BUG: pd.cut raises with duplicated index and include_lowest=True

[mlondschien]

• 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.

pandas.cut fails for a pandas.Series with non-unique index as input.

In [1]: import pandas as pd                                                                                                                  
   ...:        
   ...: s = pd.Series([0, 1, 2, 3, 0], index=[0, 1, 2, 3, 0])                                                                                
   ...:                                        
   ...: cut = pd.cut(s, [0, 2, 4])                                                                                                           
   ...: cut    
Out[1]:                                           
0           NaN                                                                                                                              
1    (0.0, 2.0]                                                
2    (0.0, 2.0]                            
3    (2.0, 4.0]                                                       
0           NaN                              
dtype: category                          
Categories (2, interval[int64]): [(0, 2] < (2, 4]]                                                                         
                                                                                                                                             
In [2]: cut = pd.cut(s, [0, 2, 4], include_lowest=True)                                                                                      
   ...: cut                                                           
/home/mlondschien/miniforge3/envs/quantcore.thek/lib/python3.9/site-packages/pandas/core/reshape/tile.py:410: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted a
s an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
  ids[x == bins[0]] = 1                                      
---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
~/miniforge3/envs/quantcore.thek/lib/python3.9/site-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance)
   3079             try:                          
-> 3080                 return self._engine.get_loc(casted_key)                                                                              
   3081             except KeyError as err:
                                                                                                                                             
pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()
                                                                                                                                             
pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()
                                                                      
pandas/_libs/index.pyx in pandas._libs.index.IndexEngine._get_loc_duplicates()
                                                                      
pandas/_libs/index_class_helper.pxi in pandas._libs.index.Int64Engine._maybe_get_bool_indexer()
                                                                                                                                             
pandas/_libs/index.pyx in pandas._libs.index.IndexEngine._unpack_bool_indexer()
                                                                      
KeyError: 4                                                           
                                                                      
The above exception was the direct cause of the following exception:                                                                                                                                                                                                                      
                                                                                                                                             
KeyError                                  Traceback (most recent call last)                                                                                                                                                                                                               
<ipython-input-5-00a66777dca1> in <module>    
----> 1 cut = pd.cut(s, [0, 2, 4], include_lowest=True)                                                                                      
      2 cut                                                                                                                                  
                                                                      
~/miniforge3/envs/quantcore.thek/lib/python3.9/site-packages/pandas/core/reshape/tile.py in cut(x, bins, right, labels, retbins, precision, include_lowest, duplicates, ordered)                                                                                                          
    271             raise ValueError("bins must increase monotonically.")                                                                    
    272                                                                                                                                                                                                                                                                                   
--> 273     fac, bins = _bins_to_cuts(                                                                                                       
    274         x,                                                                                                                           
    275         bins,                                                                                                                        
                                                                      
~/miniforge3/envs/quantcore.thek/lib/python3.9/site-packages/pandas/core/reshape/tile.py in _bins_to_cuts(x, bins, right, labels, precision, include_lowest, dtype, duplicates, ordered)
    408                                                                                                                                      
    409     if include_lowest:                                     
--> 410         ids[x == bins[0]] = 1                                                                                                        
    411                                                      
    412     na_mask = isna(x) | (ids == len(bins)) | (ids == 0)     
                                                                      
~/miniforge3/envs/quantcore.thek/lib/python3.9/site-packages/pandas/core/series.py in __getitem__(self, key)                                 
    851        
    852         elif key_is_scalar:                                                                                                          
--> 853             return self._get_value(key)
    854                                                                                                                                      
    855         if is_hashable(key):
                                                                      
~/miniforge3/envs/quantcore.thek/lib/python3.9/site-packages/pandas/core/series.py in _get_value(self, label, takeable)                      
    959                                                        
    960         # Similar to Index.get_value, but we do not fall back to positional
--> 961         loc = self.index.get_loc(label)                       
    962         return self.index._get_values_for_loc(self, loc, label)
    963                                  
                                                                      
~/miniforge3/envs/quantcore.thek/lib/python3.9/site-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance)
   3080                 return self._engine.get_loc(casted_key)
   3081             except KeyError as err:                           
-> 3082                 raise KeyError(key) from err                  
   3083                                           
   3084         if tolerance is not None:                                                                                                    
                                                                      
KeyError: 4

In [3]: cut = pd.cut(s.to_numpy(), [0, 2, 4], include_lowest=True)
   ...: cut
Out[3]: 
[(-0.001, 2.0], (-0.001, 2.0], (-0.001, 2.0], (2.0, 4.0], (-0.001, 2.0]]
Categories (2, interval[float64]): [(-0.001, 2.0] < (2.0, 4.0]]

import pandas as pd

s = pd.Series([0, 1, 2, 3, 0], index=[0, 1, 2, 3, 0])

cut = pd.cut(s, [0, 2, 4])
cut

cut = pd.cut(s, [0, 2, 4], include_lowest=True)

cut = pd.cut(s.to_numpy(), [0, 2, 4], include_lowest=True)
cut

In [8]: pd.show_versions()

INSTALLED VERSIONS
------------------
commit           : 2cb96529396d93b46abab7bbc73a208e708c642e
python           : 3.9.2.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.4.0-74-generic
Version          : #83-Ubuntu SMP Sat May 8 02:35:39 UTC 2021
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.2.4
numpy            : 1.19.5
pytz             : 2021.1
dateutil         : 2.8.1
pip              : 21.1.1
setuptools       : 49.6.0.post20210108
Cython           : None
pytest           : 6.2.3
hypothesis       : None
sphinx           : 3.5.4
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.3
IPython          : 7.23.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : 2021.04.0
fastparquet      : None
gcsfs            : None
matplotlib       : 3.4.2
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 3.0.0
pyxlsb           : None
s3fs             : None
scipy            : 1.6.3
sqlalchemy       : None
tables           : None
tabulate         : 0.8.9
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

[simonjayhawkins]

Thanks @mlondschien for the report

just to confirm, expected output?

0    (-0.001, 2.0]
1    (-0.001, 2.0]
2    (-0.001, 2.0]
3       (2.0, 4.0]
0    (-0.001, 2.0]
dtype: category
Categories (2, interval[float64]): [(-0.001, 2.0] < (2.0, 4.0]]

[mlondschien]

Yes, this looks reasonable. Thanks!

[debnathshoham]

take