'Create new columns based on previous columns with multiplication

I want to create a list of columns where the new columns are based on previous columns times 1.5. It will roll until Year 2020. I tried to use previous and current but it didn't work as expected. How can I make it work as expected?

df = pd.DataFrame({
         'us2000':[5,3,6,9,2,4],

}); df

a = []
for i in range(1, 21):
    a.append("us202" + str(i))
for previous, current in zip(a, a[1:]):
    df[current] = df[previous] * 1.5

python pandas

Solution 1:^[1]

Try:

for i in range(1, 21):
    df[f"us{int(2000+i):2d}"] = df[f"us{int(2000+i-1):2d}"].mul(1.5)

>>> df
   us2000  us2001  us2002  ...       us2018       us2019        us2020
0       5     7.5   11.25  ...   7389.45940  11084.18910  16626.283650
1       3     4.5    6.75  ...   4433.67564   6650.51346   9975.770190
2       6     9.0   13.50  ...   8867.35128  13301.02692  19951.540380
3       9    13.5   20.25  ...  13301.02692  19951.54038  29927.310571
4       2     3.0    4.50  ...   2955.78376   4433.67564   6650.513460
5       4     6.0    9.00  ...   5911.56752   8867.35128  13301.026920

[6 rows x 21 columns]

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Solution	Source
Solution 1	not_speshal

'Create new columns based on previous columns with multiplication

Solution 1:[1]

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Related Questions

Solution 1:^[1]