BUG: pd.NA ignored in DataFrame.to_html(na_rep)

[ramseykarim]

• 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

A short example adjusted from the one in issue #29975 (which appeared to be the closest bug to this one, unless I missed something)

>>> df = pd.DataFrame({'a': [1, pd.NA, 2]})
>>> df
>>> 'zzzz' in df.to_csv(na_rep='zzzz')
True
>>> 'zzzz' in df.to_html(na_rep='zzzz')
False

Problem description

pd.NA seems to be ignored by the na_rep in to_html(). In the HTML, pd.NA shows up as <NA>.

The na_rep works fine for pd.NA in to_csv() and works fine for NaNs in to_html():

>>> df = pd.DataFrame({'a': [1, float('nan'), 2]})
>>> 'zzzz' in df.to_csv(na_rep='zzzz')
True
>>> 'zzzz' in df.to_html(na_rep='zzzz')
True

Expected Output

I'd expect pd.NA to be represented by the na_rep in the output of to_html().

Output of pd.show_versions()

commit : None
python : 3.7.7.final.0
python-bits : 64
OS : Linux
OS-release : 5.3.0-7642-generic
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.0.3
numpy : 1.18.1
pytz : 2019.3
dateutil : 2.8.1
pip : 20.0.2
setuptools : 46.1.3.post20200330
Cython : 0.29.15
pytest : 5.4.1
hypothesis : 5.8.3
sphinx : 2.4.4
blosc : None
feather : None
xlsxwriter : 1.2.8
lxml.etree : 4.5.0
html5lib : 1.0.1
pymysql : None
psycopg2 : None
jinja2 : 2.11.1
IPython : 7.13.0
pandas_datareader: None
bs4 : 4.8.2
bottleneck : 1.3.2
fastparquet : None
gcsfs : None
lxml.etree : 4.5.0
matplotlib : 3.1.3
numexpr : 2.7.1
odfpy : None
openpyxl : 3.0.3
pandas_gbq : None
pyarrow : None
pytables : None
pytest : 5.4.1
pyxlsb : None
s3fs : None
scipy : 1.4.1
sqlalchemy : 1.3.15
tables : 3.6.1
tabulate : None
xarray : None
xlrd : 1.2.0
xlwt : 1.3.0
xlsxwriter : 1.2.8
numba : 0.48.0

[k-fillmore]

take

[gerardsyd]

This also doesn't work for NaT either. For example in below:

>>> df = pd.DataFrame({'Label': ['One', 'Two', 'Total'], 'Date': [datetime(2020, 8, 20), datetime(2020, 8, 20), np.NaN]})
>>> df['Date'] = pd.to_datetime(df['Date'], errors='ignore')
>>> df

	Label	Date
0	One	2020-08-20
1	Two	2020-08-20
2	Total	NaT

>>> 'oooo' in df.to_html(na_rep='oooo')

False