SuccessConsole Output

[EnvInject] - Mask passwords passed as build parameters.
GitHub pull request #459 of commit 91afb247fdd4960d8be6c4d0f4a33c394b7a90d6 automatically merged.
[EnvInject] - Loading node environment variables.
Building remotely on research-jenkins-worker-08 (ubuntu research-08) in workspace /home/jenkins/workspace/Modin-PRB
[WS-CLEANUP] Deleting project workspace...
[WS-CLEANUP] Done
Cloning the remote Git repository
Cloning repository https://github.com/modin-project/modin
 > git init /home/jenkins/workspace/Modin-PRB # timeout=10
Fetching upstream changes from https://github.com/modin-project/modin
 > git --version # timeout=10
 > git fetch --tags --progress https://github.com/modin-project/modin +refs/heads/*:refs/remotes/origin/*
 > git config remote.origin.url https://github.com/modin-project/modin # timeout=10
 > git config --add remote.origin.fetch +refs/heads/*:refs/remotes/origin/* # timeout=10
 > git config remote.origin.url https://github.com/modin-project/modin # timeout=10
Fetching upstream changes from https://github.com/modin-project/modin
 > git fetch --tags --progress https://github.com/modin-project/modin +refs/pull/*:refs/remotes/origin/pr/*
 > git rev-parse origin/pr/459/merge^{commit} # timeout=10
 > git branch -a -v --no-abbrev --contains 8ea3c648b0d8e636d3c1cf3b1d8a36293804844d # timeout=10
Checking out Revision 8ea3c648b0d8e636d3c1cf3b1d8a36293804844d (origin/pr/459/merge)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 8ea3c648b0d8e636d3c1cf3b1d8a36293804844d
 > git rev-list 4a6bff1e957494d4b59f1fb3eede99447e9959c1 # timeout=10
First time build. Skipping changelog.
[Modin-PRB] $ /bin/sh -xe /tmp/hudson101628947202838702.sh
+ bash .jenkins/build-tests/run_ci.sh
++ git rev-parse --verify --short HEAD
+ sha_tag=8ea3c64
+ docker build -t modin-project/test:8ea3c64 -f .jenkins/build-tests/Dockerfile .
Sending build context to Docker daemon  9.177MB

