How to Filter Pandas DataFrames by Date Within the Next Two Months?

Filter Pandas DataFrames on Dates

Problem:

You want to extract rows from a DataFrame that fall within a specific date range, excluding dates outside that range. In this case, you need to keep rows within the next two months.

Solution:

There are several approaches to filtering Pandas DataFrames based on dates:

1. Index-Based Indexing (If 'date' Column is the Index):

• Use .loc for label-based indexing to select rows within a date range:

df.loc['2023-04-01':'2023-06-01']

• Use .iloc for positional indexing if 'date' is not the index but is a column:

df.iloc[start_index:end_index]  # Select rows by position

2. Non-Index-Based Indexing (If 'date' Column is Not the Index):

• Temporarily set 'date' as the index or permanently if it represents time-series data:

df.set_index('date', inplace=True)

• Use boolean indexing to filter rows:

df[(df['date'] > '2023-04-01') & (df['date'] < '2023-06-01')]

Note:

• .ix has been deprecated.
• For additional information and examples, refer to the Pandas documentation: [Indexing](http://pandas.pydata.org/pandas-docs/stable/dsintro.html#indexing-selection)

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