How to Create a New Race Label Column in Pandas Based on Multiple Ethnicity Columns?

Creating New Column Based on Values from Multiple Columns Using a Function in Pandas

When working with dataframes in Pandas, it may be necessary to create a new column based on values from multiple existing columns. A common scenario arises when a custom function needs to be applied to a set of columns row-wise to determine the new column's values.

Example Scenario

Consider the following dataframe with six ethnicity-related indicator columns:

df = pd.DataFrame({
    'ERI_Hispanic': [0, 1, 0, 0, 0, 0, 0, 0, 0, 0],
    'ERI_AmerInd_AKNatv': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
    'ERI_Asian': [0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
    'ERI_Black_Afr.Amer': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
    'ERI_HI_PacIsl': [0, 0, 0, 0, 0, 0, 0, 1, 0, 0],
    'ERI_White': [1, 0, 1, 1, 0, 1, 1, 1, 1, 1]
})

The goal is to create a new column named 'race_label' that classifies each row based on the following criteria:

1. If ERI_Hispanic equals 1, return "Hispanic".
2. If the sum of all non-Hispanic ERI columns (ERI_AmerInd_AKNatv, ERI_Asian, ERI_Black_Afr.Amer, ERI_HI_PacIsl, and ERI_White) is greater than 1, return "Two or More".
3. For any other non-zero value in the ERI columns, return the corresponding race label (e.g., "A/I AK Native", "Asian", "Black/AA", "Haw/Pac Isl.", or "White").

Solution

The solution involves two steps: creating a custom function to perform the classification and applying the function to the dataframe row-wise.

1. Defining the Custom Function

def label_race(row):
    if row['ERI_Hispanic'] == 1:
        return 'Hispanic'
    elif row['ERI_AmerInd_AKNatv'] + row['ERI_Asian'] + row['ERI_Black_Afr.Amer'] + row['ERI_HI_PacIsl'] + row['ERI_White'] > 1:
        return 'Two or More'
    elif row['ERI_AmerInd_AKNatv'] == 1:
        return 'A/I AK Native'
    elif row['ERI_Asian'] == 1:
        return 'Asian'
    elif row['ERI_Black_Afr.Amer'] == 1:
        return 'Black/AA'
    elif row['ERI_HI_PacIsl'] == 1:
        return 'Haw/Pac Isl.'
    elif row['ERI_White'] == 1:
        return 'White'
    else:
        return 'Other'

This function takes a row of the dataframe as input and returns the appropriate race label based on the provided criteria.

2. Applying the Function to the Dataframe

To create the new 'race_label' column, use the apply() function along with the axis=1 parameter to apply the label_race function to each row of the dataframe.

df['race_label'] = df.apply(label_race, axis=1)

The resulting dataframe with the new column is displayed below:

    ERI_Hispanic  ERI_AmerInd_AKNatv  ERI_Asian  ERI_Black_Afr.Amer  ERI_HI_PacIsl  ERI_White  \
0             0                  0         0                     0             0          1   
1             1                  0         0                     0             0          0   
2             0                  0         0                     0             0          1   
3             0                  0         0                     0             0          1   
4             0                  0         0                     0             0          0   
5             0                  0         0                     0             0          1   
6             0                  0         1                     0             0          1   
7             0                  0         0                     0             1          1   
8             0                  0         0                     1             0          0   
9             0                  0         0                     0             0          1   

     race_label  
0         White  
1      Hispanic  
2         White  
3         White  
4         Other  
5         White  
6   Two or More  
7         White  
8  Haw/Pac Isl.  
9         White  

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