Step 1/7 : FROM python:3.6.6-stretch
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Digest: sha256:5b2e0d981c74fa8b53db311e0c5b7672c8c3958053496f42ef29697cec3af277
Status: Downloaded newer image for python:3.6.6-stretch
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Step 2/7 : COPY requirements.txt requirements.txt
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Step 3/7 : RUN pip install -r requirements.txt
 ---> Running in fc54390fe458
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Collecting six (from distributed==1.25.0->-r requirements.txt (line 4))
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Requirement already satisfied: wheel in /usr/local/lib/python3.6/site-packages (from strip_hints==0.1.1->-r requirements.txt (line 7)) (0.32.1)
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Requirement already satisfied: setuptools in /usr/local/lib/python3.6/site-packages (from pytest==3.9.3->-r requirements.txt (line 14)) (40.4.3)
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  Stored in directory: /root/.cache/pip/wheels/f6/0c/4a/9d60d30768e178ac53e0e547ee8bc22d42e3368f2f30fbbdd3
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  Running setup.py bdist_wheel for feather-format: started
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  Stored in directory: /root/.cache/pip/wheels/5a/de/77/f07186146bd0337342dd8c86fa12441f4f9c59573c51dcce9d
  Running setup.py bdist_wheel for sqlalchemy: started
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  Stored in directory: /root/.cache/pip/wheels/b3/94/e4/e556159f8d26575bfa3cf64cff277b9112f1ad8a50cc438bbb
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  Running setup.py bdist_wheel for toolz: finished with status 'done'
  Stored in directory: /root/.cache/pip/wheels/f4/0c/f6/ce6b2d1aa459ee97cc3c0f82236302bd62d89c86c700219463
  Running setup.py bdist_wheel for tornado: started
  Running setup.py bdist_wheel for tornado: finished with status 'done'
  Stored in directory: /root/.cache/pip/wheels/6d/e1/ce/f4ee2fa420cc6b940123c64992b81047816d0a9fad6b879325
  Running setup.py bdist_wheel for pyyaml: started
  Running setup.py bdist_wheel for pyyaml: finished with status 'done'
  Stored in directory: /root/.cache/pip/wheels/ad/da/0c/74eb680767247273e2cf2723482cb9c924fe70af57c334513f
  Running setup.py bdist_wheel for et-xmlfile: started
  Running setup.py bdist_wheel for et-xmlfile: finished with status 'done'
  Stored in directory: /root/.cache/pip/wheels/2a/77/35/0da0965a057698121fc7d8c5a7a9955cdbfb3cc4e2423cad39
  Running setup.py bdist_wheel for locket: started
  Running setup.py bdist_wheel for locket: finished with status 'done'
  Stored in directory: /root/.cache/pip/wheels/26/1e/e8/4fa236ec931b1a0cdd61578e20d4934d7bf188858723b84698
  Running setup.py bdist_wheel for heapdict: started
  Running setup.py bdist_wheel for heapdict: finished with status 'done'
  Stored in directory: /root/.cache/pip/wheels/40/b9/42/344857b482c954f48bcff6db72d388e30bf2bee4ed14706faa
Successfully built psutil strip-hints pathlib feather-format openpyxl sqlalchemy toolz tornado pyyaml et-xmlfile locket heapdict
Installing collected packages: six, python-dateutil, numpy, pytz, pandas, toolz, locket, partd, cloudpickle, click, psutil, tornado, sortedcontainers, pyyaml, tblib, heapdict, zict, msgpack, distributed, dask, colorama, funcsigs, pluggy, attrs, atomicwrites, more-itertools, py, pytest, filelock, redis, flatbuffers, ray, strip-hints, typing, xarray, MarkupSafe, Jinja2, pathlib, numexpr, tables, scipy, coverage, pytest-cov, pytest-forked, apipkg, execnet, pytest-xdist, pyarrow, feather-format, lxml, jdcal, et-xmlfile, openpyxl, xlrd, cycler, pyparsing, kiwisolver, matplotlib, sqlalchemy
Successfully installed Jinja2-2.10 MarkupSafe-1.1.0 apipkg-1.5 atomicwrites-1.3.0 attrs-18.2.0 click-7.0 cloudpickle-0.7.0 colorama-0.4.1 coverage-4.5.2 cycler-0.10.0 dask-1.0.0 distributed-1.25.0 et-xmlfile-1.0.1 execnet-1.5.0 feather-format-0.4.0 filelock-3.0.10 flatbuffers-1.10 funcsigs-1.0.2 heapdict-1.0.0 jdcal-1.4 kiwisolver-1.0.1 locket-0.2.0 lxml-4.3.0 matplotlib-3.0.2 more-itertools-5.0.0 msgpack-0.6.1 numexpr-2.6.9 numpy-1.15.0 openpyxl-2.6.0 pandas-0.23.4 partd-0.3.9 pathlib-1.0.1 pluggy-0.8.1 psutil-5.4.8 py-1.7.0 pyarrow-0.12.0 pyparsing-2.3.1 pytest-3.9.3 pytest-cov-2.6.1 pytest-forked-1.0.1 pytest-xdist-1.26.1 python-dateutil-2.8.0 pytz-2018.9 pyyaml-3.13 ray-0.6.2 redis-3.1.0 scipy-1.2.0 six-1.12.0 sortedcontainers-2.1.0 sqlalchemy-1.2.17 strip-hints-0.1.1 tables-3.4.4 tblib-1.3.2 toolz-0.9.0 tornado-5.1.1 typing-3.6.6 xarray-0.11.3 xlrd-1.2.0 zict-0.1.3
You are using pip version 18.1, however version 19.0.1 is available.
You should consider upgrading via the 'pip install --upgrade pip' command.
Removing intermediate container fc54390fe458
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Step 4/7 : COPY . .
 ---> b72722fbb50a
Step 5/7 : RUN pip install -e .
 ---> Running in 30285917d465
Obtaining file:///
Requirement already satisfied: pandas==0.23.4 in /usr/local/lib/python3.6/site-packages (from modin==0.3.0) (0.23.4)
Requirement already satisfied: ray==0.6.2 in /usr/local/lib/python3.6/site-packages (from modin==0.3.0) (0.6.2)
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Requirement already satisfied: pytz>=2011k in /usr/local/lib/python3.6/site-packages (from pandas==0.23.4->modin==0.3.0) (2018.9)
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Requirement already satisfied: filelock in /usr/local/lib/python3.6/site-packages (from ray==0.6.2->modin==0.3.0) (3.0.10)
Requirement already satisfied: click in /usr/local/lib/python3.6/site-packages (from ray==0.6.2->modin==0.3.0) (7.0)
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Requirement already satisfied: colorama in /usr/local/lib/python3.6/site-packages (from ray==0.6.2->modin==0.3.0) (0.4.1)
Requirement already satisfied: funcsigs in /usr/local/lib/python3.6/site-packages (from ray==0.6.2->modin==0.3.0) (1.0.2)
Requirement already satisfied: pyyaml in /usr/local/lib/python3.6/site-packages (from ray==0.6.2->modin==0.3.0) (3.13)
Requirement already satisfied: flatbuffers in /usr/local/lib/python3.6/site-packages (from ray==0.6.2->modin==0.3.0) (1.10)
Requirement already satisfied: pytest in /usr/local/lib/python3.6/site-packages (from ray==0.6.2->modin==0.3.0) (3.9.3)
Requirement already satisfied: more-itertools>=4.0.0 in /usr/local/lib/python3.6/site-packages (from pytest->ray==0.6.2->modin==0.3.0) (5.0.0)
Requirement already satisfied: atomicwrites>=1.0 in /usr/local/lib/python3.6/site-packages (from pytest->ray==0.6.2->modin==0.3.0) (1.3.0)
Requirement already satisfied: pluggy>=0.7 in /usr/local/lib/python3.6/site-packages (from pytest->ray==0.6.2->modin==0.3.0) (0.8.1)
Requirement already satisfied: py>=1.5.0 in /usr/local/lib/python3.6/site-packages (from pytest->ray==0.6.2->modin==0.3.0) (1.7.0)
Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.6/site-packages (from pytest->ray==0.6.2->modin==0.3.0) (18.2.0)
Requirement already satisfied: setuptools in /usr/local/lib/python3.6/site-packages (from pytest->ray==0.6.2->modin==0.3.0) (40.4.3)
