如何在 Pandas 數據透視表查詢中創建帶有日期的字典？

Question

我有一個看起來像這樣的數據框：-

我需要創建一個 Pandas 數據透視表，它將輸出一個這樣的表：

也就是說，它將所有小於 01-Oct-20 的日期匯總為過期，然后正常地匯總所有從 01-Oct-20 開始的日期。

下面的代碼是我到目前為止所想出的。

#!/usr/bin/env python3
import pandas as pd
import numpy as np
# creating a data frame 
df = pd.read_csv("CSVData2.csv") 

table = pd.pivot_table(data=df,index=['Code'], columns=['Process Month'], values = ['Number'], aggfunc=sum)
print(table)

Answer 1

也許這對你有用？

# Recreating your dataframe in code
df = pd.DataFrame({'Code':'A1 P2 B3 B3 C4 A1 B3 A1 A1'.split(' '),
                  'Branch':'UW2 RQ2 UW2 UW2 X01 X01 DN9 PE7 PE7'.split(' '),
                  'Process Month':'01-Oct-20 01-Nov-20 01-Sep-20 01-Sep-20 01-Aug-20 01-Oct-20 01-Sep-20 01-Dec-20 01-Sep-20'.split(' '),
                  'Number':[1]*9})

#Change string to datetime dtype
df['Process Month'] = pd.to_datetime(df['Process Month'])

# Create mask to defined 'Overdue'    
m = df['Process Month'] < '01-Oct-20'

# Output Process Month back as string
df['Process Month'] = df['Process Month'].dt.strftime('%d-%b-%Y')

# Overwriting Process Month with 'OverDue' per mask above
df.loc[m, 'Process Month'] = 'OverDue'

# Creating a crosstab with totals
df_out = pd.crosstab(df['Code'], df['Process Month'], margins=True, margins_name='Total')

df_out.drop('Total', axis=1) #Don't need row Totals column

輸出：

Process Month  01-Dec-2020  01-Nov-2020  01-Oct-2020  OverDue
Code                                                         
A1                       1            0            2        1
B3                       0            0            0        3
C4                       0            0            0        1
P2                       0            1            0        0
Total                    1            1            2        5