How to Filter DataFrame Rows Based on the Date in Pandas?

How to Filter DataFrame Rows Based on the Date in Pandas?

Filtering DataFrame rows based on a date in pandas can be done using boolean indexing. Here's a step-by-step guide on how to achieve this:

  • First, ensure that the date column in your DataFrame is of datetime type. If it's not, you need to convert it.
  • Second, use boolean indexing to filter rows based on certain conditions related to the date.

Let's walk through an example:

Example:

Suppose we have a DataFrame df with a date column named 'date'.

import pandas as pd data = { 'date': ['2022-01-01', '2022-01-02', '2022-01-03', '2022-01-04', '2022-01-05'], 'value': [10, 20, 30, 40, 50] } df = pd.DataFrame(data) print(df)

Now, let's filter the rows:

  • Convert the 'date' column to datetime type:
df['date'] = pd.to_datetime(df['date'])
  • Filter rows based on certain date conditions:
  • a. Rows after a specific date:
filtered_df = df[df['date'] > '2022-01-02'] print(filtered_df)
  • b. Rows before a specific date:
filtered_df = df[df['date'] < '2022-01-04'] print(filtered_df)
  • c. Rows between two specific dates:
filtered_df = df[(df['date'] >= '2022-01-02') & (df['date'] <= '2022-01-04')] print(filtered_df)
  • d. Rows for a specific date:
filtered_df = df[df['date'] == '2022-01-03'] print(filtered_df)

Using this approach, you can create any custom filter based on dates to select the desired rows from your DataFrame.

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