pandas 按年和月分组 Panda Pivot Table
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Group by Year and Month Panda Pivot Table
提问by Huzaifa M Aamir
I have data like this
我有这样的数据
Date LoanOfficer User_Name Loan_Number
0 2017-11-30 00:00:00 Mark Evans underwriterx 1100000293
1 2017-11-30 00:00:00 Kimberly White underwritery 1100004947
2 2017-11-30 00:00:00 DClair Phillips underwriterz 1100007224
I've created df pivot table like this:
我已经像这样创建了 df 数据透视表：
pd.pivot_table(df,index=["User_Name","LoanOfficer"],
values=["Loan_Number"],
aggfunc='count',fill_value=0,
columns=["Date"]
)
However I need the Date column to be grouped by Year and Month. I was looking at other solutions of resampling the dataframe and then applying the pivot but it only does it for Month and Days. Any help would be appreciated
但是，我需要按年和月对日期列进行分组。我正在研究重新采样数据框然后应用数据透视表的其他解决方案，但它仅适用于月和日。任何帮助，将不胜感激
回答by YOBEN_S
You can convert you Date column to %Y-%m , then do the pivot_table
您可以将 Date 列转换为 %Y-%m ，然后执行 pivot_table
df.Date=pd.to_datetime(df.Date)
df.Date=df.Date.dt.strftime('%Y-%m')
df
Out[143]:
Date LoanOfficer User_Name Loan_Number
0 2017-11 Mark Evans underwriterx 1100000293
1 2017-11 Kimberly White underwritery 1100004947
2 2017-11 DClair Phillips underwriterz 1100007224
pd.pivot_table(df,index=["User_Name","LoanOfficer"],
values=["Loan_Number"],
aggfunc='count',fill_value=0,
columns=["Date"]
)
Out[144]:
Loan_Number
Date 2017-11
User_Name LoanOfficer
underwriterx Mark Evans 1
underwritery Kimberly White 1
underwriterz DClair Phillips 1
