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Pandas recently introduced IntegerArrays which allow integer types to also store a NaN-like value pandas.NA.
pandas.NA
Is there a way to use datatest to validate that a pandas.DataFrame's column is of type Int64, i.e. all values are of that type.
Int64
I tried df["mycolumn"].validate(pd.arrays.IntegerArray) and df["mycolumn"].validate(pd.Int64Dtype) to no avail.
df["mycolumn"].validate(pd.arrays.IntegerArray)
df["mycolumn"].validate(pd.Int64Dtype)
The text was updated successfully, but these errors were encountered:
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Pandas recently introduced IntegerArrays which allow integer types to also store a NaN-like value
pandas.NA.Is there a way to use datatest to validate that a pandas.DataFrame's column is of type
Int64, i.e. all values are of that type.I tried
df["mycolumn"].validate(pd.arrays.IntegerArray)anddf["mycolumn"].validate(pd.Int64Dtype)to no avail.The text was updated successfully, but these errors were encountered: