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To compute the sum of values in a pandas dataframe based on months, you can use the groupby() function along with the resample() function.
Assuming you have a dataframe called 'df' with a datetime column called 'date' and a value column called 'value', here's an example code snippet to compute the sum of values based on months:
df['date'] = pd.to_datetime(df['date']) # Convert date column to datetime format if not already done
df.set_index('date', inplace=True) # Set date column as index
monthly_sum = df.resample('M').sum() # Resample data by month and compute sum of values
print(monthly_sum) # Print monthly sum dataframe
The resample() function with argument 'M' resamples the data by month, computing the monthly sum of values. The resulting dataframe 'monthly_sum' will have the sum of values for each month, with a datetime index representing the end of each month.