I have a data frame that looks like below:
import pandas as pd
df = pd.DataFrame({'Date':[2019-08-06,2019-08-08,2019-08-01,2019-10-12], 'Name':['A','A','B','C'], 'grade':[100,90,69,80]})
I want to groupby the data by month and year from the Datetime and also group by Name. Then sum up the other columns.
So, the desired output will be something similar to this
df = pd.DataFrame({'Date':[2019-08, 2019-08, 2019-10-12], 'Name':['A','B','C'], 'grade':[190,69,80]})
I have tried grouper
df.groupby(pd.Grouper(freq='M').sum()
However, it won't take the Name column into play and just drop the entire column.
Try :
df['Date'] = pd.to_datetime(df.Date)
df.groupby([df.Date.dt.to_period('M'), 'Name']).sum().reset_index()
Date Name grade
0 2019-08 A 190
1 2019-08 B 69
2 2019-10 C 80
I assume date column is of dtype datetime. Then group with
grouped = df.groupby([df.Date.dt.year, df.Date.dt.month, 'Name']).sum()
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