Description
Pandas version checks
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I have checked that this issue has not already been reported.
-
I have confirmed this bug exists on the latest version of pandas. (confirmed on
1.5.1,1.5.2is not yet available on pip) -
I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
import pandas as pd
freq = pd.offsets.BusinessHour(start="9:00", end="17:00")
x = pd.DatetimeIndex(["20200106 09:00"], name="time", freq=freq) # Works
x = pd.DatetimeIndex(["20200106 09:00","20200106 10:00"], name="time", freq=freq) # Works
x = pd.DatetimeIndex(["20200106 10:00"], name="time", freq=freq) # FailsIssue Description
Creation of DatetimeIndex with BusinessHour frequency fails when the ts_input arg to DatetimeIndex does not start at BusinessHour start time, resulting in the following error:
Traceback (most recent call last):
File "C:\Users\...\site-packages\pandas\core\arrays\datetimelike.py", line 962, in _validate_frequency
raise ValueError
ValueError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "C:\Users\...\site-packages\pandas\core\indexes\datetimes.py", line 327, in __new__
dtarr = DatetimeArray._from_sequence_not_strict(
File "C:\Users\...\site-packages\pandas\core\arrays\datetimes.py", line 377, in _from_sequence_not_strict
cls._validate_frequency(result, freq, ambiguous=ambiguous)
File "C:\Users\...\site-packages\pandas\core\arrays\datetimelike.py", line 973, in _validate_frequency
raise ValueError(
ValueError: Inferred frequency None from passed values does not conform to passed frequency BH
Expected Behavior
Returns the specified Timestamp without error.
Installed Versions
INSTALLED VERSIONS
commit : e8093ba
python : 3.10.4.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19045
machine : AMD64
processor : Intel64 Family 6 Model 167 Stepping 1, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : German_Austria.1252
pandas : 1.4.3
numpy : 1.22.4
pytz : 2022.4
dateutil : 2.8.2
setuptools : 59.8.0
pip : 22.2.2
Cython : 0.29.32
pytest : 7.2.0
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : 2.9.4
jinja2 : None
IPython : 8.5.0
pandas_datareader: None
bs4 : None
bottleneck : None
brotli : None
fastparquet : None
fsspec : 2022.8.2
gcsfs : None
markupsafe : 2.1.1
matplotlib : 3.6.0
numba : 0.56.2
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.9.1
snappy : None
sqlalchemy : 1.4.41
tables : None
tabulate : None
xarray : 2022.9.0
xlrd : None
xlwt : None
zstandard : None