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BUG: AssertionError calling df.shift(axis=1) on empty DataFrame #57301

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Closed
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sfc-gh-joshi opened this issue Feb 8, 2024 · 3 comments
Closed
3 tasks done

BUG: AssertionError calling df.shift(axis=1) on empty DataFrame #57301

sfc-gh-joshi opened this issue Feb 8, 2024 · 3 comments
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Algos Non-arithmetic algos: value_counts, factorize, sorting, isin, clip, shift, diff Bug Regression Functionality that used to work in a prior pandas version
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@sfc-gh-joshi
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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
pd.DataFrame().shift(axis=1)

Issue Description

The above code raises an AssertionError:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/joshi/miniconda3/envs/pandas-latest/lib/python3.11/site-packages/pandas/core/frame.py", line 5799, in shift
    return super().shift(
           ^^^^^^^^^^^^^^
  File "/Users/joshi/miniconda3/envs/pandas-latest/lib/python3.11/site-packages/pandas/core/generic.py", line 10706, in shift
    assert axis == 0  # axis == 1 cases handled in DataFrame.shift
           ^^^^^^^^^
AssertionError

Expected Behavior

Shifting an empty dataframe should return an empty dataframe, regardless of axis (this behavior apparently worked in pandas 1.5.3).

Installed Versions

INSTALLED VERSIONS

commit : 7fe86b6
python : 3.11.7.final.0
python-bits : 64
OS : Darwin
OS-release : 23.3.0
Version : Darwin Kernel Version 23.3.0: Wed Dec 20 21:31:00 PST 2023; root:xnu-10002.81.5~7/RELEASE_ARM64_T6020
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 3.0.0.dev0+263.g7fe86b67d3
numpy : 2.0.0.dev0+git20240203.5c34c87
pytz : 2024.1
dateutil : 2.8.2
setuptools : 68.2.2
pip : 23.3.1
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 : 2023.4
qtpy : None

@sfc-gh-joshi sfc-gh-joshi added Bug Needs Triage Issue that has not been reviewed by a pandas team member labels Feb 8, 2024
@ajo2705
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ajo2705 commented Feb 8, 2024

Thanks for finding and reporting this issue.
Is anyone looking into this issue or can I investigate this issue..?

@simonjayhawkins simonjayhawkins added the Regression Functionality that used to work in a prior pandas version label Feb 8, 2024
@rhshadrach rhshadrach added this to the 2.2.1 milestone Feb 10, 2024
@lithomas1
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Go for it.

@lithomas1 lithomas1 added Algos Non-arithmetic algos: value_counts, factorize, sorting, isin, clip, shift, diff and removed Needs Triage Issue that has not been reviewed by a pandas team member labels Feb 10, 2024
@rhshadrach
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Closed by #57340

sfc-gh-joshi added a commit to snowflakedb/snowpark-python that referenced this issue May 2, 2024
…1) (#1470)

Please answer these questions before submitting your pull requests.
Thanks!

1. What GitHub issue is this PR addressing? Make sure that there is an
accompanying issue to your PR.

   Fixes SNOW-1357700

2. Fill out the following pre-review checklist:

- [ ] I am adding a new automated test(s) to verify correctness of my
new code
   - [ ] I am adding new logging messages
   - [ ] I am adding a new telemetry message
   - [ ] I am adding new credentials
   - [ ] I am adding a new dependency

3. Please describe how your code solves the related issue.

pandas bug pandas-dev/pandas#57301 was fixed
in 2.2.1, so we should remove the workaround for it.
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Labels
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