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BUG: Timestamp.to_julian_date() does not take into account timezone #54763

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2 of 3 tasks
danmoser opened this issue Aug 25, 2023 · 4 comments · May be fixed by #60280
Open
2 of 3 tasks

BUG: Timestamp.to_julian_date() does not take into account timezone #54763

danmoser opened this issue Aug 25, 2023 · 4 comments · May be fixed by #60280
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@tev-dixon
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Bug Timestamp pd.Timestamp and associated methods Timezones Timezone data dtype

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@danmoser
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Pandas version checks

  • I have checked that this issue has not already been reported.

  • I have confirmed this bug exists on the latest version of pandas.

  • I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

import pandas as pd
import pytz

ts = pd.Timestamp('1858-11-17T00:00:00.0', tzinfo=pytz.utc)
ts
# Timestamp('1858-11-17 00:00:00+0000', tz='UTC')
ts.to_julian_date()
# 2400000.5

ts = pd.Timestamp('1858-11-17T00:00:00.0', tzinfo=pytz.timezone('US/Mountain'))
ts
# Timestamp('1858-11-17 00:00:00-0700', tz='US/Mountain')
ts.to_julian_date()
# 2400000.5
# it should be 2400000.7916666665

pd.__version__
# '2.0.3'

pytz.__version__
# '2022.1'

Issue Description

Timestamp.to_julian_date() does not take into account the timezone information.

Expected Behavior

ts
# Timestamp('1858-11-17 00:00:00-0700', tz='US/Mountain')
ts.to_julian_date()
# 2400000.5
# it should be 2400000.7916666665

Installed Versions

INSTALLED VERSIONS
------------------
commit           : 0f437949513225922d851e9581723d82120684a6
python           : 3.8.13.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.18.0-372.32.1.el8_6.x86_64
Version          : #1 SMP Fri Oct 7 12:35:10 EDT 2022
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 2.0.3
numpy            : 1.23.1
pytz             : 2022.1
dateutil         : 2.8.2
setuptools       : 68.0.0
pip              : 23.2
Cython           : 0.29.15
pytest           : 7.3.1
hypothesis       : None
sphinx           : 4.3.0
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.9.1
html5lib         : 1.1
pymysql          : None
psycopg2         : 2.9.6
jinja2           : 3.1.2
IPython          : 7.29.0
pandas_datareader: None
bs4              : 4.12.0
bottleneck       : None
brotli           : None
fastparquet      : None
fsspec           : 2023.3.0
gcsfs            : None
matplotlib       : 3.5.1
numba            : None
numexpr          : None
odfpy            : None
openpyxl         : 3.1.2
pandas_gbq       : None
pyarrow          : None
pyreadstat       : None
pyxlsb           : None
s3fs             : None
scipy            : 1.9.0
snappy           : None
sqlalchemy       : 2.0.19
tables           : None
tabulate         : 0.8.9
xarray           : None
xlrd             : None
zstandard        : None
tzdata           : 2023.3
qtpy             : None
pyqt5            : None
@danmoser danmoser added Bug Needs Triage Issue that has not been reviewed by a pandas team member labels Aug 25, 2023
@rsm-23
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rsm-23 commented Aug 30, 2023

@danmoser can you please update the title with a meaningful description?

@danmoser danmoser changed the title BUG: BUG: Timestamp.to_julian_date() does not take into account timezone Aug 30, 2023
@danmoser
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@danmoser can you please update the title with a meaningful description?

Done!

@jbrockmendel jbrockmendel added the Timestamp pd.Timestamp and associated methods label Nov 1, 2023
@mroeschke mroeschke added Timezones Timezone data dtype and removed Needs Triage Issue that has not been reviewed by a pandas team member labels Jul 17, 2024
@AdamRJensen
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AdamRJensen commented Oct 2, 2024 •
edited
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This is indeed an issue! Julian Dates shouldn't be timezone dependent.

pandas/pandas/core/arrays/datetimes.py

Lines 2247 to 2278 in fd823d2

def to_julian_date(self) -> npt.NDArray[np.float64]:
"""
Convert Datetime Array to float64 ndarray of Julian Dates.
0 Julian date is noon January 1, 4713 BC.
https://en.wikipedia.org/wiki/Julian_day
"""
# http://mysite.verizon.net/aesir_research/date/jdalg2.htm
year = np.asarray(self.year)
month = np.asarray(self.month)
day = np.asarray(self.day)
testarr = month < 3
year[testarr] -= 1
month[testarr] += 12
return (
day
+ np.fix((153 * month - 457) / 5)
+ 365 * year
+ np.floor(year / 4)
- np.floor(year / 100)
+ np.floor(year / 400)
+ 1_721_118.5
+ (
self.hour
+ self.minute / 60
+ self.second / 3600
+ self.microsecond / 3600 / 10**6
+ self.nanosecond / 3600 / 10**9
)
/ 24
)

@tev-dixon
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take

@tev-dixon tev-dixon linked a pull request Nov 11, 2024 that will close this issue
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Bug Timestamp pd.Timestamp and associated methods Timezones Timezone data dtype
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BUG: Fix #54763 to_julian_date does not consider timezone tev-dixon/pandas
6 participants
@danmoser @jbrockmendel @mroeschke @AdamRJensen @tev-dixon @rsm-23