Uninformative error when parsing numbers with a non-standard n/a value 
- [x] I have checked that this issue has not already been reported.
- [x] 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.

---

#### Code Sample

*data.csv*
> key,value
> a,1.234
> b,"1,234.00"
> c,":"

Reading the data works ok without parsing the numbers
```python
>>> 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:
```python
>>> 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
```python
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()``

<details>

INSTALLED VERSIONS
------------------
commit           : 2cb96529396d93b46abab7bbc73a208e708c642e
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
</details>