Installing collected packages: modin
  Running setup.py develop for modin
Successfully installed modin
You are using pip version 18.1, however version 19.0.1 is available.
You should consider upgrading via the 'pip install --upgrade pip' command.
Removing intermediate container 30285917d465
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Step 6/7 : RUN pip install awscli pytest-html
 ---> Running in f62203a0ac87
Collecting awscli
  Downloading https://files.pythonhosted.org/packages/cd/29/4f5cee313320f0c284d83c0111bd5b3a26398316d09df3daf883354c9554/awscli-1.16.99-py2.py3-none-any.whl (1.4MB)
Collecting pytest-html
  Downloading https://files.pythonhosted.org/packages/67/95/ca1c8fdf96f3bc8be8cef942478df3c79c2cdf1ba44de1f0e41dc336d4ab/pytest_html-1.20.0-py2.py3-none-any.whl
Requirement already satisfied: PyYAML<=3.13,>=3.10 in /usr/local/lib/python3.6/site-packages (from awscli) (3.13)
Collecting rsa<=3.5.0,>=3.1.2 (from awscli)
  Downloading https://files.pythonhosted.org/packages/e1/ae/baedc9cb175552e95f3395c43055a6a5e125ae4d48a1d7a924baca83e92e/rsa-3.4.2-py2.py3-none-any.whl (46kB)
Collecting colorama<=0.3.9,>=0.2.5 (from awscli)
  Downloading https://files.pythonhosted.org/packages/db/c8/7dcf9dbcb22429512708fe3a547f8b6101c0d02137acbd892505aee57adf/colorama-0.3.9-py2.py3-none-any.whl
Collecting docutils>=0.10 (from awscli)
  Downloading https://files.pythonhosted.org/packages/36/fa/08e9e6e0e3cbd1d362c3bbee8d01d0aedb2155c4ac112b19ef3cae8eed8d/docutils-0.14-py3-none-any.whl (543kB)
Collecting botocore==1.12.89 (from awscli)
  Downloading https://files.pythonhosted.org/packages/c8/6c/2058039815eb4eac4f2f7462ecae3e352e994d6618ba1f27114d9b985618/botocore-1.12.89-py2.py3-none-any.whl (5.2MB)
Collecting s3transfer<0.3.0,>=0.2.0 (from awscli)
  Downloading https://files.pythonhosted.org/packages/d7/de/5737f602e22073ecbded7a0c590707085e154e32b68d86545dcc31004c02/s3transfer-0.2.0-py2.py3-none-any.whl (69kB)
Requirement already satisfied: pytest>=3.0 in /usr/local/lib/python3.6/site-packages (from pytest-html) (3.9.3)
Collecting pytest-metadata (from pytest-html)
  Downloading https://files.pythonhosted.org/packages/ce/8f/d0542e1aa0e23d902ce6acce2790736473da94453a36bdc7829f25734199/pytest_metadata-1.8.0-py2.py3-none-any.whl
Collecting pyasn1>=0.1.3 (from rsa<=3.5.0,>=3.1.2->awscli)
  Downloading https://files.pythonhosted.org/packages/7b/7c/c9386b82a25115cccf1903441bba3cbadcfae7b678a20167347fa8ded34c/pyasn1-0.4.5-py2.py3-none-any.whl (73kB)
Collecting jmespath<1.0.0,>=0.7.1 (from botocore==1.12.89->awscli)
  Downloading https://files.pythonhosted.org/packages/b7/31/05c8d001f7f87f0f07289a5fc0fc3832e9a57f2dbd4d3b0fee70e0d51365/jmespath-0.9.3-py2.py3-none-any.whl
Collecting urllib3<1.25,>=1.20; python_version >= "3.4" (from botocore==1.12.89->awscli)
  Downloading https://files.pythonhosted.org/packages/62/00/ee1d7de624db8ba7090d1226aebefab96a2c71cd5cfa7629d6ad3f61b79e/urllib3-1.24.1-py2.py3-none-any.whl (118kB)
Requirement already satisfied: python-dateutil<3.0.0,>=2.1; python_version >= "2.7" in /usr/local/lib/python3.6/site-packages (from botocore==1.12.89->awscli) (2.8.0)
Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.6/site-packages (from pytest>=3.0->pytest-html) (18.2.0)
Requirement already satisfied: six>=1.10.0 in /usr/local/lib/python3.6/site-packages (from pytest>=3.0->pytest-html) (1.12.0)
Requirement already satisfied: pluggy>=0.7 in /usr/local/lib/python3.6/site-packages (from pytest>=3.0->pytest-html) (0.8.1)
Requirement already satisfied: atomicwrites>=1.0 in /usr/local/lib/python3.6/site-packages (from pytest>=3.0->pytest-html) (1.3.0)
Requirement already satisfied: more-itertools>=4.0.0 in /usr/local/lib/python3.6/site-packages (from pytest>=3.0->pytest-html) (5.0.0)
Requirement already satisfied: setuptools in /usr/local/lib/python3.6/site-packages (from pytest>=3.0->pytest-html) (40.4.3)
Requirement already satisfied: py>=1.5.0 in /usr/local/lib/python3.6/site-packages (from pytest>=3.0->pytest-html) (1.7.0)
Installing collected packages: pyasn1, rsa, colorama, docutils, jmespath, urllib3, botocore, s3transfer, awscli, pytest-metadata, pytest-html
  Found existing installation: colorama 0.4.1
    Uninstalling colorama-0.4.1:
      Successfully uninstalled colorama-0.4.1
Successfully installed awscli-1.16.99 botocore-1.12.89 colorama-0.3.9 docutils-0.14 jmespath-0.9.3 pyasn1-0.4.5 pytest-html-1.20.0 pytest-metadata-1.8.0 rsa-3.4.2 s3transfer-0.2.0 urllib3-1.24.1
You are using pip version 18.1, however version 19.0.1 is available.
You should consider upgrading via the 'pip install --upgrade pip' command.
Removing intermediate container f62203a0ac87
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Step 7/7 : ENTRYPOINT ["bash", ".jenkins/build-tests/run_test.sh"]
 ---> Running in d000f9073672
Removing intermediate container d000f9073672
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Successfully built 2a62755f60e3
Successfully tagged modin-project/test:8ea3c64
+ docker run --rm --shm-size=16g --cpus=4 -e MODIN_DEBUG=1 -e AWS_ACCESS_KEY_ID=**** -e AWS_SECRET_ACCESS_KEY=**** modin-project/test:8ea3c64
+ source activate py3
.jenkins/build-tests/run_test.sh: line 3: activate: No such file or directory
+ python -c 'import ray; ray.init()'
/usr/local/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
  return f(*args, **kwds)
/usr/local/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88
  return f(*args, **kwds)
WARNING: Not updating worker name since `setproctitle` is not installed. Install this with `pip install setproctitle` (or ray[debug]) to enable monitoring of worker processes.
Process STDOUT and STDERR is being redirected to /tmp/ray/session_2019-02-07_02-17-03_8/logs.
Waiting for redis server at 127.0.0.1:48946 to respond...
Waiting for redis server at 127.0.0.1:16699 to respond...
Starting Redis shard with 10.0 GB max memory.
Warning: Capping object memory store to 20.0GB. To increase this further, specify `object_store_memory` when calling ray.init() or ray start.
WARNING: The object store is using /tmp instead of /dev/shm because /dev/shm has only 17179869184 bytes available. This may slow down performance! You may be able to free up space by deleting files in /dev/shm or terminating any running plasma_store_server processes. If you are inside a Docker container, you may need to pass an argument with the flag '--shm-size' to 'docker run'.
Starting the Plasma object store with 20.0 GB memory using /tmp.
Failed to start the UI, you may need to run 'pip install jupyter'.
+ pytest -n auto --html=test_dataframe.html --self-contained-html --disable-pytest-warnings modin/pandas/test/test_dataframe.py
============================= test session starts ==============================
platform linux -- Python 3.6.6, pytest-3.9.3, py-1.7.0, pluggy-0.8.1
rootdir: /, inifile:
plugins: xdist-1.26.1, metadata-1.8.0, html-1.20.0, forked-1.0.1, cov-2.6.1
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=================================== FAILURES ===================================
________________________ test_floordiv[dense_nan_data] _________________________
[gw19] linux -- Python 3.6.6 /usr/local/bin/python

