Description
Pandas version checks
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I have checked that this issue has not already been reported.
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I have confirmed this bug exists on the latest version of pandas.
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I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
pandas as pd
valid = '2024-01-01'
invalid = 'N'
S = pd.Series([valid]*45_000 + [invalid])
T = pd.to_datetime(S, format='%Y-%m-%d', exact=True)
################################
# Traceback redacted.
################################
ValueError: time data "N" doesn't match format "%Y-%m-%d", at position 1. You might want to try:
- passing `format` if your strings have a consistent format;
- passing `format='ISO8601'` if your strings are all ISO8601 but not necessarily in exactly the same format;
- passing `format='mixed'`, and the format will be inferred for each element individually. You might want to use `dayfirst` alongside this.Issue Description
As you can see a ValueError is raised. That is fine.
The description says it happens for item at postition 1, however, which is not correct. It happens for item at position 45000.
Expected Behavior
The correct position would be reported to the user. I'd like to do S[] and be able to see why it raised valueError.
Installed Versions
INSTALLED VERSIONS
commit : d9cdd2e
python : 3.11.8.final.0
python-bits : 64
OS : Linux
OS-release : 6.9.7-amd64
Version : #1 SMP PREEMPT_DYNAMIC Debian 6.9.7-1 (2024-06-27)
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : C.UTF-8
LOCALE : en_US.UTF-8
pandas : 2.2.2
numpy : 2.0.1
pytz : 2024.1
dateutil : 2.9.0.post0
setuptools : 68.1.2
pip : 24.1.1
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 : None
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2024.1
qtpy : None
pyqt5 : None