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rapidsai / cudf

cuDF - GPU DataFrame Library
https://docs.rapids.ai/api/cudf/stable/
Apache License 2.0
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[BUG] `cudf.read_csv` should not cast to floating types if there are null entries in csv #6313

Open galipremsagar opened 3 years ago

galipremsagar commented 3 years ago

Describe the bug We seem to be reading in an integer column with nulls as a floating column. This is similar to pandas behavior but since we have support for nullable dtypes in all dtypes, should we even type-cast to float?

Steps/Code to reproduce bug

In[20]: df = cudf.DataFrame({'a':cudf.Series([1, 2, 3], dtype='uint64')})
In[21]: df.to_csv('temp.csv')
In[22]: cudf.read_csv('temp.csv')
Out[22]: 
   Unnamed: 0  a
0           0  1
1           1  2
2           2  3
In[23]: pd.read_csv('temp.csv')
Out[23]: 
   Unnamed: 0  a
0           0  1
1           1  2
2           2  3
In[24]: df = cudf.DataFrame({'a':cudf.Series([1, 2, 3, None], dtype='uint64')})
In[25]: df.to_csv('temp.csv')
In[26]: cudf.read_csv('temp.csv')
Out[26]: 
   Unnamed: 0     a
0           0   1.0
1           1   2.0
2           2   3.0
3           3  <NA>
In[27]: pd.read_csv('temp.csv')
Out[27]: 
   Unnamed: 0    a
0           0  1.0
1           1  2.0
2           2  3.0
3           3  NaN

Expected behavior Expected behavior is to not type-cast to float and only cast to the inferred dtype.

Environment overview (please complete the following information)

Environment details Please run and paste the output of the cudf/print_env.sh script here, to gather any other relevant environment details

Click here to see environment details

     **git***
     commit 768b67c37c2e3539f3d80d3c881ff8b1b320e56b (HEAD -> branch-0.16, upstream/branch-0.16)
     Author: GALI PREM SAGAR 
     Date:   Thu Sep 24 09:18:00 2020 -0500

     Implement Fuzz tests for cuIO (#6114)

     * add log reporting for failed tests

     * add random data generation apis for all dtypes

     * make size as mandatory param

     * add random dataframe generation api

     * add Fuzz tests for parquet reader

     * add support for datetime, timedelta and category dtypes datageneration

     * add parquet writer tests

     * add csv writer and reader tests

     * add all dtypes support for random dataframe generation

     * add logging for exception

     * add all dtypes in CSV and parquet testing

     * cleanup

     * code cleanup

     * typo

     * add support for regression run from crash files

     * add json reader writer tests

     * fix issue related to picking random dtypes

     * replace prints with logging

     * exclude timedelta dtypes in CSV reader / writer tests

     * use seed in generate_input apis

     * add max_columns param

     * change param file extension to json from xml

     * add columns param

     * fix issues with regression run

     * add Readme for fuzz tests

     * add call method to fuzzer

     * add readme for fuzz tests

     * change main block code

     * add url

     * fix issue with float dtype data generation

     * add tips in readme

     * Update CHANGELOG.md

     * apply seeds

     * change the format of the dtypes_meta for rand_dataframe

     * re-organize tests into their respective files

     * move common code

     * use 3x faster np.radom apis instead of mimesis

     * make optimizations in _generate_column and fix lambda scope issues

     * remove redundant numpy computation

     * moved common code into utils.py

     * make max string length generation random

     * add todo for list dtype support

     * add copyright and use string buffer

     * change print to an error

     * handle keyboard interrupts and exit

     * replace writing to parquet directly from pyarrow

     * remove skipping of timedelta types in csv

     * give limits to datetime and duration types

     * parametrize max_string_length

     * move common code into a base class implementation

     * push down common logic into IOBase

     * use common logic from IOBase

     * remove unused variables

     * change default max_rows to 100000

     * add utility function to translate to pandas nullable dtypes

     * rename IOBase to IOFuzz

     * copyright

     * change default max_rows_size to 100000

     * change from saving to file to return buffer

     * Update python/cudf/cudf/fuzz_tests/readme.md

     Co-authored-by: Christopher Harris 

     * add comparison of file contents

     * handle deafult param for dirs

     * remove redundant test code

     * change default value for max rows:

