Create Empty Dataframe in Pandas specifying column types

Question

I'm trying to create an empty data frame with an index and specify the column types. The way I am doing it is the following:

df = pd.DataFrame(index=['pbp'],                   columns=['contract',                            'state_and_county_code',                            'state',                            'county',                            'starting_membership',                            'starting_raw_raf',                            'enrollment_trend',                            'projected_membership',                            'projected_raf'],                   dtype=['str', 'str', 'str', 'str',                          'int', 'float', 'float',                          'int', 'float']) 

However, I get the following error,

TypeError: data type not understood 

What does this mean?

Answer 1

You can use the following:

df = pd.DataFrame({'a': pd.Series(dtype='int'),                    'b': pd.Series(dtype='str'),                    'c': pd.Series(dtype='float')}) 

or more abstractly:

df = pd.DataFrame({c: pd.Series(dtype=t) for c, t in {'a': 'int', 'b': 'str', 'c': 'float'}.items()}) 

then if you call df you have:

>>> df  Empty DataFrame  Columns: [a, b, c] Index: [] 

and if you check its types:

>>> df.dtypes a      int32 b     object c    float64 dtype: object