Add multiple rows in existing dataframe based on a list pandas

Question

i have a dataframe df with 1 row and 20 columns:

id    name   age...... And so on
1      Ian    29......

I also have a list L

L = ['Doctor', 'Carpenter']

I want to create a column 'Occupation' in my dataframe such that, all the other column values remain same.

Final output required:

id    name   age...... Occupation
1      Ian    29...... Doctor
1      Ian    29...... Carpenter

I was trying to iterate the list and then use pd.concat to append two slices.

Is there a better way to do it?

jezrael · Accepted Answer · 2021-04-15 11:55:41Z

5

You can repeat index values by length of list and then assign to new column:

L = ['Doctor', 'Carpenter']

df = df.loc[df.index.repeat(len(L))].assign(Occupation = L).reset_index(drop=True)
print (df)
   id name age Occupation
0   1  Ian  29 Doctor
1   1  Ian  29 Carpenter

Another idea with first assign nested list and then DataFrame.explode:

df = df.assign(Occupation = [L]).explode('Occupation').reset_index(drop=True)

edited Apr 15, 2021 at 11:55

answered Apr 15, 2021 at 11:49

jezrael

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