Skipping the first column while renaming column using for loop in python

Question

The ask is simple, for renaming multiple dataframe's with a single code I have written the below but when I am using the code the column which contains the primary key is also getting renamed what I want my code to do is to skip the first column and rename the rest.

Codes have been provided below for better understanding of what I am trying to achieve:

import pandas as pd

USA = pd.read_excel(r"C:\Users\Rage\Desktop\usa.xlsx")
BRA = pd.read_excel(r"C:\Users\Rage\Desktop\usa.xlsx")
CAN = pd.read_excel(r"C:\Users\Rage\Desktop\usa.xlsx")


df_dict = {"USA":USA, "BRA":BRA, "CAN":CAN}

for name, df in df_dict.items():
        df.columns = df.columns + "_" + name

Which gives me the below output:

Primary Key_CAN local stat_CAN  valid stat_CAN  valid date_CAN
123                Approved        completed      2018-02-02
554                Restrict        pending        2020-06-05
789                Declined        pending        2016-08-07

Which is perfect but with one problem I want the loop to skip the first column that is "Primary key" Making my expected output to be below:

Primary Key   local stat_CAN      valid stat_CAN valid date_CAN
123                Approved        completed      2018-02-02
554                Restrict        pending        2020-06-05
789                Declined        pending        2016-08-07

there is no difference between your expected output and the output you got. could you have a look at your post — sammywemmy, Feb 18 '20 at 09:19
Does this answer your question? [Renaming columns in pandas](https://stackoverflow.com/questions/11346283/renaming-columns-in-pandas) — Mateen Ulhaq, Feb 18 '20 at 09:24
@Mateen Ulhaq no Mateen but Mohit Sharma answered my query thanks for the the help :) — ragethewolf, Feb 18 '20 at 09:29

Mohit Sharma · Answer 1 · 2020-02-18T12:26:00.917

2

This will work for you

for name, df in df_dict.items():
        new_col = {c:c+"_"+name for c in df.columns[1:]}
        df.rename(columns=new_col, inplace = True)

edited Feb 18 '20 at 12:26

answered Feb 18 '20 at 09:21

Mohit Sharma

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1 question can u please explain new_col = {c:c+"_"+name for c in df.columns[1:]} kind of a newbie here – ragethewolf Feb 18 '20 at 09:23
1

@ragethewolf That's called a "dictionary comprehension". Read up on "list comprehensions" if you're not familiar. – Mateen Ulhaq Feb 18 '20 at 09:26
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its a dict comprehension, in simple terms: `new_col = {} for c in df.columns[1:]: # it will iterate through columns excluding 1st new_col[c] = c+"_"+name` dict will be created with key (old names) and value (new names) – Mohit Sharma Feb 18 '20 at 09:26

score 2 · Accepted Answer · answered Feb 18 '20 at 09:35

2

You should split the columns index in 2 sublists and only change the second one:

df.columns = [df.columns[0]] + (df.columns[1:] + '_' + 'CAN').tolist()

answered Feb 18 '20 at 09:35

Serge Ballesta

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Loved this answer too :) – ragethewolf Feb 20 '20 at 07:12

Skipping the first column while renaming column using for loop in python

2 Answers2