Converting columns into rows and adding separate header later in pandas

Question

I am trying to convert the first column row of dataframe to add into a first row and will shift all the other rows to the bottom without losing a last row.

import numpy as np
import pandas as pd
df = pd.DataFrame(np.random.randint(0,3,size=(3, 4)), columns=list('1234'))
df

dataframe output

    1   2   3   4
0   1   1   0   1
1   2   1   1   1
2   0   0   1   2

expected output

    A   B   C   D
0   1   2   3   4
1   1   1   0   1
2   2   1   1   1
3   0   0   1   2

what I tried so far

df.columns.values[0:4] =["A", "B", "C", "D"]

current output

    A   B   C   D
0   1   1   0   1
1   2   1   1   1
2   0   0   1   2

I just lost the last row but I want to add column row into the first row and then add column headers

Naveed · Accepted Answer · 2022-09-29 22:09:03Z

4

here is one way to do it

# add a blank row
df.loc[len(df)] = 0

#shift down the rows
df=df.shift()

#copy column values as rows
df.loc[0]=df.columns.values

#add new column names
df.columns.values[0:4] =["A", "B", "C", "D"]

#makes values int
df.astype(int)

    A   B   C   D
0   1   2   3   4
1   0   2   2   1
2   1   2   2   0
3   2   1   1   0

starting DF

    1   2   3   4
0   0   2   2   1
1   1   2   2   0
2   2   1   1   0

edited Sep 29, 2022 at 22:09

answered Sep 29, 2022 at 22:03

Naveed

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Comments

Mohammad Tehrani · Accepted Answer · 2022-09-29 22:15:40Z

2

Here is another solution:

df = pd.DataFrame(np.concatenate([[[1,2,3,4]], np.random.randint(0,3,size=(3, 4))], axis=0), columns=["A", "B", "C", "D"])

answered Sep 29, 2022 at 22:15

Mohammad Tehrani

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