This what look like my dataframe:

And this is what I want to achieve :

I have tried many things but with no luck.

CodePudding user response：

Assuming your dataframe is named 'd', have you tried:

a = d[['Cat', 'Car_tax']].rename(columns={'Car_tax':'Type'})
b = d[['tax','Type_tax']]].rename(columns={'Type_tax':'Type', 'tax':'Cat' })
pd.concat([a,b]).reset_index(drop=True)

CodePudding user response：

new_cols = ['Cat', 'Type']

sub_1 = df[['Cat', 'Car_tax']]
sub_2 = df[['tax', 'Type_tax']]
sub_1.columns = sub_2.columns = new_cols

result = pd.concat([sub_1, sub_2]).reset_index(drop=True)

CodePudding user response：

You can just append the columns to each other, there is no merge/concat involved:

import pandas as pd


data = {'car1' : ['car10', 'car11'], 'car2': ['car20', 'car21'], 'car3': ['car30', 'car31'], 'car4': ['car40', 'car41']}
df = pd.DataFrame(data)
car1 = df['car1'].append(df['car2'])
car2 = df['car3'].append(df['car4'])
df2 = pd.DataFrame({'car1': car1, 'car2': car2})
df2 = df2.reset_index(drop=True)