qcut bin formatting bugs

[sunfaquir]

I'm reading CSV tables and then use qcut to bin the continuous numbers. Given the number of bins, most of the time the qcut works fine. However, some times, it doesn't function correctly. The following are some weird cases I got in the result levels index. Sorry I can't give the experimental data now because I'm running it on a very large data collections and currently I'm not allowed to public the data

(1) When dealing with negative numbers, sometimes it gives [-117.-1, 1], This happens at the first bin index in my test case.
(2) when bin# is two, it gives results like [1, 2005], (2005, 2005]
(3)a bin result like this: please note the value 0.993, and value 0.1
array([[0.6, 0.991], (0.991, 0.992], (0.992, 0.993], (0.993, 0.993],
(0.993, 0.994], (0.994, 0.995], (0.995, 0.996], (0.996, 0.997],
(0.997, 0.998], (0.998, 0.1], (0.1, 1.2], (1.2, 1.5], (1.5, 2.1],
(2.1, 3.5], (3.5, 5.2], (5.2, 7.1], (7.1, 8.5], (8.5, 11],
(11, 13.7], (13.7, 65.8]], dtype=object)

(2) and (3) might be caused by the same reason

I'm using pandas 0.8.1 thanks.

[wesm]

related also #1978

[wesm]

Could you give some sufficiently anonymized data that illustrates these issues?

[sunfaquir]

Sure. please allow me some time to post it.
For case(3), using the following data as a column tmpcol
pd.qcut(tmpcol, 20), I got the bin's levels as

array([[0.6, 0.991], (0.991, 0.992], (0.992, 0.993], (0.993, 0.993],
(0.993, 0.994], (0.994, 0.995], (0.995, 0.996], (0.996, 0.997],
(0.997, 0.998], (0.998, 0.1], (0.1, 1.2], (1.2, 1.5], (1.5, 2.1],
(2.1, 3.5], (3.5, 5.2], (5.2, 7.1], (7.1, 8.5], (8.5, 11],
(11, 13.7], (13.7, 65.8]], dtype=object)

Note (0.993, 0.993], and (0.998, 0.1]

[sunfaquir]

