How to apply custom function to pandas data frame for each row
You were almost there:
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_pop
and growth_rate
def final_pop(row):
return row.initial_pop*math.e**(row.growth_rate*35)