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

Create a New Column Based on Values from Multiple Columns in Pandas

To create a new column in a Pandas dataframe based on values from multiple other columns, we can leverage the apply() function. This function allows us to apply a custom function to each row of the dataframe.

In this case, we want to create a new column with race labels based on the following criteria:

Race Label Criteria:

• If the ERI_Hispanic column is 1, the label is "Hispanic."
• Else if the sum of the remaining ERI columns is greater than 1, the label is "Two or More."
• Else if the ERI_AmerInd_AKNatv column is 1, the label is "A/I AK Native."
• Else if the ERI_Asian column is 1, the label is "Asian."
• Else if the ERI_Black_Afr.Amer column is 1, the label is "Black/AA."
• Else if the ERI_HI_PacIsl column is 1, the label is "Haw/Pac Isl."
• Else if the ERI_White column is 1, the label is "White."

Custom Function for Race Labeling:

To define the custom function for race labeling, we can use the following code:

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

Applying the Custom Function with apply():

To apply the label_race function to each row of the dataframe, we can use the apply() function with the axis=1 argument, which specifies that the function should be applied to each row:

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

This will create a new column named race_label in the dataframe with the appropriate race labels.

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