Is it possible to assign a Series to a DataFrame and use the Series' name as column name?

Question

Given a Series s like this:

0     6
1     0
2     0
3     8
4     8
5    10
6    10
7     9
Name: my_series, dtype: int64

and given a df, would it be possible to assign the series to the df without having
to specify a column name? (The Series name would be used instead)

So, I’d like to avoid having to do this explicitly:

df['my_series'] = s # avoid

My mind goes to something like this:

pd.concat([df, s.to_frame()], axis=1)

but I guess it is counterintuitive.

I have also thought of using df.assign, but I think it requires specifying a column name as well.

Asked By: ttsak

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Source

Answer 1

You can try using pandas.Series.name in the first solution:

df[s.name] = s
# or df.assign(**{s.name: s})

Note that this will override the column if the column with the same name is already present (unlike the pd.concat solution).

Another option – df.join:

df = df.join(s)

This one will throw in case of column with same name being present.

Answered By: Guru Stron

Answer 2

Use DataFrame.join:

df = pd.DataFrame({'col_name':['12','13','14']})

s = pd.Series([0,1,2], name='my_series')

df = df.join(s)
print (df)
  col_name  my_series
0       12          0
1       13          1
2       14          2

Answered By: jezrael

Answer 3

df.insert(1,"my_series",s)

Insert function enables to insert column into DataFrame at specified location, first argument shows where to insert a column second means column name and last your list or series

Answered By: Burak Altınışık

Is it possible to assign a Series to a DataFrame and use the Series' name as column name?

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