Elegant way to create empty pandas DataFrame with NaN of type float
Simply pass the desired value as first argument, like 0, math.inf or, here, np.nan. The constructor then initializes and fills the value array to the size specified by arguments index and columns:
>>> import numpy as np>>> import pandas as pd>>> df = pd.DataFrame(np.nan, index=[0, 1, 2, 3], columns=['A', 'B'])>>> df A B0 NaN NaN1 NaN NaN2 NaN NaN3 NaN NaN>>> df.dtypesA float64B float64dtype: object
You could specify the dtype directly when constructing the DataFrame:
>>> df = pd.DataFrame(index=range(0,4),columns=['A'], dtype='float')>>> df.dtypesA float64dtype: objectSpecifying the dtype forces Pandas to try creating the DataFrame with that type, rather than trying to infer it.