1.001
0.994
0.9951
0.9956
0.9956
0.9951
0.9949
1.001
0.994
0.9938
0.9908
0.9947
0.992
0.9912
1.0002
0.9914
0.9928
0.9892
0.9917
0.9955
0.9892
0.9912
0.993
0.9937
0.9951
0.9955
0.993
0.9961
0.9914
0.9906
0.9974
0.9934
0.992
0.9939
0.9962
0.9905
0.9934
0.9906
0.9999
0.9999
0.9937
0.9937
0.9954
0.9934
0.9934
0.9931
0.994
0.9939
0.9954
0.995
0.9917
0.9914
0.991
0.9911
0.993
0.9908
0.9962
0.9972
0.9931
0.9926
0.9951
0.9972
0.991
0.9931
0.9927
0.9934
0.9903
0.992
0.9926
0.9962
0.9956
0.9958
0.9964
0.9941
0.9926
0.9962
0.9898
0.9912
0.9961
0.9949
0.9929
0.9985
0.9946
0.9966
0.9974
0.9975
0.9974
0.9972
0.9974
0.9975
0.9974
0.9957
0.99
0.9899
0.9916
0.9969
0.9979
0.9913
0.9956
0.9979
0.9975
0.9962
0.997
1
0.9975
0.9974
0.9962
0.999
0.999
0.9927
0.9959
1
0.9982
0.9968
0.9968
0.994
0.9914
0.9911
0.9982
0.9982
0.9934
0.9984
0.9952
0.9952
0.9928
0.9912
0.994
0.9958
0.9924
0.9924
0.994
0.9958
0.9979
0.9982
0.9961
0.9979
0.992
0.9975
0.9917
0.9923
0.9927
0.9975
0.992
0.9947
0.9921
0.9905
0.9918
0.9951
0.9917
0.994
0.9934
0.9968
0.994
0.9919
0.9966
0.9979
0.9979
0.9898
0.9894
0.9894
0.9898
0.998
0.9932
0.9979
0.997
0.9972
0.9974
0.9896
0.9968
0.9958
0.9906
0.9917
0.9902
0.9918
0.999
0.9927
0.991
0.9972
0.9931
0.995
0.9951
0.9936
1.001
0.9979
0.997
0.9972
0.9954
0.9924
0.9906
0.9962
0.9962
1.001
0.9928
0.9942
0.9942
0.9942
0.9942
0.9961
0.998
0.9961
0.9984
0.998
0.9973
0.9949
0.9924
0.9972
0.9958
0.9968
0.9938
0.993
0.994
0.9918
0.9958
0.9944
0.9912
0.9961
0.9939
0.9961
0.9989
0.9938
0.9939
0.9971
0.9912
0.9936
0.9929
0.9998
0.9938
0.9969
0.9938
0.9998
0.9972
0.9976
0.9976
0.9979
0.9979
0.9979
0.9979
0.9972
0.9918
0.9982
0.9985
0.9944
0.9903
0.9934
0.9975
0.9923
0.99
0.9905
0.9905
0.996
0.9964
0.998
0.9975
0.9913
0.9932
0.9935
0.9927
0.9927
0.9912
0.9904
0.9939
0.9996
0.9944
0.9977
0.9912
0.9996
0.9965
0.9944
0.9945
0.9944
0.9965
0.9944
0.9972
0.9949
0.9966
0.9954
0.9954
0.9915
0.9919
0.9916
0.99
0.9909
0.9938
0.9982
0.9988
0.9961
0.9978
0.9979
0.9979
0.9979
0.9979
0.9945
1
0.9957
0.9968
0.9934
0.9976
0.9932
0.997
0.9923
0.9914
0.992
0.9914
0.9914
0.9949
0.9949
0.995
0.995
0.9927
0.9928
0.9917
0.9918
0.9954
0.9941
0.9941
0.9934
0.9927
0.9938
0.9933
0.9934
0.9927
0.9938
0.9927
0.9946
0.993
0.9946
0.9976
0.9944
0.9978
0.992
0.9912
0.9927
0.9906
0.9954
0.9923
0.9906
0.991
0.9972
0.9945
0.9934
0.9964
0.9948
0.9962
0.9931
0.993
0.9942
0.9906
0.9995
0.998
0.997
0.9914
0.992
0.9924
0.992
0.9937
0.9978
0.9978
0.9927
0.994
0.9935
0.9968
0.9941
0.9942
0.9978
0.9923
0.9912
0.9923
0.9927
0.9931
0.9941
0.9927
0.9931
0.9934
0.9936
0.9893
0.9893
0.9919
0.9924
0.9927
0.9919
0.9924
0.9975
0.9969
0.9936
0.991
0.9893
0.9906
0.9941
0.995
0.9983
0.9983
0.9916
0.9957
0.99
0.9976
0.992
0.9917
0.9917
0.9993
0.9908
0.9917
0.9976
0.9934
1
0.9918
0.992
0.9896
0.9932
0.992
0.9917
0.9999
0.998
0.9918
0.9918
0.9999
0.998
0.9927
0.9959
0.9927
0.9929
0.9898
0.9954
0.9954
0.9954
0.9954
0.9954
0.9954
0.9974
0.9936
0.9978
0.9974
0.9927
0.9934
0.9938
0.9922
0.992
0.9935
0.9906
0.9934
0.9934
0.9913
0.9938
0.9898
0.9975
0.9975
0.9937
0.9914
0.9982
0.9982
0.9929
0.9971
0.9921
0.9931
0.9924
0.9929
0.9982
0.9892
0.9956
0.9924
0.9971
0.9956
0.9982
0.9973
0.9932
0.9976
0.9962
0.9956
0.9932
0.9976
0.9992
0.9983
0.9937
0.99
0.9944
0.9938
0.9965
0.9893
0.9927
0.994
0.9928
0.9964
0.9917
0.9972
0.9964
0.9954
0.993
0.9928
0.9916
0.9936
0.9962
0.9899
0.9898
0.996
0.9907
0.994
0.9913
0.9976
0.9904
0.992
0.9976
0.999
0.9975
0.9937
0.9937
0.998