data = {'col1': [92.29539458679021, nan, nan, nan, 78.50721123857032, nan, ...], 'col10': [39.476437324251044, nan, nan, nan,...nan, nan, 67.82636383275062, nan, ...], 'col12': [72.13146856907872, nan, nan, nan, 36.890913096920066, nan, ...], ...}

    @pytest.mark.parametrize("data", test_data_values, ids=test_data_keys)
    def test_floordiv(data):
        modin_df = pd.DataFrame(data)
        pandas_df = pandas.DataFrame(data)
    
>       inter_df_math_helper(modin_df, pandas_df, "floordiv")

modin/pandas/test/test_dataframe.py:155: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

modin_df =          col33      col34      col35    ...          col30      col31      col32
0    74.258330  59.757155  49.562614 ...aN        NaN
255        NaN        NaN        NaN    ...            NaN        NaN        NaN

[256 rows x 64 columns]
pandas_df =          col33      col34      col35    ...          col30      col31      col32
0    74.258330  59.757155  49.562614 ...aN        NaN
255        NaN        NaN        NaN    ...            NaN        NaN        NaN

[256 rows x 64 columns]
op = 'floordiv'

    def inter_df_math_helper(modin_df, pandas_df, op):
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df)
        else:
            modin_result = getattr(modin_df, op)(modin_df)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4)
        else:
            modin_result = getattr(modin_df, op)(4)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4.0)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4.0)
        else:
            modin_result = getattr(modin_df, op)(4.0)
            df_equals(modin_result, pandas_result)
    
        frame_data = {
            "{}_other".format(modin_df.columns[0]): [0, 2],
            modin_df.columns[0]: [0, 19],
            modin_df.columns[1]: [1, 1],
        }
        modin_df2 = pd.DataFrame(frame_data)
        pandas_df2 = pandas.DataFrame(frame_data)
    
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df2)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df2)
        else:
            modin_result = getattr(modin_df, op)(modin_df2)
            df_equals(modin_result, pandas_result)
    
        list_test = random_state.randint(RAND_LOW, RAND_HIGH, size=(modin_df.shape[1]))
        try:
            pandas_result = getattr(pandas_df, op)(list_test, axis=1)
        except Exception as e:
            with pytest.raises(type(e)):
>               getattr(modin_df, op)(list_test, axis=1)
E               Failed: DID NOT RAISE <class 'ValueError'>

modin/pandas/test/test_dataframe.py:110: Failed
________________________ test_floordiv[sparse_nan_data] ________________________
[gw16] linux -- Python 3.6.6 /usr/local/bin/python

data = {'col1': [45.35039845130123, 72.01610496520077, 86.76524545079926, 77.65593101109458, 24.166235692456127, 32.039925501...2717829184296, 86.8633794277037, 30.485115473223058, 98.41367757584875, 84.76899537555335, 40.2922619524976, ...], ...}

    @pytest.mark.parametrize("data", test_data_values, ids=test_data_keys)
    def test_floordiv(data):
        modin_df = pd.DataFrame(data)
        pandas_df = pandas.DataFrame(data)
    
>       inter_df_math_helper(modin_df, pandas_df, "floordiv")

modin/pandas/test/test_dataframe.py:155: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

modin_df =          col33      col34      col35    ...          col30      col31      col32
0          NaN  23.181605  87.475885 ...90  26.737976
255  88.840191  62.418131  42.345827    ...      38.167143  87.250508  78.063869

[256 rows x 64 columns]
pandas_df =          col33      col34      col35    ...          col30      col31      col32
0          NaN  23.181605  87.475885 ...90  26.737976
255  88.840191  62.418131  42.345827    ...      38.167143  87.250508  78.063869

[256 rows x 64 columns]
op = 'floordiv'

    def inter_df_math_helper(modin_df, pandas_df, op):
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df)
        else:
            modin_result = getattr(modin_df, op)(modin_df)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4)
        else:
            modin_result = getattr(modin_df, op)(4)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4.0)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4.0)
        else:
            modin_result = getattr(modin_df, op)(4.0)
            df_equals(modin_result, pandas_result)
    
        frame_data = {
            "{}_other".format(modin_df.columns[0]): [0, 2],
            modin_df.columns[0]: [0, 19],
            modin_df.columns[1]: [1, 1],
        }
        modin_df2 = pd.DataFrame(frame_data)
        pandas_df2 = pandas.DataFrame(frame_data)
    
