Answers for "create new column pandas from other columns"

pandas create column from another column

# Creates a new column 'blue_yn' based on the existing 'color' column
# If the 'color' column value is 'blue' then the new column value is 'YES'
df['blue_yn'] = np.where(df['color'] == 'blue', 'YES', 'NO')
# Can also do this using .apply and a lambda function
df['blue_yn']= df['color'].apply(lambda x: 'YES' if (x == 'blue') else 'NO')

pandas new column from others

import pandas as pd

#Here a and b are existing columns

df['c'] = df.apply(lambda row: row.a + row.b, axis=1)
df
#    a  b  c
# 0  1  3  4
# 1  2  4  6

select columns to include in new dataframe in python

new = old[['A', 'C', 'D']].copy()

create new columns pandas from another column

def label_race (row):
   if row['eri_hispanic'] == 1 :
      return 'Hispanic'
   if row['eri_afr_amer'] + row['eri_asian'] + row['eri_hawaiian'] + row['eri_nat_amer'] + row['eri_white'] > 1 :
      return 'Two Or More'
   if row['eri_nat_amer'] == 1 :
      return 'A/I AK Native'
   if row['eri_asian'] == 1:
      return 'Asian'
   if row['eri_afr_amer']  == 1:
      return 'Black/AA'
   if row['eri_hawaiian'] == 1:
      return 'Haw/Pac Isl.'
   if row['eri_white'] == 1:
      return 'White'
   return 'Other'

df.apply(lambda row: label_race(row), axis=1)