0.998
0.9944
0.9938
0.9907
0.9938
0.9921
0.9908
0.9931
0.9915
0.9952
0.9926
0.9934
0.992
0.9918
0.9942
0.9942
0.9942
0.9901
0.9898
0.9902
0.9934
0.9906
0.9898
0.9896
0.9922
0.9947
0.9945
0.9976
0.9976
0.9976
0.9987
0.9987
0.9976
0.992
0.9955
0.9953
0.9976
0.992
0.9952
0.9983
0.9933
0.9958
0.9922
0.9928
0.9976
0.9976
0.9916
0.9901
0.9976
0.9901
0.9916
0.9982
0.993
0.9969
0.991
0.9953
0.9924
0.9969
0.9928
0.9945
0.9967
0.9944
0.9928
0.9929
0.9948
0.9976
0.9912
0.9987
0.99
0.991
0.9933
0.9933
0.9899
0.9912
0.9912
0.9976
0.994
0.9947
0.9954
0.993
0.9954
0.9963
0.992
0.9926
0.995
0.9983
0.992
0.9968
0.9905
0.9904
0.9926
0.9968
0.9928
0.9949
0.9909
0.9937
0.9914
0.9905
0.9904
0.9924
0.9924
0.9965
0.9965
0.9993
0.9965
0.9908
0.992
0.9978
0.9978
0.9978
0.9978
0.9912
0.9928
0.9928
0.993
0.9993
0.9965
0.9937
0.9913
0.9934
0.9952
0.9983
0.9957
0.9957
0.9916
0.9999
0.9999
0.9936
0.9972
0.9933
0.9934
0.9931
0.9976
0.9937
0.9937
0.991
0.9979
0.9971
0.9969
0.9968
0.9961
0.993
0.9973
0.9944
0.9986
0.9986
0.9986
0.9986
0.9972
0.9917
0.992
0.9932
0.9936
0.9915
0.9922
0.9934
0.9952
0.9972
0.9934
0.9958
0.9944
0.9908
0.9958
0.9925
0.9966
0.9972
0.9912
0.995
0.9928
0.9968
0.9955
0.9981
0.991
0.991
0.991
0.992
0.9931
0.997
0.9948
0.9923
0.9976
0.9938
0.9984
0.9972
0.9922
0.9935
0.9944
0.9942
0.9944
0.9997
0.9977
0.9912
0.9982
0.9982
0.9983
0.998
0.9894
0.9927
0.9917
0.9904
0.993
0.9941
0.9943
0.99855
0.99345
0.998
0.9916
0.9916
0.99475
0.99325
0.9933
0.9969
1.0002
0.9933
0.9937
0.99685
0.99455
0.9917
0.99035
0.9914
0.99225
0.99155
0.9954
0.99455
0.9924
0.99695
0.99655
0.9934
0.998
0.9971
0.9948
0.998
0.9971
0.99215
0.9948
0.9915
0.99115
0.9932
0.9977
0.99535
0.99165
0.9953
0.9928
0.9958
0.9928
0.9928
0.9964
0.9987
0.9953
0.9932
0.9907
0.99755
0.99935
0.9932
0.9932
0.9958
0.99585
1.00055
0.9985
0.99505
0.992
0.9988
0.99175
0.9962
0.9962
0.9942
0.9927
0.9927
0.99985
0.997
0.9918
0.99215
0.99865
0.9992
1.0006
0.99135
0.99715
0.9992
1.0006
0.99865
0.99815
0.99815
0.99815
0.9949
0.99815
0.99815
0.99225
0.99445
0.99225
0.99335
0.99625
0.9971
0.9983
0.99445
0.99085
0.9977
0.9953
0.99775
0.99795
0.99505
0.9977
0.9975
0.99745
0.9976
0.99775
0.9953
0.9932
0.99405
1
0.99785
0.9939
0.9939
0.99675
0.9939
0.99675
0.98965
0.9971
0.99445
0.9945
0.9939
0.9958
0.9956
0.99055
0.9959
0.9925
0.9963
0.9935
0.99105
0.99045
0.9963
0.99155
0.99085
0.99085
0.99085
0.9924
0.9924
0.99975
0.99975
0.99315
0.9917
0.9917
0.99845
0.9921
0.99975
0.9909
0.99315
0.99855
0.9934
0.9978
0.9934
0.9949
0.99855
0.9986
0.99725
0.9946
0.99255
0.9996
0.9939
0.99
0.9937
0.9886
0.9934
1
0.9994
0.9926
0.9956
0.9978
0.9915
0.9939
0.9932
0.993
0.9898
0.9921
0.9932
0.9919
0.993
0.9953
0.9928
0.9928
0.9976
0.9906
0.9918
0.99185
0.9918
0.99185
0.994
0.9908
0.9928
0.9896
0.9908
0.9918
0.9952
0.9923
0.9915
0.9952
0.9947
0.9983
0.9975
0.995
0.9944
0.994
0.9944
0.9908
0.99795
0.9985
0.99425
0.99425
0.9943
0.9924
0.9946
0.9924
0.995
0.9919
0.99
0.9923
0.9956
0.9978
0.9978
0.9967
0.9934
0.9936
0.9932
0.9934
0.998
0.9978
0.9929
0.9974
0.99685
0.99495
0.99745
0.99505
0.992
0.9978
0.9956
0.9982
0.99485
0.9971
0.99265
0.9904
0.9965
0.9946
0.99965
0.9935
0.996
0.9942
0.9936
0.9965
0.9928
0.9928
0.9965
0.9936
0.9938
0.9926
0.9926
0.9983
0.9983
0.992
0.9983
0.9923
0.9972
0.9928
0.9928
0.9994
0.991
0.9906
0.9894
0.9898
0.9994
0.991
0.9925
0.9956
0.9946
0.9966
0.9951
0.9927
0.9927
0.9951
0.9894
0.9907
0.9925
0.9928
0.9941
0.9941
0.9925
0.9935
0.9932
0.9944
0.9972
0.994