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df2)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df2)
        else:
            modin_result = getattr(modin_df, op)(modin_df2)
            df_equals(modin_result, pandas_result)
    
        list_test = random_state.randint(RAND_LOW, RAND_HIGH, size=(modin_df.shape[1]))
        try:
            pandas_result = getattr(pandas_df, op)(list_test, axis=1)
        except Exception as e:
            with pytest.raises(type(e)):
>               getattr(modin_df, op)(list_test, axis=1)
E               Failed: DID NOT RAISE <class 'ValueError'>

modin/pandas/test/test_dataframe.py:110: Failed
__________________________ test_floordiv[float_data] ___________________________
[gw17] linux -- Python 3.6.6 /usr/local/bin/python

data = {'col1': array([4.04591833e+01, 1.54958233e+01, 5.41896501e+01, 8.42917583e+01,
       5.24753939e+01, 3.59835962e+00,...334956, 68.02361963,
       60.55892736, 98.46654945, 28.88154063, 78.61429819, 23.46398883,
       43.56079776]), ...}

    @pytest.mark.parametrize("data", test_data_values, ids=test_data_keys)
    def test_floordiv(data):
        modin_df = pd.DataFrame(data)
        pandas_df = pandas.DataFrame(data)
    
>       inter_df_math_helper(modin_df, pandas_df, "floordiv")

modin/pandas/test/test_dataframe.py:155: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

modin_df =          col33      col34      col35    ...          col30      col31      col32
0    94.214248   9.487071  31.696365 ...17  14.351571
255  32.907742  88.382932  83.466852    ...      16.448429  75.436854  11.777942

[256 rows x 64 columns]
pandas_df =          col33      col34      col35    ...          col30      col31      col32
0    94.214248   9.487071  31.696365 ...17  14.351571
255  32.907742  88.382932  83.466852    ...      16.448429  75.436854  11.777942

[256 rows x 64 columns]
op = 'floordiv'

    def inter_df_math_helper(modin_df, pandas_df, op):
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df)
        else:
            modin_result = getattr(modin_df, op)(modin_df)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4)
        else:
            modin_result = getattr(modin_df, op)(4)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4.0)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4.0)
        else:
            modin_result = getattr(modin_df, op)(4.0)
            df_equals(modin_result, pandas_result)
    
        frame_data = {
            "{}_other".format(modin_df.columns[0]): [0, 2],
            modin_df.columns[0]: [0, 19],
            modin_df.columns[1]: [1, 1],
        }
        modin_df2 = pd.DataFrame(frame_data)
        pandas_df2 = pandas.DataFrame(frame_data)
    
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df2)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df2)
        else:
            modin_result = getattr(modin_df, op)(modin_df2)
            df_equals(modin_result, pandas_result)
    
        list_test = random_state.randint(RAND_LOW, RAND_HIGH, size=(modin_df.shape[1]))
        try:
            pandas_result = getattr(pandas_df, op)(list_test, axis=1)
        except Exception as e:
            with pytest.raises(type(e)):
>               getattr(modin_df, op)(list_test, axis=1)
E               Failed: DID NOT RAISE <class 'ValueError'>

modin/pandas/test/test_dataframe.py:110: Failed
___________________________ test_floordiv[int_data] ____________________________
[gw14] linux -- Python 3.6.6 /usr/local/bin/python

data = {'col1': array([94, 30, 39, 47, 50, 42, 97, 54, 87, 48, 89, 79, 56, 76, 14, 26, 67,
       79, 63, 93, 29, 35, 66, 85,...2, 67, 73, 24, 94, 66,  1,
       88, 48, 69, 25, 71, 98, 26, 88, 17, 53,  0, 60,  2, 67, 40, 36, 50,
       14]), ...}

    @pytest.mark.parametrize("data", test_data_values, ids=test_data_keys)
    def test_floordiv(data):
        modin_df = pd.DataFrame(data)
        pandas_df = pandas.DataFrame(data)
    
>       inter_df_math_helper(modin_df, pandas_df, "floordiv")

modin/pandas/test/test_dataframe.py:155: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

modin_df =      col33  col34  col35  col36  col37  ...    col28  col29  col30  col31  col32
0       51     79     61     16     6...    66      2
255     69     93     62     74     37  ...       56     33     55     29     54

[256 rows x 64 columns]
pandas_df =      col33  col34  col35  col36  col37  ...    col28  col29  col30  col31  col32
0       51     79     61     16     6...    66      2
255     69     93     62     74     37  ...       56     33     55     29     54

[256 rows x 64 columns]
op = 'floordiv'

    def inter_df_math_helper(modin_df, pandas_df, op):
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df)
        else:
            modin_result = getattr(modin_df, op)(modin_df)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4)
        else:
            modin_result = getattr(modin_df, op)(4)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4.0)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4.0)
        else:
            modin_result = getattr(modin_df, op)(4.0)
            df_equals(modin_result, pandas_result)
    
        frame_data = {
            "{}_other".format(modin_df.columns[0]): [0, 2],
            modin_df.columns[0]: [0, 19],
            modin_df.columns[1]: [1, 1],
        }
        modin_df2 = pd.DataFrame(frame_data)
        pandas_df2 = pandas.DataFrame(frame_data)
    
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df2)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df2)
        else:
            modin_result = getattr(modin_df, op)(modin_df2)
            df_equals(modin_result, pandas_result)
    
        list_test = random_state.randint(RAND_LOW, RAND_HIGH, size=(modin_df.shape[1]))
        try:
            pandas_result = getattr(pandas_df, op)(list_test, axis=1)
        except Exception as e:
            with pytest.raises(type(e)):
>               getattr(modin_df, op)(list_test, axis=1)
E               Failed: DID NOT RAISE <class 'ValueError'>

modin/pandas/test/test_dataframe.py:110: Failed
________________________ test___rmod__[sparse_nan_data] ________________________
[gw26] linux -- Python 3.6.6 /usr/local/bin/python

data = {'col1': [45.35039845130123, 72.01610496520077, 86.76524545079926, 77.65593101109458, 24.166235692456127, 32.039925501...2717829184296, 86.8633794277037, 30.485115473223058, 98.41367757584875, 84.76899537555335, 40.2922619524976, ...], ...}

