Reorganizing DataFrame (interchanging row information as columns)

Question

I have the next DataFrame.

data={
 'date':['2023-01', '2023-01', '2023-01', '2023-01', '2023-02', '2023-02', '2023-02', '2023-02', '2023-02'],
'concept':['FOOD', 'CAR', 'EDUCATION', 'ELECTRICITY', 'FOOD', 'CAR', 'TRAVEL', 'WATER', 'ELECTRICITY'],
'amount':[455.54, 237.41, 3.91, 213.2, 28.72, 422.72, 263.29, 3.93, 89.35]  
      }
df = pd.DataFrame(data)

I would like to reorder the information so I have all the concepts as rows, and then each column is a month. Finally a third column with the total sum of all months. The result should be a DataFrame like this:

	Jan-23	Feb-23	Total
CAR	237.41	422.72	660.13
EDUCATION	3.91	0	3.91
ELECTRICITY	213.2	89.35	302.55
FOOD	455.54	28.72	484.26
TRAVEL	0	263.29	263.29
WATER	0	3.93	3.93

How could I do it?

Asked By: nekovolta

||

Source

Answer 1

You can use the pivot function like this and then use the sum function

new_df = df.pivot(columns='date', index='concept', values='amount')
new_df['total'] = new_df.sum(axis=1)

Answered By: P. Shroff

Reorganizing DataFrame (interchanging row information as columns)

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