Why is the Series in the pandas DataFrame giving NaN?

Question

Trying to create a dataframe in Python pandas.

data = {
        'Date_Range': pd.date_range('20130101', periods=6), 
        'Series': pd.Series(data=["start", 2, 5.6, pd.datetime( 2020, 1, 31), True, "last"]),
        'Int_Array': np.array([3, 7, 5, 2, 8, 1], dtype='int32'),
        'Name': pd.Categorical(["John", "Kurt", "Carl", "Mary", "Alfred", "Tom"]),
        'Constant': 'foobar'
}

df = pd.DataFrame(data, index=data["Date_Range"])
# df = pd.DataFrame(data)

print(df)

When I add the index, then the Series gives Nan, but without the index, there is no problem. Why is this happening?

           Date_Range Series  Int_Array    Name Constant
2013-01-01 2013-01-01    NaN          3    John   foobar
2013-01-02 2013-01-02    NaN          7    Kurt   foobar
2013-01-03 2013-01-03    NaN          5    Carl   foobar
2013-01-04 2013-01-04    NaN          2    Mary   foobar
2013-01-05 2013-01-05    NaN          8  Alfred   foobar
2013-01-06 2013-01-06    NaN          1     Tom   foobar

Answer 1

Editing answer

df = pd.DataFrame(data)
df.set_index("Date_Range", inplace=True)
print(df)
print(df['Series'])

Series has Index, u need to define Dataframe First and then set Index.

Output:

Date_Range                Series  Int_Array    Name Constant                                               
2013-01-01                start          3    John   foobar
2013-01-02                    2          7    Kurt   foobar
2013-01-03                  5.6          5    Carl   foobar
2013-01-04  2020-01-31 00:00:00          2    Mary   foobar
2013-01-05                 True          8  Alfred   foobar
2013-01-06                 last          1     Tom   foobar

Output 2:

Date_Range
2013-01-01                  start
2013-01-02                      2
2013-01-03                    5.6
2013-01-04    2020-01-31 00:00:00
2013-01-05                   True
2013-01-06                   last