rapidsai / cudf

cuDF - GPU DataFrame Library
https://docs.rapids.ai/api/cudf/stable/
Apache License 2.0
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[BUG] Series.mean with skipna = False result is hard to interpret #7520

Closed bryevdv closed 3 years ago

bryevdv commented 3 years ago

Describe the bug

Series.mean with skipna=False gives a result that is hard to understand

Steps/Code to reproduce bug

In [2]: s = cudf.Series([None, 0, 1, 1, None, 2, 3, 3, 4, 4])
In [3]: s.mean(False)
Out[3]: 2.25

Expected behavior

With skipna=False I would expect either of two things:

But appears that in this case:

Alternatively, another way to look at this is to note that in the presence of nulls, mean gives the same result regardless of the value of skipna

In [5]: s.mean(skipna=True)
Out[5]: 2.25

which seems incorrect.

Is this intended/expected behavior? Is it documented somewhere? I looked but could not find anything to describe what skipna=False does in precise, exact terms.

Environment overview (please complete the following information)

Environment details

Click here to see environment details

     **git***
     commit 3c15d3028ac5083e4d025f5c70657e9a1dd3247b (HEAD -> branch-0.18)
     Author: Robert (Bobby) Evans 
     Date:   Fri Dec 11 11:07:25 2020 -0600

     Fix java cufile tests when cufile is not installed(#6987)

     Just disables the tests when cufile is not installed.

     Authors:
     - Robert (Bobby) Evans 

     Approvers:
     - Kuhu Shukla

     URL: https://github.com/rapidsai/cudf/pull/6987
     **git submodules***

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     Fri Mar  5 09:40:08 2021
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     |                               |                      |               MIG M. |
     |===============================+======================+======================|
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     | 33%   32C    P8    32W / 260W |   3314MiB / 48601MiB |      0%      Default |
     |                               |                      |                  N/A |
     +-------------------------------+----------------------+----------------------+
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     | 33%   41C    P8    29W / 260W |    639MiB / 48578MiB |     26%      Default |
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     +-------------------------------+----------------------+----------------------+

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     | Processes:                                                                  |
     |  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
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     |    1   N/A  N/A      1510      G   xfwm4                               4MiB |
     +-----------------------------------------------------------------------------+

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     CPU op-mode(s):                  32-bit, 64-bit
     Byte Order:                      Little Endian
     Address sizes:                   46 bits physical, 48 bits virtual
     CPU(s):                          12
     On-line CPU(s) list:             0-11
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     Core(s) per socket:              6
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     Model:                           85
     Model name:                      Intel(R) Xeon(R) Gold 6128 CPU @ 3.40GHz
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     L2 cache:                        6 MiB
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     Vulnerability L1tf:              Mitigation; PTE Inversion
     Vulnerability Mds:               Mitigation; Clear CPU buffers; SMT vulnerable
     Vulnerability Meltdown:          Mitigation; PTI
     Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp
     Vulnerability Spectre v1:        Mitigation; usercopy/swapgs barriers and __user pointer sanitization
     Vulnerability Spectre v2:        Mitigation; Full generic retpoline, IBPB conditional, IBRS_FW, STIBP conditional, RSB filling
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     Vulnerability Tsx async abort:   Mitigation; Clear CPU buffers; SMT vulnerable
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     nvcc: NVIDIA (R) Cuda compiler driver
     Copyright (c) 2005-2021 NVIDIA Corporation
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     python_abi                3.8                      1_cp38    conda-forge
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bryevdv commented 3 years ago

OK this was a usage error, cudf matches pandas

In [6]: s.mean(skipna=False)
Out[6]: nan

(is there any thought to making options like this be kwarg-only?)