How to apply custom function to pandas data frame for each row

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facts['pop2050'] = facts.apply(lambda row: final_pop(row['population'],row['population_growth']),axis=1)

Using lambda allows you to keep the specific (interesting) parameters listed in your function, rather than bundling them in a 'row'.

Apply will pass you along the entire row with axis=1. Adjust like this assuming your two columns are called initial_popand growth_rate

def final_pop(row):
    return row.initial_pop*math.e**(row.growth_rate*35)