int values are being stringified with floating points

[andyndang]

Description

import pandas as pd

df = pd.DataFrame({'int-only': [1, 1, 1]})

print(why.log(df).view().to_pandas()["frequent_items/frequent_strings"])

Expected to see only "1", not "1.0000"

The actual output:

column
int-only    [FrequentItem(value='1.000000', est=3, upper=3...
Name: frequent_items/frequent_strings, dtype: object

Related

I suspect somehow the Python code is passing the numpy array as float type, but I'm not sure

[andyndang]

Weird. Calling the sketching lib with a numpy thing works:

    import numpy as np  # type: ignore
    import whylogs_sketching as ds  # type: ignore
    freq = ds.frequent_strings_sketch(12)
    freq.update_np(np.array([1, 1, 1]))

[andyndang]

One thing is the arr.dtype in metrics.py:445 is that it shows up as int64

[andyndang]

np.array([1,1, 1]).dtype is also int64

[andyndang]

Ohhh so we're passing as Pandas Series in whylogs, and somehow it turns into float in numpy conversion

[andyndang]

This PR will fix it: #794

[jamie256]

Nice root cause analysis, thanks for the details and investigation Andy!

[github-actions]

This issue is stale. Remove stale label or it will be closed tomorrow.

[andyndang]

Fixed by #794