    @pytest.mark.parametrize("data", test_data_values, ids=test_data_keys)
    def test___rmod__(data):
        modin_df = pd.DataFrame(data)
        pandas_df = pandas.DataFrame(data)
    
>       inter_df_math_helper(modin_df, pandas_df, "__rmod__")

modin/pandas/test/test_dataframe.py:331: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
modin/pandas/test/test_dataframe.py:113: in inter_df_math_helper
    df_equals(modin_result, pandas_result)
modin/pandas/test/utils.py:266: in df_equals
    check_index_type=False,
usr/local/lib/python3.6/site-packages/pandas/util/testing.py:1365: in assert_frame_equal
    obj='DataFrame.iloc[:, {idx}]'.format(idx=i))
usr/local/lib/python3.6/site-packages/pandas/util/testing.py:1233: in assert_series_equal
    check_dtype=check_dtype)
usr/local/lib/python3.6/site-packages/pandas/util/testing.py:1104: in assert_numpy_array_equal
    _raise(left, right, err_msg)
usr/local/lib/python3.6/site-packages/pandas/util/testing.py:1098: in _raise
    raise_assert_detail(obj, msg, left, right)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

obj = 'numpy array', message = 'numpy array values are different (5.46875 %)'
left = '[nan, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 1.1193275089538268, 26.0, 26.0, 26.0, 26.0, 26.0, 5.96118108339... 26.0, 2.6904399843458258, 26.0, 26.0, 26.0, 26.0, 3.8713133503867496, 26.0, 26.0, 26.0, 26.0, 6.493827829720345, ...]'
right = '[nan, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 1.1193275089538268, 26.0, 26.0, 26.0, 26.0, 26.0, 5.96118108339... 26.0, 2.6904399843458258, 26.0, 26.0, 26.0, 26.0, 3.8713133503867496, 26.0, 26.0, 26.0, 26.0, 6.493827829720345, ...]'
diff = None

    def raise_assert_detail(obj, message, left, right, diff=None):
        if isinstance(left, np.ndarray):
            left = pprint_thing(left)
        elif is_categorical_dtype(left):
            left = repr(left)
    
        if PY2 and isinstance(left, string_types):
            # left needs to be printable in native text type in python2
            left = left.encode('utf-8')
    
        if isinstance(right, np.ndarray):
            right = pprint_thing(right)
        elif is_categorical_dtype(right):
            right = repr(right)
    
        if PY2 and isinstance(right, string_types):
            # right needs to be printable in native text type in python2
            right = right.encode('utf-8')
    
        msg = """{obj} are different
    
    {message}
    [left]:  {left}
    [right]: {right}""".format(obj=obj, message=message, left=left, right=right)
    
        if diff is not None:
            msg += "\n[diff]: {diff}".format(diff=diff)
    
>       raise AssertionError(msg)
E       AssertionError: numpy array are different
E       
E       numpy array values are different (5.46875 %)
E       [left]:  [nan, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 1.1193275089538268, 26.0, 26.0, 26.0, 26.0, 26.0, 5.9611810833955925, 26.0, 4.027588817044403, 26.0, 26.0, 12.088999815532329, 26.0, 26.0, 26.0, 11.23333888585124, 26.0, 7.170286769906006, 26.0, 26.0, 3.8233925764446717, 26.0, 9.556421671109817, 26.0, 1.142350700607874, 26.0, 9.651266496340469, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 12.907344050514034, 26.0, 26.0, 26.0, 26.0, 26.0, 2.0536899183406945, 26.0, 26.0, 26.0, 26.0, 1.7383803623957075, 8.856033870792999, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 8.411850846983903, 26.0, 26.0, 26.0, 5.213709284456758, 5.694693419229067, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 8.502091127926036, 26.0, 26.0, 2.6904399843458258, 26.0, 26.0, 26.0, 26.0, 3.8713133503867496, 26.0, 26.0, 26.0, 26.0, 6.493827829720345, ...]
E       [right]: [nan, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 1.1193275089538268, 26.0, 26.0, 26.0, 26.0, 26.0, 5.961181083395594, 26.0, 4.027588817044403, 26.0, 26.0, 12.088999815532329, 26.0, 26.0, 26.0, 11.23333888585124, 26.0, 7.170286769906006, 26.0, 26.0, 3.8233925764446717, 26.0, 9.556421671109817, 26.0, 1.1423507006078744, 26.0, 9.651266496340469, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 12.907344050514034, 26.0, 26.0, 26.0, 26.0, 26.0, 2.0536899183406945, 26.0, 26.0, 26.0, 26.0, 1.7383803623957093, 8.856033870792999, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 8.411850846983903, 26.0, 26.0, 26.0, 5.213709284456758, 5.694693419229068, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 26.0, 8.502091127926036, 26.0, 26.0, 2.6904399843458258, 26.0, 26.0, 26.0, 26.0, 3.8713133503867496, 26.0, 26.0, 26.0, 26.0, 6.493827829720345, ...]

usr/local/lib/python3.6/site-packages/pandas/util/testing.py:1035: AssertionError
_________________________ test___floordiv__[int_data] __________________________
[gw31] linux -- Python 3.6.6 /usr/local/bin/python

data = {'col1': array([94, 30, 39, 47, 50, 42, 97, 54, 87, 48, 89, 79, 56, 76, 14, 26, 67,
       79, 63, 93, 29, 35, 66, 85,...2, 67, 73, 24, 94, 66,  1,
       88, 48, 69, 25, 71, 98, 26, 88, 17, 53,  0, 60,  2, 67, 40, 36, 50,
       14]), ...}

    @pytest.mark.parametrize("data", test_data_values, ids=test_data_keys)
    def test___floordiv__(data):
        modin_df = pd.DataFrame(data)
        pandas_df = pandas.DataFrame(data)
    
