Issue
I'm having this data frame:
Name Date Quantity
Apple 07/11/17 20
orange 07/14/17 20
Apple 07/14/17 70
Orange 07/25/17 40
Apple 07/20/17 30
I want to aggregate this by Name
and Date
to get sum of quantities
Details:
Date: Group, the result should be at the beginning of the week (or just on Monday)
Quantity: Sum, if two or more records have same Name and Date (if falls on same interval)
The desired output is given below:
Name Date Quantity
Apple 07/10/17 90
orange 07/10/17 20
Apple 07/17/17 30
orange 07/24/17 40
Thanks in advance
Solution
First, convert column date
to_datetime
and subtract one week as we want the sum for the week ahead of the date and not the week before that date.
Then use groupby
with Grouper
by W-MON and aggregate sum
:
df['Date'] = pd.to_datetime(df['Date']) - pd.to_timedelta(7, unit='d')
df = df.groupby(['Name', pd.Grouper(key='Date', freq='W-MON')])['Quantity']
.sum()
.reset_index()
.sort_values('Date')
print (df)
Name Date Quantity
0 Apple 2017-07-10 90
3 orange 2017-07-10 20
1 Apple 2017-07-17 30
2 Orange 2017-07-24 40
Answered By - jezrael
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