0.9956
0.9927
0.9924
0.9966
0.9997
0.9936
0.9936
0.9952
0.9952
0.9928
0.9911
0.993
0.9911
0.9932
0.993
0.993
0.9932
0.9932
0.9943
0.9968
0.9994
0.9926
0.9968
0.9932
0.9916
0.9946
0.9925
0.9925
0.9935
0.9962
0.9928
0.993
0.993
0.9956
0.9941
0.9972
0.9948
0.9955
0.9972
0.9972
0.9983
0.9942
0.9936
0.9956
0.9953
0.9918
0.995
0.992
0.9952
1.001
0.9924
0.9932
0.9937
0.9918
0.9934
0.991
0.9962
0.9932
0.9908
0.9962
0.9918
0.9941
0.9931
0.9981
0.9931
0.9944
0.992
0.9966
0.9956
0.9956
0.9949
1.0002
0.9942
0.9923
0.9917
0.9931
0.992
1.0002
0.9953
0.9951
0.9974
0.9904
0.9974
0.9944
1.0004
0.9952
0.9956
0.995
0.995
0.9995
0.9942
0.9977
0.992
0.992
0.9995
0.9934
1.0006
0.9982
0.9928
0.9945
0.9963
0.9906
0.9956
0.9942
0.9962
0.9894
0.995
0.9908
0.9914
0.9938
0.9977
0.9922
0.992
0.9903
0.9893
0.9952
0.9903
0.9912
0.9983
0.9937
0.9932
0.9928
0.9922
0.9976
0.9922
0.9974
0.998
0.9931
0.9911
0.9944
0.9937
0.9974
0.989
0.992
0.9928
0.9918
0.9936
0.9944
0.9988
0.994
0.9953
0.9986
0.9914
0.9934
0.996
0.9937
0.9921
0.998
0.996
0.9933
0.9933
0.9959
0.9936
0.9953
0.9938
0.9952
0.9959
0.9959
0.9937
0.992
0.9967
0.9944
0.9998
0.9998
0.9942
0.9998
0.9945
0.9998
0.9946
0.9942
0.9928
0.9946
0.9927
0.9938
0.9918
0.9945
0.9966
0.9954
0.9913
0.9931
0.9986
0.9965
0.9984
0.9952
0.9956
0.9949
0.9954
0.996
0.9931
0.992
0.9912
0.9978
0.9938
0.9914
0.9932
0.9944
0.9913
0.9948
0.998
0.9998
0.9964
0.9992
0.9948
0.9998
0.998
0.9939
0.992
0.9922
0.9955
0.9917
0.9917
0.9954
0.9986
0.9955
0.9917
0.9907
0.9922
0.9958
0.993
0.9917
0.9926
0.9959
0.9906
0.9993
0.993
0.9906
0.992
0.992
0.994
0.9959
0.9908
0.9902
0.9908
0.9943
0.9921
0.9911
0.9986
0.992
0.992
0.9943
0.9937
0.993
0.9902
0.9928
0.9896
0.998
0.9954
0.9938
0.9918
0.9896
0.9944
0.9999
0.9953
0.992
0.9925
0.9981
0.9952
0.9927
0.9927
0.9911
0.9936
0.9959
0.9946
0.9948
0.9955
0.9951
0.9952
0.9946
0.9946
0.9944
0.9938
0.9963
0.991
1.0003
0.9966
0.9993
1.0003
0.9938
0.9965
0.9938
0.9993
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0.99704
0.9911
0.99334
0.99334
0.99094
0.99014
0.99304
0.99652
0.98944
0.99772
0.99367
0.99304
0.99183
0.99126
0.98944
0.99577
0.99772
0.99652
0.99428
0.99388
0.99208
0.99256
0.99388
0.9925
0.99904
0.99216
0.99208
0.99428
0.99165
0.99924
0.99924
0.99924
0.9956
0.99562
0.9972
0.99924
0.9958
0.99976
0.99976
0.99296
0.9957
0.9958
0.99579
0.99541
0.99976
0.99518
0.99168
0.99276
0.99085
0.99873
0.99172
0.99312
0.99276
0.9972
0.99278
0.99092
0.9962
0.99053
0.99858
0.9984
0.99335
0.99053
0.9949
0.9962
0.99092
0.99532
0.99727
0.99026
0.99668
0.99727
0.9952
0.99144
0.99144
0.99015
0.9914
0.99693
0.99035
0.99693
0.99035
0.99006
0.99126
0.98994
0.98985
0.9971
0.99882
0.99477
0.99478
0.99576
0.99578
0.99354
0.99244
0.99084
0.99612
0.99356
0.98952
0.99612
0.99084
0.99244
0.99955
0.99374
0.9892
0.99144
0.99352
0.99352
0.9935
0.99237
0.99144
0.99022
0.99032
1.03898
0.99587
0.99587
0.99587
0.99976
0.99354
0.99976
0.99552
0.99552
0.99587
0.99604
0.99584
0.98894
0.9963
0.993
0.98894
0.9963
0.99068
0.98964
0.99604
0.99584
0.9923
0.99437
0.993
0.99238
0.99801
0.99802
0.99566
0.99067
0.99066
0.9929
0.9934
0.99067
0.98912
0.99066
0.99228
0.98912
0.9958
0.99052
0.99312
0.9968
0.99502
0.99084
0.99573
0.99256
0.9959
0.99084
0.99084
0.99644
0.99526
0.9954
0.99095
0.99188
0.9909
0.99256
0.9959
0.99581
0.99132
0.98936
0.99136
0.99142
0.99232
0.99232
0.993
0.99311
0.99132
0.98993
0.99208
0.99776
0.99839
0.99574
0.99093
0.99156
0.99278
0.9924
0.98984
0.99035
0.9924