>       inter_df_math_helper(modin_df, pandas_df, "__floordiv__")

modin/pandas/test/test_dataframe.py:291: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

modin_df =      col33  col34  col35  col36  col37  ...    col28  col29  col30  col31  col32
0       51     79     61     16     6...    66      2
255     69     93     62     74     37  ...       56     33     55     29     54

[256 rows x 64 columns]
pandas_df =      col33  col34  col35  col36  col37  ...    col28  col29  col30  col31  col32
0       51     79     61     16     6...    66      2
255     69     93     62     74     37  ...       56     33     55     29     54

[256 rows x 64 columns]
op = '__floordiv__'

    def inter_df_math_helper(modin_df, pandas_df, op):
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df)
        else:
            modin_result = getattr(modin_df, op)(modin_df)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4)
        else:
            modin_result = getattr(modin_df, op)(4)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4.0)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4.0)
        else:
            modin_result = getattr(modin_df, op)(4.0)
            df_equals(modin_result, pandas_result)
    
        frame_data = {
            "{}_other".format(modin_df.columns[0]): [0, 2],
            modin_df.columns[0]: [0, 19],
            modin_df.columns[1]: [1, 1],
        }
        modin_df2 = pd.DataFrame(frame_data)
        pandas_df2 = pandas.DataFrame(frame_data)
    
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df2)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df2)
        else:
            modin_result = getattr(modin_df, op)(modin_df2)
            df_equals(modin_result, pandas_result)
    
        list_test = random_state.randint(RAND_LOW, RAND_HIGH, size=(modin_df.shape[1]))
        try:
            pandas_result = getattr(pandas_df, op)(list_test, axis=1)
        except Exception as e:
            with pytest.raises(type(e)):
>               getattr(modin_df, op)(list_test, axis=1)
E               Failed: DID NOT RAISE <class 'ValueError'>

modin/pandas/test/test_dataframe.py:110: Failed
________________________ test___rmod__[dense_nan_data] _________________________
[gw27] linux -- Python 3.6.6 /usr/local/bin/python

data = {'col1': [92.29539458679021, nan, nan, nan, 78.50721123857032, nan, ...], 'col10': [39.476437324251044, nan, nan, nan,...nan, nan, 67.82636383275062, nan, ...], 'col12': [72.13146856907872, nan, nan, nan, 36.890913096920066, nan, ...], ...}

    @pytest.mark.parametrize("data", test_data_values, ids=test_data_keys)
    def test___rmod__(data):
        modin_df = pd.DataFrame(data)
        pandas_df = pandas.DataFrame(data)
    
>       inter_df_math_helper(modin_df, pandas_df, "__rmod__")

modin/pandas/test/test_dataframe.py:331: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
modin/pandas/test/test_dataframe.py:113: in inter_df_math_helper
    df_equals(modin_result, pandas_result)
modin/pandas/test/utils.py:266: in df_equals
    check_index_type=False,
usr/local/lib/python3.6/site-packages/pandas/util/testing.py:1365: in assert_frame_equal
    obj='DataFrame.iloc[:, {idx}]'.format(idx=i))
usr/local/lib/python3.6/site-packages/pandas/util/testing.py:1233: in assert_series_equal
    check_dtype=check_dtype)
usr/local/lib/python3.6/site-packages/pandas/util/testing.py:1104: in assert_numpy_array_equal
    _raise(left, right, err_msg)
usr/local/lib/python3.6/site-packages/pandas/util/testing.py:1098: in _raise
    raise_assert_detail(obj, msg, left, right)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

obj = 'numpy array', message = 'numpy array values are different (0.39062 %)'
left = '[11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, ..., 0.08002679592768036, nan, nan, nan, 5.283863351024122, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, ...]'
right = '[11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, ..., 0.08002679592767947, nan, nan, nan, 5.283863351024122, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, ...]'
diff = None

    def raise_assert_detail(obj, message, left, right, diff=None):
        if isinstance(left, np.ndarray):
            left = pprint_thing(left)
        elif is_categorical_dtype(left):
            left = repr(left)
    
        if PY2 and isinstance(left, string_types):
            # left needs to be printable in native text type in python2
            left = left.encode('utf-8')
    
        if isinstance(right, np.ndarray):
            right = pprint_thing(right)
        elif is_categorical_dtype(right):
            right = repr(right)
    
        if PY2 and isinstance(right, string_types):
            # right needs to be printable in native text type in python2
            right = right.encode('utf-8')
    
        msg = """{obj} are different
    
    {message}
    [left]:  {left}
    [right]: {right}""".format(obj=obj, message=message, left=left, right=right)
    
        if diff is not None:
            msg += "\n[diff]: {diff}".format(diff=diff)
    
>       raise AssertionError(msg)
E       AssertionError: numpy array are different
E       
E       numpy array values are different (0.39062 %)
E       [left]:  [11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 2.1086803139762544, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 1.3186752936024018, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 0.08002679592768036, nan, nan, nan, 5.283863351024122, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, ...]
E       [right]: [11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 2.1086803139762544, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 1.3186752936024018, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, 0.08002679592767947, nan, nan, nan, 5.283863351024122, nan, nan, nan, 11.0, nan, nan, nan, 11.0, nan, nan, nan, ...]

usr/local/lib/python3.6/site-packages/pandas/util/testing.py:1035: AssertionError
______________________________ test_pow[int_data] ______________________________
[gw3] linux -- Python 3.6.6 /usr/local/bin/python

data = {'col1': array([94, 30, 39, 47, 50, 42, 97, 54, 87, 48, 89, 79, 56, 76, 14, 26, 67,
       79, 63, 93, 29, 35, 66, 85,...2, 67, 73, 24, 94, 66,  1,
       88, 48, 69, 25, 71, 98, 26, 88, 17, 53,  0, 60,  2, 67, 40, 36, 50,
       14]), ...}

