append each column with one fixed one D array in a dataframe-CodePudding

How can append each column with one fixed one dimensional array in a dataframe?

df = pd.DataFrame([
    ['234', '434', '471', '4744', '477'],
    ['2.4', '2.4', '2.4'],
])
df.columns = ['col 1', 'col 2', 'col 3', 'col 4', 'col 5']

df

col 1       col 2          col 3           col 4          col 5
234         434             473            4744             477
2.4         2.4             2.4             2.4             2.4

oneD_array = [1, 0, 0, 1, 2, 3]

how can I add my oneD_array to the each column of given dataframe df.

expected output

df

col 1              col 2           col 3           col 4          col 5
234                 434             473            4744             477
2.4                 2.4             2.4             2.4             2.4
 1                   1               1               1               1
 0                   0               0               0               0
 0                   0               0               0               0
 1                   1               1               1               1
 2                   2               2               2               2
 3                   3               3               3               3

CodePudding user response：

Let's repeat the lst n times then concat it to the dataframe

# It's ok to create a n times repeated list like this to create dataframe, but not suitable if you want to use it as variable
out = pd.concat([df, pd.DataFrame([oneD_array] * len(df.columns), index=df.columns).T],
                ignore_index=True)

print(out)

  col 1 col 2 col 3 col 4 col 5
0   234   434   471  4744   477
1   2.4   2.4   2.4  None  None
2     1     1     1     1     1
3     0     0     0     0     0
4     0     0     0     0     0
5     1     1     1     1     1
6     2     2     2     2     2
7     3     3     3     3     3

CodePudding user response：

You can use np.repeat to prepare the additional rows:

n_col = df.shape[1]
arr = np.array(oneD_array).repeat(n_col).reshape(-1, n_col)
result = pd.concat([df, pd.DataFrame(arr, columns=df.columns)], ignore_index=True)