0.99165
0.9923
0.99278
0.99008
0.98964
0.99156
0.9909
0.98984
0.9889
0.99178
0.99076
0.9889
0.99046
0.98999
0.98946
0.98976
0.99046
0.99672
0.99482
0.98945
0.98883
0.99362
0.99075
0.99436
0.98988
0.99158
0.99265
0.99195
0.99168
0.9918
0.99313
0.9895
0.9932
0.99848
0.9909
0.99014
0.9952
0.99652
0.99848
0.99104
0.99772
0.9922
0.99076
0.99622
0.9902
0.99114
0.9938
0.99594
0.9902
0.99035
0.99032
0.99558
0.99622
0.99076
0.99413
0.99043
0.99043
0.98982
0.98934
0.9902
0.99449
0.99629
0.9948
0.98984
0.99326
0.99834
0.99555
0.98975
0.99216
0.99216
0.99834
0.9901
0.98975
0.99573
0.99326
0.99215
0.98993
0.99218
0.99555
0.99564
0.99564
0.99397
0.99576
0.99601
0.99564
0.99397
0.98713
0.99308
0.99308
0.99582
0.99494
0.9929
0.99471
0.9929
0.9929
0.99037
0.99304
0.99026
0.98986
0.99471
0.98951
0.99634
0.99368
0.99792
0.99026
0.99362
0.98919
0.99835
0.99835
0.99038
0.99104
0.99038
0.99286
0.99296
0.99835
0.9954
0.9914
0.99286
0.99604
0.99604
0.99119
0.99007
0.99507
0.99596
0.99011
0.99184
0.99469
0.99469
0.99406
0.99305
0.99096
0.98956
0.9921
0.99496
0.99406
0.99406
0.9888
0.98942
0.99082
0.98802
17.3
1.4
1.3
1.6
5.25
2.4
14.6
11.8
1.5
1.8
7.7
2
1.8
1.4
16.7
8.1
8
4.7
8.1
2.1
16.7
6.4
1.5
7.6
1.5
12.4
1.3
1.7
8.1
7.1
7.6
2.3
6.5
1.4
12.7
1.6
1.1
1.2
6.5
4.6
0.6
10.6
4.6
4.8
2.7
12.6
0.6
9.2
6.6
7
8.45
11.1
18.15
18.15
4.1
4.1
4.6
18.15
4.9
8.3
1.4
11.5
1.8
1.6
2.4
4.9
1.8
4.3
4.4
1.4
1.6
1.3
5.2
5.6
5.3
4.9
2.4
1.6
2.1
1.4
7.1
1.6
10.7
11.1
10.7
1.6
1.6
1.5
1.5
1.6
1.6
8
7.7
2.7
15.1
15.1
8.9
6
12.3
13.1
6.7
12.3
2.3
11.1
1.5
6.7
6
15.2
10.2
13.1
10.7
17.1
17.1
17.1
1.9
10.7
17.1
1.2
1.2
3.1
1.5
10.7
4.9
12.6
10.7
4.9
12.15
12
1.7
2.6
1.4
1.9
16.9
16.9
2.1
7
7.1
5.9
7.1
8.7
13.2
15.3
15.3
13.2
2.7
10.65
10
6.8
15.6
13.2
5.1
3
15.3
2.1
1.9
8.6
8.75
3.6
4.7
1.3
1.8
9.7
4
2.4
4.7
18.8
1.8
1.8
12.8
12.8
12.8
12.8
12.8
7.8
16.75
12.8
12.8
7.8
5.4
16.75
1.3
10.1
3.8
10.9
6.6
9.8
11.7
1.2
1.4
9.6
12.2
2.6
10.7
4.9
12.2
9.6
1.4
1.1
1
8.2
11.3
7.3
2.3
8.2
2.1
2
10
15.75
3.9
2
1.5
1.6
1.4
1.5
1.4
2
13.8
1.3
3.8
6.9
2.2
1.6
13.8
10.8
12.8
10.8
15.3
12.1
12
11.6
9.2
11.6
9.2
2.8
1.6
6.1
8.5
7.8
14.9
6.2
8.5
8.2
7.8
10.6
11.2
11.6
7.1
14.9
6.2
1.7
7.7
17.3
1.4
7.7
7.7
3.4
1.6
1.4
1.4
10.4
1.4
10.4
4.1
2.8
15.7
10.9
15.7
6.5
10.9
5.9
17.3
1.4
13.5
8.5
6.2
1.4
14.95
7.7
1.3
7.7
1.3
1.3
1.3
15.6
15.6
15.6
15.6
4.9
5
15.6
6.5
1.4
2.7
1.2
6.5
6.4
6.9
7.2
10.6
3.5
6.4
2.3
12.05
7
11.8
1.4
5
2.2
14.6
1.6
1.3
14.6
2.8
1.6
3.3
6.3
8.1
1.6
10.6
11.8
1.7
8.1
1.4
1.3
1.8
7.2
1.1
11.95
1.1
11.95
2.2
12.7
1.4
10.6
1.9
17.8
10.2
4.8
9.8
8.4
7.2
4.8
8.4
4.5
1.4
7.2
11
11.1
2.6
2
10.1
13.3
11.4
1.3
1.4
1.4
7
2
1.2
12.9
5
10.1
3.75
1.7
12.6
1.3
1.6
7.6
8.1
14.9
6
6
7.2
3
1.2
2
4.9
2
8.9
16.45
2
1.9
5.1
4.4
5.8
4.4
12.9
1.3
1.3
1.2
2.7
1.7
8.2
1.5
1.5
12.9
3.9
17.75
4.9
1.6
1.4
2
2
8.2
2.1
1.8
8.5
4.45
5.8
13
2.7
7.3
19.1
8.8
2.7
7.4
2.3
6.85
11.4
0.9
19.35
7.9
11.75
7.7
3
7.7
3
1.5
7.5
1.5
7.5
8.3
7.05
8.4
13.9
17.5
5.6
9.4
4.8
9.4
9.7
6.3
1.6
14.6
2.5
14.6
2.6
2.5
8.2
1.5
2.3
10
10
1.6
1.6
16
10.4
7.4
7.4
10.4
16.05
16.05
2.6
2.5
10.8
1.2
12.1
11.95
1.7
0.8
1.4
1.3
6.3
10.3
15.55
1.5
1.5
1.4
1.5
7.9
13
1
4.85
7.1
7.9
7.5
7.6
10.3
1.7
1.7
19.95
7.7
5.3
19.95
12.7
12.7
1.5
11.3
18.1
18.1
7
18.1
6.4
1.4
1.4
3.1
14.1
7.7
5.2
11.6
10.4
7.5
11.2
0.8
1.4
4.7
3.1
4
11.3
3.1
8.1
14.8
1.4
8.1
3.5
14.8
8.1
1.4
1.5
1.5
12.8
1.6
7.1
7.1
11.2
1.7
6.7
17.3
8.6
8.6
1.5
12.1
6.7
10.7
17.3
1.8
1.4
7.5
4.8
7.1
16.9
4.8
7.1
11.3
1.1
1.2
1.1
12.9
