about pandas dataframe reverse column’s data order

Code

import pandas as pd
import numpy as np

df = pd.DataFrame({"K1":[1,2,3],"K2":[4,5,6]})
df["result"] = (df["K1"].shift(1)*df["K2"]).fillna(1)[::-1] #line A
print(df["result"])
print((df["K1"].shift(1)*df["K2"]).fillna(1)[::-1]) #line B
print((df["K1"].shift(1)*df["K2"]).fillna(1)) # line C

Output

0     1.0
1     5.0
2    12.0
Name: result, dtype: float64

2    12.0
1     5.0
0     1.0
dtype: float64

0     1.0
1     5.0
2    12.0
dtype: float64

Why column result not get reverse order in line A but it work in line B?

Answers:

Thank you for visiting the Q&A section on Magenaut. Please note that all the answers may not help you solve the issue immediately. So please treat them as advisements. If you found the post helpful (or not), leave a comment & I’ll get back to you as soon as possible.

Method 1

By using [::-1], you are reversing the Series, including the index (as you can see by your prints). So, the index-value pairs remain the same. Pandas will use the Series index to align the it to the existing index in the df DataFrame. To solve this, you need to assign the raw values to the column, not a Pandas Series, e.g. by using .to_numpy().

df["result"] = (df["K1"].shift(1)*df["K2"]).fillna(1).to_numpy()[::-1] #line A

All methods was sourced from stackoverflow.com or stackexchange.com, is licensed under cc by-sa 2.5, cc by-sa 3.0 and cc by-sa 4.0