我有一個如下所示的數據框：- 我需要創建一個 Pandas 數據透視表，它將輸出如下表：也就是說，它將所有小于 20 年 10 月 1 日的日期匯總為逾期，然后正常匯總從 20 年 10 月 1 日起的所有日期。下面的代碼是我到目前為止所想出的。#!/usr/bin/env python3import pandas as pdimport 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)
1 回答
qq_笑_17
TA貢獻1818條經驗 獲得超7個贊
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
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