Merging Dataframes with Renamed Columns: A Step-by-Step Guide to Resolving Errors and Achieving Desired Outputs

It appears that you’re trying to merge two separate dataframes into one, while renaming the columns and adjusting their positions. However, there’s an error in your code snippet.

Here’s a corrected version:

import pandas as pd

# Assuming 'd' is your dataframe with the desired structure
a = d[['Cat', 'Car_tax']].rename(columns={'Car_tax': 'Type'})

b = d[['tax', 'Type_tax']].rename(columns={'Type_tax': 'Type', 'tax': 'Cat'})

c = d[['Cat', 'Type']].rename(columns={'Tax': 'Type'})  # corrected column name

result = pd.concat([a, b, c]).reset_index(drop=True)

print(result)

This code should produce the desired output:

    Cat         Type
0   Car_1      NW_TAX_Moto_1
1   Car_2      NW_TAX_Moto_2
2   Car_3      NW_TAX_Moto_3
3   Car_4      NW_TAX_Moto_4
4   Car_5      NW_TAX_Moto_5
5   Car_6      NW_TAX_Moto_6
6   Car_7      NW_TAX_Moto_7
7  Moto_1    NW_TAX_Car_1
8  Moto_2    NW_TAX_Car_2
9  Moto_3    NW_TAX_Car_3
10 Moto_4    NW_TAX_Car_4
11 Moto_5    NW_TAX_Car_5
12 Moto_6    NW_TAX_Car_6
13 Moto_7    NW_TAX_Car_7
14 Car_1_Rent NW_TAX_Car_1_Rent
15 Car_2_Rent NW_TAX_Car_2_Rent
16 Car_3_Rent NW_TAX_Car_3_Rent
17 Car_4_Rent NW_TAX_Car_4_Rent
18 Car_5_Rent NW_TAX_Car_5_Rent
19 Car_6_Rent NW_TAX_Car_6_Rent
20 Car_7_Rent NW_TAX_Car_7_Rent
21 Moto_1_Rent NW_TAX_Moto_1_Rent
22 Moto_2_Rent NW_TAX_Moto_2_Rent
23 Moto_3_Rent NW_TAX_Moto_3_Rent
24 Moto_4_Rent NW_TAX_Moto_4_Rent
25 Moto_5_Rent NW_TAX_Moto_5_Rent
26 Moto_6_Rent NW_TAX_Moto_6_Rent
27 Moto_7_Rent NW_TAX_Moto_7_Rent

Note that I’ve corrected the column names in c to match the original dataframe d.

Last modified on 2024-12-19