     Co-authored-by: Christopher Harris 
     **git submodules***

     ***OS Information***
     DISTRIB_ID=Ubuntu
     DISTRIB_RELEASE=20.04
     DISTRIB_CODENAME=focal
     DISTRIB_DESCRIPTION="Ubuntu 20.04.1 LTS"
     NAME="Ubuntu"
     VERSION="20.04.1 LTS (Focal Fossa)"
     ID=ubuntu
     ID_LIKE=debian
     PRETTY_NAME="Ubuntu 20.04.1 LTS"
     VERSION_ID="20.04"
     HOME_URL="https://www.ubuntu.com/"
     SUPPORT_URL="https://help.ubuntu.com/"
     BUG_REPORT_URL="https://bugs.launchpad.net/ubuntu/"
     PRIVACY_POLICY_URL="https://www.ubuntu.com/legal/terms-and-policies/privacy-policy"
     VERSION_CODENAME=focal
     UBUNTU_CODENAME=focal
     Linux pgali-HP-Z8-G4-Workstation 5.4.0-48-generic #52-Ubuntu SMP Thu Sep 10 10:58:49 UTC 2020 x86_64 x86_64 x86_64 GNU/Linux

     ***GPU Information***
     Thu Sep 24 15:26:03 2020
     +-----------------------------------------------------------------------------+
     | NVIDIA-SMI 450.66       Driver Version: 450.66       CUDA Version: 11.0     |
     |-------------------------------+----------------------+----------------------+
     | GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
     | Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
     |                               |                      |               MIG M. |
     |===============================+======================+======================|
     |   0  Quadro RTX 8000     Off  | 00000000:22:00.0 Off |                  Off |
     | 33%   30C    P8     4W / 260W |    874MiB / 48601MiB |      0%      Default |
     |                               |                      |                  N/A |
     +-------------------------------+----------------------+----------------------+
     |   1  Quadro RTX 8000     Off  | 00000000:2D:00.0  On |                  Off |
     | 33%   35C    P8    20W / 260W |    588MiB / 48592MiB |     18%      Default |
     |                               |                      |                  N/A |
     +-------------------------------+----------------------+----------------------+

     +-----------------------------------------------------------------------------+
     | Processes:                                                                  |
     |  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
     |        ID   ID                                                   Usage      |
     |=============================================================================|
     |    0   N/A  N/A       960      G   /usr/lib/xorg/Xorg                  4MiB |
     |    0   N/A  N/A      1820      G   /usr/lib/xorg/Xorg                  4MiB |
     |    0   N/A  N/A      5056      C   .../envs/cudf_dev/bin/python      695MiB |
     |    0   N/A  N/A      6256      C   ...ffice/program/soffice.bin      165MiB |
     |    1   N/A  N/A       960      G   /usr/lib/xorg/Xorg                 39MiB |
     |    1   N/A  N/A      1820      G   /usr/lib/xorg/Xorg                287MiB |
     |    1   N/A  N/A      2020      G   /usr/bin/gnome-shell              200MiB |
     |    1   N/A  N/A      5616      G   /usr/lib/firefox/firefox            3MiB |
     |    1   N/A  N/A      5788      G   ...AAAAAAAAA= --shared-files       44MiB |
     +-----------------------------------------------------------------------------+

     ***CPU***
     Architecture:                    x86_64
     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
     Thread(s) per core:              2
     Core(s) per socket:              6
     Socket(s):                       1
     NUMA node(s):                    1
     Vendor ID:                       GenuineIntel
     CPU family:                      6
     Model:                           85
     Model name:                      Intel(R) Xeon(R) Gold 6128 CPU @ 3.40GHz
     Stepping:                        4
     CPU MHz:                         1200.141
     CPU max MHz:                     3700.0000
     CPU min MHz:                     1200.0000
     BogoMIPS:                        6800.00
     Virtualization:                  VT-x
     L1d cache:                       192 KiB
     L1i cache:                       192 KiB
     L2 cache:                        6 MiB
     L3 cache:                        19.3 MiB
     NUMA node0 CPU(s):               0-11
     Vulnerability Itlb multihit:     KVM: Vulnerable
     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
     Vulnerability Srbds:             Not affected
     Vulnerability Tsx async abort:   Mitigation; Clear CPU buffers; SMT vulnerable
     Flags:                           fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cdp_l3 invpcid_single pti intel_ppin ssbd mba ibrs ibpb stibp tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm cqm mpx rdt_a avx512f avx512dq rdseed adx smap clflushopt clwb intel_pt avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req pku ospke md_clear flush_l1d

