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
import pandas as pd
assert pd.__version__ == '2.2.0'
# example from the book "Effective Pandas 2 (by Matt Harrison)"
classes = ['cs106', 'cs150', 'hist205', 'hist206', 'hist207']
start_dates = (
pd.Series([
'2015-03-08',
'2015-03-08',
'2015-03-09',
'2015-03-09',
'2015-03-11'
], dtype='datetime64[ns]', index=classes
).astype('timestamp[ns][pyarrow]'))
end_dates = (
pd.Series([
'2015-05-28 23:59:59',
'2015-06-01 3:00:00',
'2015-06-03',
'2015-06-02 14:20',
'2015-06-01'
], dtype='datetime64[ns]', index=classes
).astype('timestamp[ns][pyarrow]'))
duration = (end_dates - start_dates)Issue Description
These are the data:
print(duration)cs106 81 days 23:59:59
cs150 85 days 03:00:00
hist205 86 days 00:00:00
hist206 85 days 14:20:00
hist207 82 days 00:00:00
dtype: duration[ns][pyarrow]
I noticed that calling .dt.components on the above duration object behaves differently for the 'timestamp[ns][pyarrow]' vs. the 'timedelta64[ns]' data types. For the former, the seconds attribute (column) give a very high value (and I assume it is total seconds for the 'HH:MM:SS' part.
print(duration.dt.components)results in:
days hours minutes seconds milliseconds microseconds nanoseconds
0 81 23 59 86399 0 0 0
1 85 3 0 10800 0 0 0
2 86 0 0 0 0 0 0
3 85 14 20 51600 0 0 0
4 82 0 0 0 0 0 0
Expected Behavior
Converting to pandas 1.x 'timedelta64[ns]' give an expected result:
print(duration.astype('timedelta64[ns]').dt.components)results in:
days hours minutes seconds milliseconds microseconds nanoseconds
cs106 81 23 59 59 0 0 0
cs150 85 3 0 0 0 0 0
hist205 86 0 0 0 0 0 0
hist206 85 14 20 0 0 0 0
hist207 82 0 0 0 0 0 0
Installed Versions
INSTALLED VERSIONS
commit : f538741
python : 3.12.1.final.0
python-bits : 64
OS : Darwin
OS-release : 21.6.0
Version : Darwin Kernel Version 21.6.0: Sun Nov 6 23:31:13 PST 2022; root:xnu-8020.240.14~1/RELEASE_ARM64_T6000
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : de_DE.UTF-8
LOCALE : de_DE.UTF-8
pandas : 2.2.0
numpy : 1.26.4
pytz : 2024.1
dateutil : 2.8.2
setuptools : 69.0.3
pip : 24.0
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 : 8.21.0
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 : 15.0.0
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.4
qtpy : None
pyqt5 : None