].copy()
    df2 = df_sum[df_sum[size_col] < threshold].copy()
        
    data = {
        label_col: [other_name],
        size_col: [df2[size_col].sum()],
    }
    
    new_row = pd.DataFrame(data)
    df_last = pd.concat([df1, new_row])
    
    sizes = df_last[size_col]
    labels = df_last[label_col]
    
    plt.figure(figsize=(15, 10))
    plt.pie(sizes, labels=labels, autopct='%1.1f%%', shadow=True, startangle=140, rotatelabels=90)
    plt.show()

Thats great!
I found it very useful for my task. My product manager will be happy about new charts)