Reputation: 3350
When typing df.dtypes
, we have the list of types.
However, is there a simple way to get the output as
{'col1': np.float32, ...}
or do I need to code a function myself?
Upvotes: 24
Views: 31845
Reputation:
The type returning object of df.dtypes
is pandas.Series. It has a to_dict
method:
df = pd.DataFrame({'A': [1, 2],
'B': [1., 2.],
'C': ['a', 'b'],
'D': [True, False]})
df
Out:
A B C D
0 1 1.0 a True
1 2 2.0 b False
df.dtypes
Out:
A int64
B float64
C object
D bool
dtype: object
df.dtypes.to_dict()
Out:
{'A': dtype('int64'),
'B': dtype('float64'),
'C': dtype('O'),
'D': dtype('bool')}
The values in the dictionary are from dtype class. If you want the names as strings, you can use apply:
df.dtypes.apply(lambda x: x.name).to_dict()
Out: {'A': 'int64', 'B': 'float64', 'C': 'object', 'D': 'bool'}
Upvotes: 62