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This is a quick post representing code sample related to how to extract month & year from datetime column of DataFrame in Pandas.
The code sample is shown using the sample data, BrentOilPrices downloaded from this Kaggle data page.
Here is the code to load the data frame.
import pandas as pd df = pd.read_csv('BrentOilPrices.csv')
Check the data type of the data using the following code:
df.dtypes
The output looks like the following:
Date object
Price float64
dtype: object
Use the following command to change the date data type from object to datetime and extract the month and year.
df['Date'] = pd.to_datetime(df['Date']) df['year'] = pd.DatetimeIndex(df['Date']).year df['month'] = pd.DatetimeIndex(df['Date']).month
Printing data using head command would print the following:
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I found it very helpful. However the differences are not too understandable for me