     ***CMake***
     /home/pgali/anaconda3/envs/cudf_dev/bin/cmake
     cmake version 3.18.2

     CMake suite maintained and supported by Kitware (kitware.com/cmake).

     ***g++***
     /usr/bin/g++
     g++ (Ubuntu 9.3.0-10ubuntu2) 9.3.0
     Copyright (C) 2019 Free Software Foundation, Inc.
     This is free software; see the source for copying conditions.  There is NO
     warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

     ***nvcc***
     /usr/local/cuda/bin/nvcc
     nvcc: NVIDIA (R) Cuda compiler driver
     Copyright (c) 2005-2020 NVIDIA Corporation
     Built on Wed_Jul_22_19:09:09_PDT_2020
     Cuda compilation tools, release 11.0, V11.0.221
     Build cuda_11.0_bu.TC445_37.28845127_0

     ***Python***
     /home/pgali/anaconda3/envs/cudf_dev/bin/python
     Python 3.7.8

     ***Environment Variables***
     PATH                            : /home/pgali/anaconda3/envs/cudf_dev/bin:/home/pgali/anaconda3/condabin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin:/usr/local/cuda/bin
     LD_LIBRARY_PATH                 : :/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64
     NUMBAPRO_NVVM                   :
     NUMBAPRO_LIBDEVICE              :
     CONDA_PREFIX                    : /home/pgali/anaconda3/envs/cudf_dev
     PYTHON_PATH                     :

