How to apply custom function to pandas data frame for each row [duplicate]

Question

I want to apply a custom function and create a derived column called population2050 that is based on two columns already present in my data frame.

import pandas as pd import sqlite3 conn = sqlite3.connect('factbook.db') query = "select * from facts where area_land =0;" facts = pd.read_sql_query(query,conn) print(list(facts.columns.values))  def final_pop(initial_pop,growth_rate):     final = initial_pop*math.e**(growth_rate*35)     return(final)  facts['pop2050'] = facts['population','population_growth'].apply(final_pop,axis=1) 

When I run the above code, I get an error. Am I not using the 'apply' function correctly?

Answer 1

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'.