1.2
1.1
1.2
2.3
10
2.3
1.2
1.4
14.9
1.8
1.8
7
8.6
1.8
1.1
1.3
4.9
1.9
10.4
10
8.6
1.7
1.7
18.95
12.8
12.8
12.8
12.8
12.8
12.8
0.7
12.8
1.4
13.3
8.5
1.5
11.7
5
1.2
2.1
1.4
2.1
16
1.1
15.3
1.4
2.8
2.8
0.9
2.5
8.1
8.2
0.9
11.1
7.8
2.8
10.1
3.2
14.2
14.2
14.2
2.9
6
20.4
10.1
2.9
14.2
3.2
0.95
1.7
1.7
9
1.3
1.4
2.4
16
11.4
14.35
2.1
11.4
14.35
1.1
1.1
1.2
15.8
5.2
5.2
9.6
5.2
1.2
0.8
14.45
9.6
6.9
3.4
2.3
11
5.95
5.1
5.4
1.2
12.6
1
6.6
1.5
1
1.1
6.6
8.2
2
1.4
2
7.5
2
2
13.3
2.85
5.6
5.6
1
3.2
1
7.1
2.4
11.2
9.5
1
1.8
2.6
2.4
8
11.2
7.1
3.3
10.3
1.2
1.6
10.3
9.65
16.4
1.5
1.2
3.3
5
16.3
16.3
16.3
6.5
6.4
10.2
16.3
7.4
13.7
13.7
1.3
7.4
7.4
7.45
7.2
13.7
10.4
1.1
6.5
4.6
13.9
5.2
1.7
6.5
16.4
3.6
1.5
12.4
1.7
6.2
6.2
2.6
1.7
9.3
12.4
1.5
9.1
12
4.8
12.3
12
2.7
3.6
3.6
4.3
1.8
11.8
1.8
11.8
1.8
1.4
6.6
1.55
0.7
6.4
11.8
4.3
5.1
5.8
5.9
1.3
1.4
1.2
7.4
10.8
1.8
7.4
1.2
1.4
14.4
1.7
3.6
3.6
10.05
10.05
10.5
1.9
3.6
1.65
1.9
65.8
6.85
7.4
7.4
20.2
11
20.2
6.2
6.2
6.85
8
8.2
2.2
10.1
7.2
2.2
10.1
1.6
1.3
8
8.2
5.3
14
7.2
1.6
11.8
9.6
6.1
2.7
3.6
1.7
1.6
2.7
1
0.9
1.6
1
10.6
2
1.2
6.2
9.2
5
6.3
3.3
8
1.2
1.2
16.2
11.6
7.2
1.1
3.4
1.4
3.3
8
9.3
2.3
0.9
3.5
1.7
1.3
1.3
5.6
7.4
2.3
1
1.5
10
14.9
9.3
1
1
5.9
5
1.25
3.9
5
0.8
1
5.9
1.6
1.3
1
1.1
1.25
1.4
1.2
5
1.4
1.7
1.8
1.6
1.5
1.7
13.9
5.9
2.1
1.1
6.7
2.7
6.7
3.95
7.75
10.6
1.6
2.5
0.7
11.1
5.15
4.7
9.7
1.7
1.4
2
7.5
9.7
0.8
13.1
1.1
2.2
8.9
1.1
0.9
1.7
6.9
1.1
1
1
7.6
8.9
2.2
1.2
1
1
3.1
1.95
2.2
8.75
11.9
2.7
5.45
6.3
14.4
7.8
1.6
9.1
9.1
14.4
1.3
1.6
11.3
6.3
0.7
1.25
0.7
7.8
10.3
10.3
7.8
8.7
8.3
10.3
7.8
1.2
8.3
8.3
6.2
5
1.8
1.6
1.8
1.8
2.9
6
0.9
1.1
1.6
5.45
14.05
8
13.1
4.9
1.3
2.2
14.9
14.9
0.95
1.4
0.95
1.7
5.6
14.9
7.1
1.2
9.6
11.4
11.4
7.9
5
11.1
8
3.8
10.55
10.2
10.2
9.8
6.3
1.1
4.5
6.3
10.9
9.8
9.8
0.8
0.8
1.2
1.3
9.8
10.2
10.9
6.3
6.3
1.2
0.9
1.1
4.5
3.7
18.1
1.35
5.5
3.1
12.85
19.8
8.25
12.85
3.8
6.9
8.25
11.7
4.6
4
19.8
12.85
1.2
8.9
11.7
6.2
14.8
14.8
10.8
1.6
8.3
8.4
2.5
3.5
17.2
2.1
12.2
11.8
16.8
17.2
1.1
14.7
5.5
6.1
1.2
1.3
8.7
1.7
8.7
10.2
4.5
5.9
1.7
1.4
5.4
7.9
1.1
7
7
7.6
7
12.3
15.3
12.3
1.2
2.3
6.1
7.6
10.2
4.1
2.9
8.5
1.5
3.1
7.9
3.5
4.9
1.1
7
1.2
4.5
2.6
9.9
4.5
9.5
1.5
3.2
2.6
11.2
3.2
2.3
4.9
4.9
1.4
1.5
6.7
2.1
4.3
10.9
7
2.3
2.5
2.6
3.2
2.5
14.7
4.5
2.2
1.9
1.6
17.3
4.2
4.2
2.5
1.9
1.4
0.8
8
1.6
1.7
5.5
17.3
8.6
6.9
2.1
2.2
1.5
2.5
17.6
4.2
2.9
4.8
11.9
0.9
1.3
6.4
4.3
11.9
8.1
1.3
0.9
17.2
17.2
17.2
8.7
17.2
8.7
7.5
17.2
4.6
3.7
2.2
7.4
15.1
7.4
4.8
7.9
1
15.1
7.4
4.8
4.6
1.4
6.2
6.1
5.1
6.3
0.9
2.3
6.6
7.5
8.6
11.9
2.3
7.1
4.3
1.1
1
7.9
1
1
1
7.3
1.7
1.3
6.4
1.8
1.5
3.8
7.9
1
1.2
5.3
9.1
6.5
9.1
6.3
5.1
6.5
2.4
9.1
7.5
5
6.75
1.2
1.6
16.05
5
12.4
0.95
4.6
1.7
1
1.3
5
2.5
2.6
2.1
12.75
1.1
12.4
3.7
2.65
2.5
8.2
7.3
1.1
6.6
7
14.5
11.8
3
3.7
6
4.6
2.5
3.3
1
1.1
1.4
3.3
8.55
2.5
6.7
3.8
4.5
4.6
4.2
11.3
5.5
4.2
2.2
14.5
14.5
14.5
14.5
14.5
14.5
1.5
18.75
3.6
1.4
5.1
10.5
2
2.6
9.2
1.8
5.7
2.4
1.9
1.4
0.9
4.6
1.4
9.2
1.4
1.8
2.3
2.3
4.4
6.4
2.9
2.8
2.9
4.4
8.2
1
2.9
7
1.8
1.5
7
8.2
7.6
2.3
8.7
1
2.9
6.7
5
1.9
2
1.9
8.5
12.6
5.2
2.1
1.1
1.3
1.1
9.2
1.2
1.1
8.3
1.8
1.4
15.7
4.35
1.8
1.6
2
5
1.8
1.3
1
1.4
8.1
8.6
3.7
5.7
2.35
13.65
13.65
13.65
15.2
4.6
1.2
4.6
6.65
13.55
13.65
9.8
10.3
6.7
15.2
9.9
7.2
1.1
8.3
11.25
12.8
9.65
12.6
12.2
8.3
11.25
1.3
9.9
7.2
1.1
1.1
4.8
1.1
1.4
1.7
10.6
1.4
1.1
5.55
2.1
1.7
9
1.7
1.8
4.7
11.3
3.6
6.9
3.6
4.9
6.95
1.9
4.7
11.3
1.8
11.3
8.2
8.3
9.55
8.4
7.8
7.8
10.2
5.5
7.8
7.4
3.3
