Assuming you have a dataframe named df
containing the columns year
, month
, and price
, you can merge the year
and month
columns to create a new column date
and then group by this column to calculate the average price for each date as follows:
import pandas as pd
# Merge year and month columns to create date column
df['date'] = pd.to_datetime(df['year'].astype(str) + '-' + df['month'].astype(str), format='%Y-%m')
# Group by date and calculate average price
average_prices = df.groupby('date')['price'].mean()
This will create a new Series object average_prices
containing the average price for each date.
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Asked: 2022-11-21 11:00:00 +0000
Seen: 7 times
Last updated: Jul 13 '22
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