Uninformative error when parsing numbers with a non-standard n/a value

[ghost]

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• 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

data.csv

key,value
a,1.234
b,"1,234.00"
c,":"

Reading the data works ok without parsing the numbers

>>> pd.read_csv('data.csv')
  key     value
0   a     1.234
1   b  1,234.00
2   c         :

When parsing numbers it fails even when the correct thousand separator is set:

>>> pd.read_csv('data.csv', dtype={'value': float}, thousands=',')
ValueError: could not convert string to float: '1,234.00'

However, with the right N/A value setting it works

pd.read_csv('data.csv', dtype={'value': float}, thousands=',', na_values=':')
  key     value
0   a     1.234
1   b  1234.000
2   c       NaN

Problem description

I think the error message saying that pandas could not convert value "1,234.00" to a number is uninformative as the error is rather in the missing value ":".

Might be related to #2570.

Expected Output

I’d expect the error message should be about the non-parsable value ":".

Output of pd.show_versions()

INSTALLED VERSIONS

commit : 2cb9652
python : 3.7.10.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.18362
machine : AMD64
processor : Intel64 Family 6 Model 142 Stepping 10, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.None

pandas : 1.2.4
numpy : 1.20.2
pytz : 2021.1
dateutil : 2.8.1
pip : 21.0.1
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 : None
IPython : 7.22.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.4.1
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

[KenilMehta]

I would like to help solving this issue. Is this open for contributions?

[lilisako]

It's been more than 2 weeks since the last comment posted here. Can I take this issue?

[KenilMehta]

I am not working on it.