Convert Pandas Column to DateTime

To convert a column in a Pandas DataFrame to a datetime data type, you can use the pandas.to_datetime() function. This function takes a series of strings and converts them to a datetime data type.

Here's an example of how to use to_datetime() to convert a column in a DataFrame:

import pandas as pd

# Load the data
df = pd.read_csv('data.csv')

# Convert the 'Date' column to datetime
df['Date'] = pd.to_datetime(df['Date'])

# Print the data types
print(df.dtypes)

This will convert the 'Date' column in the DataFrame to a datetime data type. You can then use the dt accessor to access specific attributes of the datetime objects, such as the year or month.

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For example:

# Extract the year from the datetime objects
df['Year'] = df['Date'].dt.year

# Extract the month
df['Month'] = df['Date'].dt.month

This will create two new columns in the DataFrame, 'Year' and 'Month', containing the year and month of the datetime objects in the 'Date' column.