Apply pandas function to column to create multiple new columns error

For this question i have found this example:

df = pd.DataFrame([[i] for i in range(5)], columns=['num'])
def powers(x):
    return x, x**2, x**3, x**4, x**5, x**6
df['p1'], df['p2'], df['p3'], df['p4'], df['p5'], df['p6'] = zip(*df['num'].apply(powers))
df

i changed the map() function to apply() function, it worked the same.

as you see we have passed a series for the apply() function: zip(*df['num'].apply(powers)).

This question’s answer is good, But in my case of study i want to pass a dataFrame to the apply() function as: zip(*df[['num']].apply(powers)) by adding double*double brackets df[['num']] , but i got the following error: ValueError: not enough values to unpack (expected 6, got 3).

i didn’t understand where the mistake is, can you help me please?

>Solution :

In my opinion zip with apply is not recommended combine, for add multiple new columns is possible use:

df = pd.DataFrame([[i] for i in range(5)], columns=['num'])
def powers(x):
    
    return pd.Series([x, x**2, x**3, x**4, x**5, x**6])
df[['p1','p2','p3','p4','p5','p6']] = df['num'].apply(powers)

print (df)
   num  p1  p2  p3   p4    p5    p6
0    0   0   0   0    0     0     0
1    1   1   1   1    1     1     1
2    2   2   4   8   16    32    64
3    3   3   9  27   81   243   729
4    4   4  16  64  256  1024  4096

For pass one column DataFrame is possible use:

df = pd.DataFrame([[i] for i in range(5)], columns=['num'])
def powers(x):
    
    return [x, x**2, x**3, x**4, x**5, x**6]
df[['p1','p2','p3','p4','p5','p6']] = df[['num']].pipe(powers)

print (df)
   num  p1  p2  p3   p4    p5    p6
0    0   0   0   0    0     0     0
1    1   1   1   1    1     1     1
2    2   2   4   8   16    32    64
3    3   3   9  27   81   243   729
4    4   4  16  64  256  1024  4096