Float Nullability if Entire Column None

[Ducky6944]

Describe the bug It seems that if all the values for a dataframe column are None, nullability throws an error. Not sure if theres a reason for this, or I am doing something wrong.

• [x] I have checked that this issue has not already been reported.
• [x] I have confirmed this bug exists on the latest version of pandera.
• [x] (optional) I have confirmed this bug exists on the main branch of pandera.

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Code Sample, a copy-pastable example

import pandas as pd 
import pandera as pa

df = pd.DataFrame({"test": [None, 1.1, None]})
df1=pd.DataFrame({"test": [None, None, None]})
schema = pa.DataFrameSchema(
    {"test": pa.Column(float, nullable=True)}
)
schema.validate(df)
print(df)
schema.validate(df1)
print(df1)

Expected behavior

I would expect the check to pass.

Desktop (please complete the following information):

• OS: [e.g. iOS] macOS 14.0 (23A344)
• Version: 0.19.3

[Ducky6944]

setting dtype=None in pa.Column seems to circumvent this, or explicitly setting the dtype in the dataframe prior to running validation.

[cosmicBboy]

the problem is that

pd.DataFrame({"test": [None, None, None]})

is interpreted by pandas as an object column. In this case, pandera is behaving as expected, since the test column is of object dtype. If you want pandera to coerce to dtype, use the coerce argument:

schema = pa.DataFrameSchema(
    {"test": pa.Column(float, nullable=True, coerce=True)}
)