Skip to content

BUG: .diff() not working on int8 and int16 dtype #39050

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
3 tasks done
nrcjea001 opened this issue Jan 9, 2021 · 1 comment · Fixed by #39069
Closed
3 tasks done

BUG: .diff() not working on int8 and int16 dtype #39050

nrcjea001 opened this issue Jan 9, 2021 · 1 comment · Fixed by #39069
Labels
Algos Non-arithmetic algos: value_counts, factorize, sorting, isin, clip, shift, diff Dtype Conversions Unexpected or buggy dtype conversions Regression Functionality that used to work in a prior pandas version
Milestone

Comments

@nrcjea001
Copy link

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

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

  • (optional) I have confirmed this bug exists on the master branch of pandas.


# Your code here
df=pd.DataFrame({'a':[1,2,3,3,2],'b':[0,1,1,0,0]})
df['b']=df['b'].astype(np.int8)
df.groupby('a')['b'].diff()

---------------------------------------------------------------------------
NotImplementedError                       Traceback (most recent call last)
<ipython-input-23-f6026edf0092> in <module>
      1 df=pd.DataFrame({'a':[1,2,3,3,2],'b':[0,1,1,0,0]})
      2 df['b']=df['b'].astype(np.int8)
----> 3 df.groupby('a')['b'].diff()

~\Anaconda3\lib\site-packages\pandas\core\groupby\groupby.py in wrapper(*args, **kwargs)
    815                 return self.apply(curried)
    816 
--> 817             return self._python_apply_general(curried, self._obj_with_exclusions)
    818 
    819         wrapper.__name__ = name

~\Anaconda3\lib\site-packages\pandas\core\groupby\groupby.py in _python_apply_general(self, f, data)
    926             data after applying f
    927         """
--> 928         keys, values, mutated = self.grouper.apply(f, data, self.axis)
    929 
    930         return self._wrap_applied_output(

~\Anaconda3\lib\site-packages\pandas\core\groupby\ops.py in apply(self, f, data, axis)
    235             # group might be modified
    236             group_axes = group.axes
--> 237             res = f(group)
    238             if not _is_indexed_like(res, group_axes, axis):
    239                 mutated = True

~\Anaconda3\lib\site-packages\pandas\core\groupby\groupby.py in curried(x)
    804 
    805             def curried(x):
--> 806                 return f(x, *args, **kwargs)
    807 
    808             # preserve the name so we can detect it when calling plot methods,

~\Anaconda3\lib\site-packages\pandas\core\series.py in diff(self, periods)
   2436         {examples}
   2437         """
-> 2438         result = algorithms.diff(self.array, periods)
   2439         return self._constructor(result, index=self.index).__finalize__(
   2440             self, method="diff"

~\Anaconda3\lib\site-packages\pandas\core\algorithms.py in diff(arr, n, axis, stacklevel)
   2000         # TODO: can diff_2d dtype specialization troubles be fixed by defining
   2001         #  out_arr inside diff_2d?
-> 2002         algos.diff_2d(arr, out_arr, n, axis, datetimelike=is_timedelta)
   2003     else:
   2004         # To keep mypy happy, _res_indexer is a list while res_indexer is

pandas\_libs\algos.pyx in pandas._libs.algos.diff_2d()

NotImplementedError: 

Problem description

I try to take the difference of dataframe on columns with dtype int8 and int16 but this yields an error. This was working in previous version of pandas, 1.1.5, but not in current version, 1.2.0.

Expected Output

0    NaN
1    NaN
2    NaN
3   -1.0
4   -1.0

Output of pd.show_versions()

INSTALLED VERSIONS

commit : 3e89b4c
python : 3.8.6.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19041
machine : AMD64
processor : Intel64 Family 6 Model 142 Stepping 11, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252

pandas : 1.2.0
numpy : 1.19.5
pytz : 2020.5
dateutil : 2.8.1
pip : 20.3.3
setuptools : 49.6.0.post20210108
Cython : 0.29.21
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.6.2
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.19.0
pandas_datareader: None
bs4 : 4.9.3
bottleneck : None
fsspec : 0.8.5
fastparquet : None
gcsfs : None
matplotlib : 3.3.3
numexpr : 2.7.1
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 2.0.0
pyxlsb : None
s3fs : None
scipy : 1.6.0
sqlalchemy : None
tables : 3.6.1
tabulate : 0.8.7
xarray : 0.16.2
xlrd : None
xlwt : None
numba : 0.52.0

@nrcjea001 nrcjea001 added Bug Needs Triage Issue that has not been reviewed by a pandas team member labels Jan 9, 2021
@mzeitlin11
Copy link
Member

Thanks for the report @nrcjea001!

First bad commit 0013472, PR (#37140)

@mzeitlin11 mzeitlin11 added Regression Functionality that used to work in a prior pandas version Algos Non-arithmetic algos: value_counts, factorize, sorting, isin, clip, shift, diff Dtype Conversions Unexpected or buggy dtype conversions and removed Bug Needs Triage Issue that has not been reviewed by a pandas team member labels Jan 9, 2021
@jreback jreback added this to the 1.2.1 milestone Jan 10, 2021
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
Algos Non-arithmetic algos: value_counts, factorize, sorting, isin, clip, shift, diff Dtype Conversions Unexpected or buggy dtype conversions Regression Functionality that used to work in a prior pandas version
Projects
None yet
Development

Successfully merging a pull request may close this issue.

3 participants