BUG: highlight_min and highlight_max do not work with pd.NA

[cynddl]

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• (optional) I have confirmed this bug exists on the master branch of pandas.

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Code Sample, a copy-pastable example

import pandas as pd
import numpy as np

df_ok = pd.DataFrame(dict(a=[np.nan, -1, 1], b=[np.nan, -1, 1]))
df_bug = pd.DataFrame(dict(a=[pd.NA, -1, 1], b=[pd.NA, -1, 1]))

Problem description

df_ok.style.highlight_min() works correctly while df_bug.style.highlight_min() returns the following error:

TypeError: boolean value of NA is ambiguous

Fix

For highlight_min, the error comes from https://github.com/pandas-dev/pandas/blob/v1.3.1/pandas/io/formats/style.py#L2367. Specifically, from the following line:

np.where(data == np.nanmin(data.to_numpy()), props, "")

I'm assuming this could be fixed by replacing it with:

np.where(data == data.min(skipna=True), props, "")

or by making sure to_numpy converts pd.NA to np.nan?

Happy to implement a fix.

Output of pd.show_versions()

INSTALLED VERSIONS

commit : c7f7443
python : 3.8.3.final.0
python-bits : 64
OS : Darwin
OS-release : 20.4.0
Version : Darwin Kernel Version 20.4.0: Thu Apr 22 21:46:47 PDT 2021; root:xnu-7195.101.2~1/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : en_US.UTF-8
LANG : en_GB.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.3.1
numpy : 1.19.2
pytz : 2021.1
dateutil : 2.8.1
pip : 20.0.2
setuptools : 52.0.0.post20210125
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.3
IPython : 7.20.0
pandas_datareader: None
bs4 : 4.9.3
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.4.2
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.6.2
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None

[simonjayhawkins]

df_bug.style.highlight_min() was not raising TypeError: boolean value of NA is ambiguous on 1.2.5, but was not getting the expected output either. labelling as a regression for now, pending further investigation cc @attack68

[simonjayhawkins]

df_bug.style.highlight_min() was not raising TypeError: boolean value of NA is ambiguous on 1.2.5

first bad commit: [0c3c56b] CLN: Styler simplify existing builtin methods (#39797)

[attack68]

Yeh this is odd since the previous implementation before bad commit also used np.nanmin/nanmax.
@cynddl happy to receive a receive a fix with relevant tests. Also perhaps we can deal with None as well using your solution (and test for it also)

[cynddl]

Sure, I'll have a look in the coming days!