How to Efficiently Create Multiple New Columns from a Single Text Column in Pandas?

Using Pandas to Create Multiple New Columns Based on a Single Text Column

Problem:

Extracting multiple values from a text column in Pandas and assigning them correctly to new columns proves a challenge.

Solution:

To efficiently apply a function that returns multiple values to a Pandas column, utilize the zip() function. This solution improves performance significantly compared to iterating with df.iterrows().

Implementation:

<code class="python">def powers(x):
    return x, x**2, x**3, x**4, x**5, x**6

df = pd.DataFrame([[i] for i in range(10)], columns=['num'])
df['p1'], df['p2'], df['p3'], df['p4'], df['p5'], df['p6'] = \
    zip(*df['num'].map(powers))</code>

Example Output:

num	p1	p2	p3	p4	p5	p6
0	0	0	0	0	0	0
1	1	1	1	1	1	1
2	2	4	8	16	32	64
3	3	9	27	81	243	729
4	4	16	64	256	1024	4096
5	5	25	125	625	3125	15625
6	6	36	216	1296	7776	46656
7	7	49	343	2401	16807	117649
8	8	64	512	4096	32768	262144
9	9	81	729	6561	59049	531441

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