I want to transpose after concat in pandas-CodePudding

I want to concatenate multiple columns in a DataFrame into a single column and transpose them into a single row, but when I call transpose it remains a single column.

import pandas as pd
df = pd.DataFrame(
    {
        0: [1, 2, 3],
        1: [11, 12, 13]
    }
)
print( df)
df = pd.concat( [df[0], df[1]])
df = df.T.copy()
print( '--------')
print( df)

Even with "df = df.T.copy()" (even without it), after transpose, as follows;

   0   1
0  1  11
1  2  12
2  3  13
--------
0     1
1     2
2     3
0    11
1    12
2    13
dtype: int64

Below is the shape I want.

   0   1   2   3   4   5
0  1   2   3  11  12  13

Please, somebody give me some advice.

CodePudding user response：

Dump down into numpy and build a new dataframe:

import pandas as pd
import numpy as np

out = df.to_numpy().ravel(order='F')
pd.DataFrame([out])
   0  1  2   3   4   5
0  1  2  3  11  12  13

CodePudding user response：

example:

df = pd.DataFrame(
    {
        0: [1, 2, 3],
        1: [11, 12, 13]
    }
)

use following code:

n = df.shape[0] * df.shape[1]
pd.DataFrame(df.values.reshape((1, n), order='F'))