Group duplicate columns and sum the corresponding column values using pandas
I am preprocessing apache server log data. I have 3 columns ID, TIME, and BYTES. Example:
ID TIME BYTES
1 13:00 10
2 13:02 30
3 13:03 40
4 13:02 50
5 13:03 70
I want to achieve something like this:
ID TIME BYTES
1 13:00 10
2 13:02 80
3 13:03 110
Solution
Let's try:
df['TIME'] = pd.to_datetime(df['TIME'])
ax = df.groupby('TIME')['BYTES'].sum().plot()
ax.set_xlim('13:00:00','13:03:00')
Output:
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