How to slice a Pandas Dataframe based on datetime index

How to slice a Pandas Dataframe based on datetime index

You can slice a Pandas DataFrame based on a datetime index using the loc accessor. The loc accessor allows you to select rows from a DataFrame using labels, including datetime values. Here's how you can slice a DataFrame based on a datetime index:

import pandas as pd # Create a sample DataFrame with a datetime index date_rng = pd.date_range(start='2023-01-01', end='2023-01-10', freq='D') data = {'values': range(len(date_rng))} df = pd.DataFrame(data, index=date_rng) # Slice the DataFrame using the loc accessor and datetime range start_date = '2023-01-03' end_date = '2023-01-07' sliced_df = df.loc[start_date:end_date] print(sliced_df)

In this example, the DataFrame is created with a datetime index using pd.date_range(). The loc accessor is then used to slice the DataFrame based on a datetime range defined by start_date and end_date.

The output will be:

 values 2023-01-03 2 2023-01-04 3 2023-01-05 4 2023-01-06 5 2023-01-07 6

The sliced DataFrame includes rows with datetime indices falling within the specified range. Keep in mind that the loc endpoint is inclusive, meaning that rows with the end_date index are included in the slice.

Examples

  1. "Pandas slice dataframe by date range"

    • Description: Users seeking this query aim to slice a Pandas DataFrame based on a specific date range using its datetime index.
    • Code:
      import pandas as pd # Assuming df is your DataFrame with a datetime index start_date = '2023-01-01' end_date = '2023-01-31' sliced_df = df.loc[start_date:end_date] print(sliced_df)

  2. "Slice Pandas DataFrame by month"

    • Description: This query targets slicing a Pandas DataFrame by month based on its datetime index.
    • Code:
      import pandas as pd # Assuming df is your DataFrame with a datetime index sliced_df = df.loc['2023-01'] print(sliced_df)

  3. "Pandas DataFrame slice by year"

    • Description: Users with this query are looking to slice a Pandas DataFrame by year using its datetime index.
    • Code:
      import pandas as pd # Assuming df is your DataFrame with a datetime index sliced_df = df.loc['2023'] print(sliced_df)

  4. "Slice Pandas DataFrame by specific date"

    • Description: This query focuses on slicing a Pandas DataFrame based on a specific date using its datetime index.
    • Code:
      import pandas as pd # Assuming df is your DataFrame with a datetime index specific_date = '2023-01-15' sliced_df = df.loc[specific_date] print(sliced_df)

  5. "Pandas DataFrame slice by weekday"

    • Description: Users using this query are interested in slicing a Pandas DataFrame by weekday using its datetime index.
    • Code:
      import pandas as pd # Assuming df is your DataFrame with a datetime index sliced_df = df[df.index.weekday == 0] # Selecting data for Mondays print(sliced_df)

  6. "Pandas slice DataFrame by hour of the day"

    • Description: This query aims to slice a Pandas DataFrame by hour of the day using its datetime index.
    • Code:
      import pandas as pd # Assuming df is your DataFrame with a datetime index sliced_df = df.between_time('09:00', '17:00') # Selecting data between 9am and 5pm print(sliced_df)

  7. "Pandas DataFrame slice by quarter"

    • Description: Users with this query are looking to slice a Pandas DataFrame by quarter using its datetime index.
    • Code:
      import pandas as pd # Assuming df is your DataFrame with a datetime index sliced_df = df.resample('Q').sum() # Resample by quarter and apply aggregation if needed print(sliced_df)

  8. "Slice Pandas DataFrame by specific time range"

    • Description: This query targets slicing a Pandas DataFrame by a specific time range using its datetime index.
    • Code:
      import pandas as pd # Assuming df is your DataFrame with a datetime index start_time = pd.to_datetime('09:00') end_time = pd.to_datetime('17:00') sliced_df = df.between_time(start_time, end_time) print(sliced_df)

  9. "Pandas slice DataFrame by business days"

    • Description: Users using this query are interested in slicing a Pandas DataFrame by business days using its datetime index.
    • Code:
      import pandas as pd # Assuming df is your DataFrame with a datetime index sliced_df = df[df.index.dayofweek < 5] # Selecting data for Monday to Friday print(sliced_df)

  10. "Pandas DataFrame slice by time of day"

    • Description: This query aims to slice a Pandas DataFrame by time of day using its datetime index.
    • Code:
      import pandas as pd # Assuming df is your DataFrame with a datetime index sliced_df = df.between_time('08:00', '18:00') # Selecting data between 8am and 6pm print(sliced_df)

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