5
3.3
5
1.3
1.2
7.4
7.8
9.9
0.7
4.6
5.6
9.5
14.8
4.6
2.1
11.6
1.2
11.6
2.1
20.15
4.7
4.3
14.5
4.9
14.55
14.55
10.05
4.9
14.5
14.55
15.25
3.15
1.3
5.2
1.1
7.1
8.8
18.5
8.8
1.4
1.2
5
1.6
18.75
6
9.4
9.7
4.75
6
5.35
5.35
6.8
6.9
1.4
0.9
1.2
1.3
2.6
12
9.85
3.85
2
1.6
7.8
1.9
2
10.3
1.1
12
3.85
9.85
2
4
1.1
10.4
6.1
1.8
10.4
4.7
4
1.1
6.4
8.15
6.1
4.8
1.2
1.1
1.4
7.4
1.8
1
15.5
15.5
8.4
2.4
3.95
19.95
2
3
15.5
8.4
14.3
4.2
1.4
3
4.9
2.4
14.3
10.7
11
1.4
1.2
12.9
10.8
1.3
2
1.8
1.2
7.5
9.7
3.8
7.2
9.7
6.3
6.3
0.8
8.6
6.3
3.1
7.2
7.1
6.4
14.7
7.2
7.1
1.9
1.2
4.8
1.2
3.4
4.3
8.5
1.8
1.8
19.5
8.5
19.9
8.3
1.8
1.1
16.65
16.65
16.65
0.9
6.1
10.2
0.9
16.65
3.85
4.4
4.5
3.2
4.5
4.4
9.7
4.2
4.2
1.1
9.7
4.2
5.6
4.2
1.6
1.6
1.1
14.6
2.6
1.2
7.25
6.55
7
1.5
1.4
7.25
1
4.2
17.5
17.5
17.5
1.5
1.3
3.9
4.2
7.6
1
1.1
11.8
1.4
9.7
12.9
1.6
7.2
7.1
1.9
8.8
7.2
1.4
14.3
14.3
8.8
1.4
1.8
14.3
7.2
1.2
11.8
0.9
12.6
26.05
4.7
12.6
1.2
26.05
6.1
11.8
0.9
5.6
5.3
5.7
8
8
17.6
8
8.8
1.5
1.4
4.8
2.4
3.7
4.9
5.7
5.7
4.9
2
5.1
4.5
3.2
6.65
1.6
4
17.75
1.4
17.75
7.2
5.7
8.5
11.4
5.4
2.7
4.3
1.2
1.8
1.3
5.7
2.7
11.7
4.3
11
1.6
11.6
6.2
1.8
1.2
1
2.4
1.2
8.2
18.8
9.6
12.9
9.2
1.2
12.9
8
12.9
1.6
12
2.5
9.2
4.4
8.8
9.6
8
18.8
1.3
1.2
12.9
1.2
1.6
1.5
18.15
13.1
13.1
13.1
13.1
1
1.6
11.8
1.4
1
13.1
10.6
10.4
1.1
7.4
1.2
3.4
18.15
8
2.5
2
2
6.9
1.2
9.4
2.9
6.9
5.4
1.3
20.8
10.3
1.3
1.6
13.1
1.8
8
1.6
1.4
14.7
14.7
14.7
14.7
14.7
14.7
14.7
1.8
10.6
12.5
6.8
14.7
2.9
1.4
1.4
2.1
7.4
2.9
1.4
1.4
7.4
5
2.5
6.1
2.7
2.1
12.9
12.9
12.9
13.7
12.9
2.4
9.8
13.7
1.3
12.1
6.1
7.7
6.1
1.4
7.7
12.1
6.8
9.2
8.3
17.4
2.7
12.8
8.2
8.1
8.2
8.3
8
11.8
12
1.7
17.4
13.9
10.7
2
2.2
1.3
1.1
2
6.4
1.3
1.1
10.7
6.4
6.3
6.4
15.1
2
2
2.2
12.1
8.8
8.8
5.1
6.8
6.8
3.7
12.2
5.7
8.1
2.5
4
6.8
1
5.1
5.8
10.6
3.5
3.5
16.4
4.8
3.3
1.2
1.2
4.8
3.3
2.5
8.7
1.6
4
2.5
16.2
9
16.2
1.4
7
9
3.1
1.5
4.6
4.8
4.6
1.5
2.7
6.3
7.2
7.2
12.4
6.6
6.6
4
4.8
1.3
7.2
11.1
12.4
9.8
6.6
13.3
11.7
8
1.6
16.55
1.5
10.2
6.6
17.8
17.8
1.5
7.4
17.8
2
7.4
2
17.8
12.1
8.2
1.5
8.7
3.5
6.4
2.1
7.7
12.3
1.3
8.7
3.5
1.1
2.8
3.5
1.9
3.8
3.8
2.4
4.8
4.8
6.2
1.3
3.8
1.5
4.8
1.9
6.2
7.9
1.6
1.4
2.6
14.8
2.4
0.9
0.9
1.2
9.9
3.9
15.6
15.6
1.5
1.6
7.8
5.6
1.3
16.7
7.95
6.7
1.1
6.3
8.9
1
1.5
6.6
6.2
6.3
2.1
2.2
5.4
8.9
1
17.9
2.6
1.3
17.9
2.6
2.3
4.3
7.1
7.1
11.9
11.7
5.8
3.8
12.4
6.5
7.1
7.6
7.9
2.8
10.6
2.8
1.5
7.6
7.9
1.7
7.6
7.5
1.7
1.7
12.1
4.5
1.7
8
7.6
8.6
8.6
14.6
1.6
8.6
14.6
1.1
3.7
8.9
8.9
4.7
8.9
3.1
5.8
5.8
5.8
1
15.8
1.5
5.2
1.5
2.5
1
15.8
5.9
3.1
3.1
5.8
11.5
18
4.8
8.5
1.6
18
4.8
5.9
1.1
8.5
13.1
4.1
2.9
13.1
1.1
1.5
7.75
1.15
1
17.8
5.7
17.8
7.4
1.4
1.4
1
4.4
1.6
7.9
15.5
15.5
15.5
15.5
17.55
13.5
13.5
1.3
15.5
11.6
7.9
15.5
17.55
11.6
13.15
1.9
13.5
1.3
6.1
6.1
1.9
1.9
1.6
11.3
8.4
8.3
8.4
12.2
8
1.3
12.7
1.3
10.5
12.5
9.6
1.5
1.5
7.8
10.8
12.5
8.6
1.2
14.5
3.7
1.1
1.1
3.8
4.6
10.2
7.9
2.4
10.7
4.9
10.7
1.1
7.9
5.6
2.4
14.2
9.5
9.5
4.1
4.7
1.4
0.9
20.3
3.5
2.7
1.2
1.2
2
1.1
1.5
1.2
18.1
18.1
3.6
3.5
12.1
17.45
12.1
3
1.6
5.7
5.6
6.8
15.6
6
1.8
8.6
8.6
11.5
7.8
2.4
5
8.6
1.5
5.4
11.9
11.9
9
10
11.9
11.9
15.5
5.4
15
1.4
9.4
3.7
15
1.4
6.5
1.4
6.3
13.7
13.7
13.7
13.7
13.7
13.7
1.5
1.6
1.4
3.5
1
1.4
1.5
13.7
1.6
5.2
1.4
11.9
2.4
3.2
1.7
4.2
15.4
13
5.6
9.7
2.5
4
15.4
1.2
2
1.2
5.1
1.4
1.2
6.5
1.3
6.5
2.7
1.3
7.4
12.9
1.3
1.2
2.6
2.3
1.3
10.5
2.6
14.4
1.2
3.1
1.7
6
11.8
6.2
1.4
12.1
12.1
12.1
3.9
4.6
12.1
1.2
8.1
3.9
1.1
6.5
10.1
10.7
3.2
12.4
5.2
5
2.5
9.2
6.9
2
15
15
1.2
