如何在 pandas 中的 dataframe 上使用 function？

Question

I am having an issue with applying a function to my dataframe. Simply put, I just need to make the l column increase by a factor of 1.07 each row. The math would look like:

l[0]
l[0] * 1.07 = l[1]
l[1] * 1.07 = l[2] 

It shouldn't be that hard, but I can't figure it out. Any help is appreciated!

a = 1.1
k = 3
l = 4
years = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
df = pd.DataFrame({'a' : a,
                   'l' : l,
                   'k' : k,
                   'y' :  a * (k ** (1/3)) * (l ** (2/3)),
                   'period' : years
                  })

df

Answer 1

Assuming you want to reassign it to your dataframe:

import pandas as pd 
import numpy as np 

a = 1.1
k = 3
l = 4
years = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
df = pd.DataFrame({'a' : a,
                   'l' : l,
                   'k' : k,
                   'y' :  a * (k ** (1/3)) * (l ** (2/3)),
                   'period' : years
                  })
result = pd.Series([l * 1.07**i for i in range(2)])
df.l = result 
print(df)

The key code here is

[l * 1.07**i for i in range(2)]

which is called a list comprehension, and it says generate a list of 2 elements where the i th element is 1.07**i * l . The pd.Series allows you to add the result to your dataframe (you can omit it if you set the range to 10 specifically because 10 is the number of rows in your dataframe).