     ***conda packages***
     /home/pgali/anaconda3/condabin/conda
     # packages in environment at /home/pgali/anaconda3/envs/cudf_dev:
     #
     # Name                    Version                   Build  Channel
     _libgcc_mutex             0.1                 conda_forge    conda-forge
     _openmp_mutex             4.5                       1_gnu    conda-forge
     abseil-cpp                20200225.2           he1b5a44_2    conda-forge
     alabaster                 0.7.12                     py_0    conda-forge
     appdirs                   1.4.3                      py_1    conda-forge
     argon2-cffi               20.1.0           py37h8f50634_1    conda-forge
     arrow-cpp                 1.0.1           py37hf00d4d6_5_cuda    conda-forge
     arrow-cpp-proc            1.0.1                      cuda    conda-forge
     async_generator           1.10                       py_0    conda-forge
     attrs                     20.2.0             pyh9f0ad1d_0    conda-forge
     aws-c-common              0.4.57               he1b5a44_0    conda-forge
     aws-c-event-stream        0.1.6                h72b8ae1_3    conda-forge
     aws-checksums             0.1.9                h346380f_0    conda-forge
     aws-sdk-cpp               1.7.164              h69f4914_4    conda-forge
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     backports                 1.0                        py_2    conda-forge
     backports.functools_lru_cache 1.6.1                      py_0    conda-forge
     black                     19.10b0                    py_4    conda-forge
     bleach                    3.2.1              pyh9f0ad1d_0    conda-forge
     bokeh                     2.2.1            py37hc8dfbb8_0    conda-forge
     boost-cpp                 1.74.0               h9359b55_0    conda-forge
     brotli                    1.0.9                he1b5a44_0    conda-forge
     brotlipy                  0.7.0           py37h8f50634_1000    conda-forge
     bzip2                     1.0.8                h516909a_3    conda-forge
     c-ares                    1.16.1               h516909a_3    conda-forge
     ca-certificates           2020.6.20            hecda079_0    conda-forge
     certifi                   2020.6.20        py37hc8dfbb8_0    conda-forge
     cffi                      1.14.3           py37h2b28604_0    conda-forge
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     chardet                   3.0.4           py37hc8dfbb8_1007    conda-forge
     clang                     8.0.1                hc9558a2_2    conda-forge
     clang-tools               8.0.1                hc9558a2_2    conda-forge
     clangxx                   8.0.1                         2    conda-forge
     click                     7.1.2              pyh9f0ad1d_0    conda-forge
     cloudpickle               1.6.0                      py_0    conda-forge
     cmake                     3.18.2               h5c55442_0    conda-forge
     cmake_setuptools          0.1.3                      py_0    rapidsai
     commonmark                0.9.1                      py_0    conda-forge
     cryptography              3.1              py37hb09aad4_0    conda-forge
     csv-diff                  0.6                      pypi_0    pypi
     cudatoolkit               11.0.221             h6bb024c_0    nvidia
     cudf                      0.16.0a0+1960.g848b4266fa          pypi_0    pypi
     cudnn                     8.0.0                cuda11.0_0    nvidia
     cupy                      7.8.0            py37h0ce7dbb_0    rapidsai
     cython                    0.29.21          py37h3340039_0    conda-forge
     cytoolz                   0.10.1           py37h516909a_0    conda-forge
     dask                      2.27.0+5.g5fa77484          pypi_0    pypi
     dask-cudf                 0.16.0a0+1956.g0d50234f35.dirty          pypi_0    pypi
     decorator                 4.4.2                      py_0    conda-forge
     defusedxml                0.6.0                      py_0    conda-forge
     dictdiffer                0.8.1                    pypi_0    pypi
     distlib                   0.3.1              pyh9f0ad1d_0    conda-forge
     distributed               2.27.0+1.g8aefbf36          pypi_0    pypi
     dlpack                    0.3                  he1b5a44_1    conda-forge
     docutils                  0.16             py37hc8dfbb8_1    conda-forge
     double-conversion         3.1.5                he1b5a44_2    conda-forge
     editdistance              0.5.3            py37h3340039_1    conda-forge
     entrypoints               0.3             py37hc8dfbb8_1001    conda-forge
     expat                     2.2.9                he1b5a44_2    conda-forge
     fastavro                  1.0.0.post1      py37h8f50634_0    conda-forge
     fastrlock                 0.5              py37h3340039_0    conda-forge
     filelock                  3.0.12             pyh9f0ad1d_0    conda-forge
     flake8                    3.8.3                      py_1    conda-forge
     flatbuffers               1.12.0               he1b5a44_0    conda-forge
     freetype                  2.10.2               he06d7ca_0    conda-forge
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     future                    0.18.2           py37hc8dfbb8_1    conda-forge
     gflags                    2.2.2             he1b5a44_1004    conda-forge
     glog                      0.4.0                h49b9bf7_3    conda-forge
     gmp                       6.2.0                he1b5a44_2    conda-forge
     grpc-cpp                  1.30.2               heedbac9_0    conda-forge
     heapdict                  1.0.1                      py_0    conda-forge
     hypothesis                5.28.0                     py_0    conda-forge
     icu                       67.1                 he1b5a44_0    conda-forge
     identify                  1.5.4              pyh9f0ad1d_0    conda-forge
     idna                      2.10               pyh9f0ad1d_0    conda-forge
     imagesize                 1.2.0                      py_0    conda-forge
     importlib-metadata        1.7.0            py37hc8dfbb8_0    conda-forge
     importlib_metadata        1.7.0                         0    conda-forge
     iniconfig                 1.0.1              pyh9f0ad1d_0    conda-forge
     ipykernel                 5.3.4            py37h43977f1_0    conda-forge
     ipython                   7.18.1           py37hc6149b9_0    conda-forge
     ipython_genutils          0.2.0                      py_1    conda-forge
     isort                     5.0.7            py37hc8dfbb8_0    conda-forge
     jedi                      0.17.2           py37hc8dfbb8_0    conda-forge
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     jpeg                      9d                   h516909a_0    conda-forge
     jsonschema                3.2.0            py37hc8dfbb8_1    conda-forge
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     krb5                      1.17.1               hfafb76e_3    conda-forge
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     ld_impl_linux-64          2.35                 h769bd43_9    conda-forge
     libblas                   3.8.0               17_openblas    conda-forge
     libcblas                  3.8.0               17_openblas    conda-forge
     libcurl                   7.71.1               hcdd3856_6    conda-forge
     libedit                   3.1.20191231         he28a2e2_2    conda-forge
     libev                     4.33                 h516909a_1    conda-forge
     libevent                  2.1.10               hcdb4288_2    conda-forge
     libffi                    3.2.1             he1b5a44_1007    conda-forge
     libgcc-ng                 9.3.0               h24d8f2e_16    conda-forge
     libgfortran-ng            7.5.0               hdf63c60_16    conda-forge
     libgomp                   9.3.0               h24d8f2e_16    conda-forge
     liblapack                 3.8.0               17_openblas    conda-forge
     libllvm10                 10.0.1               he513fc3_3    conda-forge
     libllvm8                  8.0.1                hc9558a2_0    conda-forge
     libnghttp2                1.41.0               h8cfc5f6_2    conda-forge
     libopenblas               0.3.10          pthreads_hb3c22a3_4    conda-forge
     libpng                    1.6.37               hed695b0_2    conda-forge
     libprotobuf               3.12.4               h8b12597_0    conda-forge
     librmm                    0.16.0a200922   cuda11.0_ge3ce8c5_384    rapidsai-nightly
     libsodium                 1.0.18               h516909a_0    conda-forge
     libssh2                   1.9.0                hab1572f_5    conda-forge
     libstdcxx-ng              9.3.0               hdf63c60_16    conda-forge
     libthrift                 0.13.0               hbe8ec66_6    conda-forge
     libtiff                   4.1.0                hc7e4089_6    conda-forge
     libutf8proc               2.5.0                h516909a_2    conda-forge
     libuv                     1.39.0               h516909a_0    conda-forge
     libwebp-base              1.1.0                h516909a_3    conda-forge
     llvmlite                  0.34.0           py37h5202443_1    conda-forge
     locket                    0.2.0                      py_2    conda-forge
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     openssl                   1.1.1h               h516909a_0    conda-forge
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     parquet-cpp               1.5.1                         2    conda-forge
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     pre_commit                2.7.1                         0    conda-forge
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     py                        1.9.0              pyh9f0ad1d_0    conda-forge
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Additional context Surfaced while running fuzz tests: #6001

