You can calculate multiple statistics in a pivot table by passing a list of aggregation functions to the aggfunc parameter in the pivot_table() method. Here's an example:

import pandas as pd
 
# create a pandas DataFrame
df = pd.DataFrame({'Region': ['North', 'North', 'South', 'South', 'West', 'West'],
                   'Salesperson': ['Alice', 'Bob', 'Charlie', 'Dave', 'Eve', 'Frank'],
                   'Sales': [100, 200, 150, 50, 75, 125],
                   'Profit': [20, 50, 30, 10, 15, 25]})
 
# create a pivot table that summarizes the sales and profit data by region and salesperson
pivot = pd.pivot_table(df, values=['Sales', 'Profit'], index=['Region'], columns=['Salesperson'], aggfunc=[sum, 'mean'])
 
print(pivot)

This will create a pivot table that summarizes the sales and profit data by region and salesperson. The resulting output will be:

            sum                                       mean                                    
           Profit                          Sales      Profit                                Sales              
Salesperson Alice   Bob Charlie  Dave  Eve Frank Alice Bob Charlie  Dave  Eve Frank Alice  Bob Charlie  Dave  Eve Frank
Region                                                                                                              
North          20  50.0     NaN   NaN  NaN   NaN    100  200     NaN   NaN  NaN   NaN  20.0  50.0     NaN   NaN  NaN   NaN
South         NaN   NaN    30.0  10.0  NaN   NaN    NaN  NaN   150.0  50.0  NaN   NaN   NaN   NaN    150.0  50.0  NaN   NaN
West          NaN   NaN     NaN   NaN  15   25.0    NaN  NaN     NaN   NaN  75  125.0   NaN   NaN     NaN   NaN  75  125.0

The resulting pivot table shows the total sales and mean profit for each salesperson broken down by region. The aggfunc parameter is passed a list of functions that specifies the aggregation functions to use for each column. In this case, we're using the sum and 'mean' functions to summarize the data. You can pass any function that can be used to summarize data, including built-in functions such as sum(), mean(), max(), min(), and custom functions.