python - Subtracting values across grouped data frames in Pandas

Python - Subtracting values across grouped data frames in Pandas

If you want to subtract values across grouped data frames in Pandas, you can use the groupby function along with transform. Here's an example:

import pandas as pd # Create a sample DataFrame data = {'Group': ['A', 'A', 'B', 'B', 'C', 'C'], 'Value': [10, 20, 30, 40, 50, 60]} df = pd.DataFrame(data) # Group by 'Group' and subtract the mean of each group from the 'Value' df['Subtracted_Value'] = df['Value'] - df.groupby('Group')['Value'].transform('mean') # Print the result print(df)

In this example, we first group the DataFrame by the 'Group' column and then subtract the mean of each group from the corresponding 'Value' using transform. The result is stored in a new column called 'Subtracted_Value'.

Examples

  1. "Subtract values in a specific column across two grouped Pandas DataFrames"

    import pandas as pd # Assuming df1 and df2 are your DataFrames, and 'column_name' is the column to subtract result_df = df1.groupby('group_column')['column_name'].sub(df2.groupby('group_column')['column_name']).reset_index()

    Description: This code subtracts values in a specific column ('column_name') across two grouped Pandas DataFrames (df1 and df2) based on a common grouping column ('group_column').

  2. "Subtract values in multiple columns across grouped Pandas DataFrames"

    import pandas as pd # Assuming df1 and df2 are your DataFrames, and columns_to_subtract is a list of columns columns_to_subtract = ['column1', 'column2', 'column3'] result_df = df1.groupby('group_column')[columns_to_subtract].sub(df2.groupby('group_column')[columns_to_subtract]).reset_index()

    Description: This code subtracts values in multiple columns ('column1', 'column2', 'column3') across two grouped Pandas DataFrames (df1 and df2) based on a common grouping column ('group_column').

  3. "Subtract mean values in a column across grouped Pandas DataFrames"

    import pandas as pd # Assuming df1 and df2 are your DataFrames, and 'column_name' is the column to subtract mean values result_df = df1.groupby('group_column')['column_name'].mean().sub(df2.groupby('group_column')['column_name'].mean()).reset_index()

    Description: This code subtracts mean values of a specific column ('column_name') across two grouped Pandas DataFrames (df1 and df2) based on a common grouping column ('group_column').

  4. "Subtract sum values in a column across grouped Pandas DataFrames"

    import pandas as pd # Assuming df1 and df2 are your DataFrames, and 'column_name' is the column to subtract sum values result_df = df1.groupby('group_column')['column_name'].sum().sub(df2.groupby('group_column')['column_name'].sum()).reset_index()

    Description: This code subtracts sum values of a specific column ('column_name') across two grouped Pandas DataFrames (df1 and df2) based on a common grouping column ('group_column').

  5. "Subtract values in a column and create a new column in grouped Pandas DataFrames"

    import pandas as pd # Assuming df1 and df2 are your DataFrames, and 'column_name' is the column to subtract df1['result_column'] = df1.groupby('group_column')['column_name'].transform(lambda x: x - df2.groupby('group_column')['column_name'].transform('first'))

    Description: This code subtracts values in a specific column ('column_name') across two grouped Pandas DataFrames (df1 and df2) based on a common grouping column ('group_column') and creates a new column ('result_column').

  6. "Subtract values in a column with a constant across grouped Pandas DataFrames"

    import pandas as pd # Assuming df1 is your DataFrame, 'column_name' is the column to subtract, and constant_value is the constant result_df = df1.groupby('group_column')['column_name'].sub(constant_value).reset_index()

    Description: This code subtracts a constant value from values in a specific column ('column_name') across a grouped Pandas DataFrame (df1) based on a common grouping column ('group_column').

  7. "Subtract values in a column with a condition across grouped Pandas DataFrames"

    import pandas as pd # Assuming df1 and df2 are your DataFrames, 'column_name' is the column to subtract, and condition_column is the condition result_df = df1.loc[df1['condition_column'] == True].groupby('group_column')['column_name'].sub(df2.loc[df2['condition_column'] == True].groupby('group_column')['column_name']).reset_index()

    Description: This code subtracts values in a specific column ('column_name') across two grouped Pandas DataFrames (df1 and df2) based on a common grouping column ('group_column') and a condition column ('condition_column').

  8. "Subtract values in a column with a rolling window across grouped Pandas DataFrames"

    import pandas as pd # Assuming df1 is your DataFrame, 'column_name' is the column to subtract, and window_size is the rolling window size result_df = df1.groupby('group_column')['column_name'].rolling(window=window_size).mean().sub(df1.groupby('group_column')['column_name'].rolling(window=window_size).mean()).reset_index(level=0, drop=True).reset_index()

    Description: This code subtracts values in a specific column ('column_name') across a grouped Pandas DataFrame (df1) based on a common grouping column ('group_column') using a rolling window.

  9. "Subtract values in a column with a lagged column across grouped Pandas DataFrames"

    import pandas as pd # Assuming df1 and df2 are your DataFrames, 'column_name' is the column to subtract, and lag_value is the lag value result_df = df1.groupby('group_column')['column_name'].sub(df2.groupby('group_column')['column_name'].shift(lag_value)).reset_index()

    Description: This code subtracts values in a specific column ('column_name') across two grouped Pandas DataFrames (df1 and df2) based on a common grouping column ('group_column') with a lagged column.

  10. "Subtract values in a column with a cumulative sum across grouped Pandas DataFrames"

    import pandas as pd # Assuming df1 is your DataFrame, 'column_name' is the column to subtract result_df = df1.groupby('group_column')['column_name'].cumsum().sub(df1.groupby('group_column')['column_name'].cumsum()).reset_index()

    Description: This code subtracts cumulative sum values of a specific column ('column_name') across a grouped Pandas DataFrame (df1) based on a common grouping column ('group_column').

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