如果满足条件，则在Pandas数据框中重命名列

Question

I am trying to figure out if it is possible to rename a column header if some condition is met. I have a pandas dataframe:

import pandas as pd

data = [[1,'Joe', '2018', 5,7,9]]

df = pd.DataFrame(data, columns = ['ID', 'Name', 'Year', 'FallScore', 'WinterScore', 'SpringScore'])

print(df)
   ID Name  Year  FallScore  WinterScore  SpringScore
0   1  Joe  2018          5            7            9

What I am trying to do is if a column contains 'Fall', 'Winter', or 'Spring' in it add the string 'NEW' to the end of the column header. Here is what the desired output would look like.

df_desired = pd.DataFrame(data, columns = ['ID', 'Name', 'Year', 'FallScoreNEW', 'WinterScoreNEW', 'SpringScoreNEW'])

print(df_desired)
   ID Name  Year  FallScoreNEW  WinterScoreNEW  SpringScoreNEW
0   1  Joe  2018             5               7               9

I was able to get an array of boolean values for each term but have not been able to figure out how to replace the column header if it 'Fall', 'Winter', or 'Spring' is found. Please note I will not know the actual columns headers I will only know that they will contain 'Fall', 'Winter', or 'Spring'

The way I got an array of boolean values is here:

df.columns.str.contains('Fall')
df.columns.str.contains('Winter')
df.columns.str.contains('Spring')

Any help would be greatly appreciated!

Answer 1

You can use rename with a lambda:

df.rename(lambda x: x + 'NEW' if any(k in x for k in keys) else x, axis=1)

   ID Name  Year  FallScoreNEW  WinterScoreNEW  SpringScoreNEW
0   1  Joe  2018             5               7               9

---

This will work as a list comprehension as well, if you don't want a copy of the data returned just for a rename operation.

df.columns = [x + 'NEW' if any(k in x for k in keys) else x for x in df]
df

   ID Name  Year  FallScoreNEW  WinterScoreNEW  SpringScoreNEW
0   1  Joe  2018             5               7               9