karthikeyann commented 3 years ago

This is an issue in pandas as well. Our code is conformant with pandas behavior. https://github.com/rapidsai/cudf/blob/60d25ea04bf018905836310a18133806f780cb22/cpp/src/io/csv/reader_impl.cu#L583-L587

In [18]: pdf = pd.DataFrame({'a':pd.Series([1, 2, 3, None], dtype='Int64')})

In [19]: pdf.dtypes
Out[19]: 
a    Int64
dtype: object

In [20]: pdf.to_csv('temp.csv')

In [21]: cat temp.csv
,a
0,1
1,2
2,3
3,

In [22]: pd.read_csv('temp.csv').dtypes
Out[22]: 
Unnamed: 0      int64
a             float64
dtype: object
galipremsagar commented 3 years ago

I guess the question is with nullable dtypes support introduced in pandas aswell do we still want to mimic pandas behavior?

kkraus14 commented 3 years ago

I guess the question is with nullable dtypes support introduced in pandas aswell do we still want to mimic pandas behavior?

Agreed. This sounds like a bug in Pandas at this point and we shouldn't replicate the behavior. @galipremsagar can you open an issue on Pandas for this?

galipremsagar commented 3 years ago

Agreed. This sounds like a bug in Pandas at this point and we shouldn't replicate the behavior. @galipremsagar can you open an issue on Pandas for this?

Linking for reference: https://github.com/pandas-dev/pandas/issues/36712

vuule commented 3 years ago

From the Pandas issue: Pandas will not change this behavior until they start using nullable types by default. We can still go ahead with the change.

github-actions[bot] commented 3 years ago

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vuule commented 1 year ago

Looks like we didn't go ahead with the change :D FWIW, Pandas still does not default to nullable types, and there's a PR to add an option to use nullable types in read_csv https://github.com/pandas-dev/pandas/pull/48776.