15
1.8
10.8
3.9
4.2
2
13.5
13.3
2.2
1.4
1.6
2.2
14.8
1.8
14.8
1.3
9.9
5.1
5.1
1.5
1.5
11.1
5.25
2.3
7.9
8
1.4
5.25
2.3
2.3
3.5
13.7
9.9
15.4
16
16
16
16
2.4
5.5
2.3
16.8
16
17.8
17.8
6.8
6.8
6.8
6.8
1.6
4.7
11.8
17.8
15.7
5.8
15.7
9
15.7
5.8
8.8
10.2
6.6
6.5
8.9
11.1
4.2
1.6
7.4
11.5
1.6
2
4.8
9.8
1.9
4.2
1.6
7.3
5.4
10.4
1.9
7.3
5.4
7.7
11.5
1.2
2.2
1
8.2
8.3
8.2
9.3
8.1
8.2
8.3
13.9
13.9
13.9
13.9
13.9
13.9
13.9
2
13.9
15.7
1.2
1.5
1.2
3.2
1.2
2.6
13.2
10.4
5.7
2.5
1.6
1.4
7.4
2.5
5.6
3.6
7.5
5.8
1.6
1.5
2.9
11.2
9.65
10.1
3.2
11.2
11.45
9.65
4.5
2.7
3.5
1.7
2.1
4.8
5
2.6
6.6
5
7.3
5
1.7
2.6
8.2
8.2
5
1.2
7.1
9.5
15.8
15.5
15.8
17.05
12.7
12.3
11.8
11.8
11.8
12.3
11.8
13.6
5.2
6.2
7.9
7.9
3.3
2.8
7.9
3.3
6.3
4.9
10.4
4.9
10.4
16
6.3
2.2
17.3
17.3
17.3
17.3
2.2
2.2
17.3
6.6
6.5
12.3
5
2.8
13.6
2.8
5.4
10.9
1.7
9.15
4.5
9.15
1.4
5.9
16.4
1.2
16.4
5.9
7.8
7.8
2.8
2.9
2.5
12.8
12.2
7.7
2.8
2.9
17.3
19.3
19.3
19.3
2.7
6.4
17.3
2.4
2.8
1.7
15.4
15.4
4.1
6.6
1.2
2.1
1
1.1
1.4
1.6
9.8
1.9
1.3
7.9
7.9
4.5
22.6
7.9
3.5
1.2
4.5
2
7.8
0.9
2.9
2.9
3.5
4.2
9.7
10.5
1.1
16.1
1.1
8.1
6.2
7.7
2.4
16.3
2.3
8.4
8.5
6
1.1
1.75
2.6
1.3
2.1
1.1
1.1
2.8
9
2.8
2.2
5.1
3.5
12.7
7.5
2
3.5
14.3
9.8
12.7
12.7
5.1
3.5
12.7
12.9
12.9
1.3
10.5
1.5
12.7
12.9
1.2
6.2
8.8
3.9
1.3
9.1
9.1
3.9
1.8
2.1
1.4
14.7
9.1
1.9
1.8
9.6
3.9
1.3
11.8
1.9
12
7.9
9.3
4.6
2.2
10.2
10.6
1.4
9.1
11.1
9.1
4.4
2.8
1.1
1.3
1.2
3.3
9.7
2.3
1.1
11.4
1.2
14.7
13.8
1.3
6.3
7.9
2
11.8
1.2
10
5.2
1.2
7.2
9.9
5.3
13.55
2.2
9.9
4.3
13
13.55
1
1.1
6.9
13.4
4.6
9.9
3
5.8
12.9
3.2
0.8
2.5
2.4
7.2
7.3
6.3
4.25
1.2
2
4.25
4.7
4.5
1.4
4.1
5.3
4.2
6.65
8.2
2.6
2.6
2
12.2
2.3
8.2
5
10.7
10.8
1.7
1.3
1.7
12.7
1.3
1.2
1.3
5.7
3.4
1.1
1
1
1.65
6.8
6.8
4.9
1.4
2.5
10.8
10.8
10.8
10.8
2.8
1.3
2
1.1
8.2
6
6.1
8.2
8.8
6.1
6
1.2
11.4
1.3
1.3
6.2
3.2
4.5
9.9
6.2
11.4
1.3
1.3
0.9
0.7
1
1
10.4
1.3
12.5
12.5
12.5
12.5
19.25
1.1
12.5
19.25
9
1.2
9
1.3
12.8
12.8
7.6
7.6
1.4
8.3
9
1.85
12.55
1.4
1.8
4
12.55
9
3
1.85
7.9
2.6
1.2
7.1
7.9
1.3
10.7
7.7
8.4
10.7
12.7
1.8
7.7
10.5
1.6
1.85
10.5
10.5
1
1.2
1.7
1.6
9
1.9
1.2
1.5
3.9
3.6
1.2
5
2.9
10.4
11.4
18.35
18.4
1.2
7.1
1.3
1.5
10.2
2.2
3.5
3.5
3.9
7.4
7.4
11
1.5
3.9
5.4
1.5
5
1.2
13
13
13
13
8.6
1.7
1.2
1.2
1.2
2
19.4
0.8
6.3
6.4
12.1
12.1
12.9
2.4
4.3
4.2
12.9
1.7
2.2
12.1
3.4
7.4
7.3
1.1
1.1
1.4
14.5
8
1.1
1.1
2.2
5.8
0.9
6.4
10.9
7.3
8.3
1.3
3.3
1
1.1
1
5.1
3.2
12.6
3.7
1.7
5.1
1
1.3
1.5
4.6
10.3
6.1
6.1
1.2
10.3
9.9
1.6
1.1
1.5
1.2
1.5
1.1
11.5
7.8
7.4
1.45
8.9
1.1
1
2.5
1.1
2.4
2.3
5.1
2.5
8.9
2.5
8.9
1.6
1.4
3.9
13.7
13.7
9.2
7.8
7.6
7.7
3
1.3
4
1.1
2
1.9
1.4
4.5
10.1
6.6
1.9
12.4
1.6
2.5
1.2
2.5
0.8
0.9
8.1
8.1
11.75
1.3
1.9
8.3
8.1
5.7
1.9
1.2
11.75
2.2
0.9
1.3
1.6
8
1.2
1.1
0.8

[wesm]

cool, can you give me the qcut function calls and arguments that fail?

[sunfaquir]

For case(3), using the above data as a column tmpcol
pd.qcut(tmpcol, 20), I got the bin's levels as

array([[0.6, 0.991], (0.991, 0.992], (0.992, 0.993], (0.993, 0.993],
(0.993, 0.994], (0.994, 0.995], (0.995, 0.996], (0.996, 0.997],
(0.997, 0.998], (0.998, 0.1], (0.1, 1.2], (1.2, 1.5], (1.5, 2.1],
(2.1, 3.5], (3.5, 5.2], (5.2, 7.1], (7.1, 8.5], (8.5, 11],
(11, 13.7], (13.7, 65.8]], dtype=object)

Note (0.993, 0.993], and (0.998, 0.1], seems two kind of different errors

case (2) can be replicated by executing qcut on any column containing 2 distinct values
Ran into case(1) a couple of weeks and I can hardly remember which data I was using.