Convert pandas Series to DataFrame

to_frame():

Starting with the following Series, df:

email
[email protected]    A
[email protected]    B
[email protected]    C
dtype: int64

I use to_frame to convert the series to DataFrame:

df = df.to_frame().reset_index()

    email               0
0   [email protected]    A
1   [email protected]    B
2   [email protected]    C
3   [email protected]    D

Now all you need is to rename the column name and name the index column:

df = df.rename(columns= {0: 'list'})
df.index.name = 'index'

Your DataFrame is ready for further analysis.

Update: I just came across this link where the answers are surprisingly similar to mine here.

One line answer would be

myseries.to_frame(name='my_column_name')

Or

myseries.reset_index(drop=True, inplace=True)  # As needed

Rather than create 2 temporary dfs you can just pass these as params within a dict using the DataFrame constructor:

pd.DataFrame({'email':sf.index, 'list':sf.values})

There are lots of ways to construct a df, see the docs