How to Filter DataFrame Rows by Date Range in Python?

Select Data Frame Rows within a Specified Date Range

Problem:

How to create a new DataFrame from a CSV file that contains only rows with dates within a specified range or between two dates.

Solution 1: Using a Boolean Mask

Ensure that the DataFrame's date column is a Series with a datetime64[ns] data type. Create a boolean mask by comparing the dates to the start and end dates. Use this mask to select the rows and either create a new DataFrame or overwrite the existing one.

Example:

df['date'] = pd.to_datetime(df['date'])
mask = (df['date'] > start_date) &amp; (df['date'] <= end_date)
df_filtered = df.loc[mask]

Solution 2: Using a DatetimeIndex

Convert the date column to a DatetimeIndex. This allows you to select rows by date using df.loc[start_date:end_date].

Example:

import pandas as pd
df['date'] = pd.date_range('2000-1-1', periods=200, freq='D')
df = df.set_index(['date'])
df_filtered = df.loc['2000-6-1':'2000-6-10']

Additional Notes:

• You don't have to include both start and end dates in the index.
• pd.read_csv has a parse_dates parameter that can be used to parse the date column during reading.

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