    @pytest.mark.parametrize("data", test_data_values, ids=test_data_keys)
    def test_pow(data):
        modin_df = pd.DataFrame(data)
        pandas_df = pandas.DataFrame(data)
    
        # TODO: Revert to others once we have an efficient way of preprocessing for positive
        # values
        try:
            pandas_df = pandas_df.abs()
        except Exception:
            pass
        else:
            modin_df = modin_df.abs()
>           inter_df_math_helper(modin_df, pandas_df, "pow")

modin/pandas/test/test_dataframe.py:195: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

modin_df =      col33  col34  col35  col36  col37  ...    col28  col29  col30  col31  col32
0       51     79     61     16     6...    66      2
255     69     93     62     74     37  ...       56     33     55     29     54

[256 rows x 64 columns]
pandas_df =      col33  col34  col35  col36  col37  ...    col28  col29  col30  col31  col32
0       51     79     61     16     6...    66      2
255     69     93     62     74     37  ...       56     33     55     29     54

[256 rows x 64 columns]
op = 'pow'

    def inter_df_math_helper(modin_df, pandas_df, op):
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df)
        else:
            modin_result = getattr(modin_df, op)(modin_df)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4)
        else:
            modin_result = getattr(modin_df, op)(4)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4.0)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4.0)
        else:
            modin_result = getattr(modin_df, op)(4.0)
            df_equals(modin_result, pandas_result)
    
        frame_data = {
            "{}_other".format(modin_df.columns[0]): [0, 2],
            modin_df.columns[0]: [0, 19],
            modin_df.columns[1]: [1, 1],
        }
        modin_df2 = pd.DataFrame(frame_data)
        pandas_df2 = pandas.DataFrame(frame_data)
    
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df2)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df2)
        else:
            modin_result = getattr(modin_df, op)(modin_df2)
            df_equals(modin_result, pandas_result)
    
        list_test = random_state.randint(RAND_LOW, RAND_HIGH, size=(modin_df.shape[1]))
        try:
            pandas_result = getattr(pandas_df, op)(list_test, axis=1)
        except Exception as e:
            with pytest.raises(type(e)):
>               getattr(modin_df, op)(list_test, axis=1)
E               Failed: DID NOT RAISE <class 'ValueError'>

modin/pandas/test/test_dataframe.py:110: Failed
___________________________ test___rpow__[int_data] ____________________________
[gw21] linux -- Python 3.6.6 /usr/local/bin/python

data = {'col1': array([94, 30, 39, 47, 50, 42, 97, 54, 87, 48, 89, 79, 56, 76, 14, 26, 67,
       79, 63, 93, 29, 35, 66, 85,...2, 67, 73, 24, 94, 66,  1,
       88, 48, 69, 25, 71, 98, 26, 88, 17, 53,  0, 60,  2, 67, 40, 36, 50,
       14]), ...}

    @pytest.mark.parametrize("data", test_data_values, ids=test_data_keys)
    def test___rpow__(data):
        modin_df = pd.DataFrame(data)
        pandas_df = pandas.DataFrame(data)
    
>       inter_df_math_helper(modin_df, pandas_df, "__rpow__")

modin/pandas/test/test_dataframe.py:275: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

modin_df =      col33  col34  col35  col36  col37  ...    col28  col29  col30  col31  col32
0       51     79     61     16     6...    66      2
255     69     93     62     74     37  ...       56     33     55     29     54

[256 rows x 64 columns]
pandas_df =      col33  col34  col35  col36  col37  ...    col28  col29  col30  col31  col32
0       51     79     61     16     6...    66      2
255     69     93     62     74     37  ...       56     33     55     29     54

[256 rows x 64 columns]
op = '__rpow__'

    def inter_df_math_helper(modin_df, pandas_df, op):
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df)
        else:
            modin_result = getattr(modin_df, op)(modin_df)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4)
        else:
            modin_result = getattr(modin_df, op)(4)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4.0)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4.0)
        else:
            modin_result = getattr(modin_df, op)(4.0)
            df_equals(modin_result, pandas_result)
    
        frame_data = {
            "{}_other".format(modin_df.columns[0]): [0, 2],
            modin_df.columns[0]: [0, 19],
            modin_df.columns[1]: [1, 1],
        }
        modin_df2 = pd.DataFrame(frame_data)
        pandas_df2 = pandas.DataFrame(frame_data)
    
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df2)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df2)
        else:
            modin_result = getattr(modin_df, op)(modin_df2)
            df_equals(modin_result, pandas_result)
    
        list_test = random_state.randint(RAND_LOW, RAND_HIGH, size=(modin_df.shape[1]))
        try:
            pandas_result = getattr(pandas_df, op)(list_test, axis=1)
        except Exception as e:
            with pytest.raises(type(e)):
>               getattr(modin_df, op)(list_test, axis=1)
E               Failed: DID NOT RAISE <class 'ValueError'>

modin/pandas/test/test_dataframe.py:110: Failed
__________________________ test___rmod__[float_data] ___________________________
[gw25] linux -- Python 3.6.6 /usr/local/bin/python

data = {'col1': array([4.04591833e+01, 1.54958233e+01, 5.41896501e+01, 8.42917583e+01,
       5.24753939e+01, 3.59835962e+00,...334956, 68.02361963,
       60.55892736, 98.46654945, 28.88154063, 78.61429819, 23.46398883,
       43.56079776]), ...}

    @pytest.mark.parametrize("data", test_data_values, ids=test_data_keys)
    def test___rmod__(data):
        modin_df = pd.DataFrame(data)
        pandas_df = pandas.DataFrame(data)
    
>       inter_df_math_helper(modin_df, pandas_df, "__rmod__")

modin/pandas/test/test_dataframe.py:331: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
modin/pandas/test/test_dataframe.py:113: in inter_df_math_helper
    df_equals(modin_result, pandas_result)
modin/pandas/test/utils.py:266: in df_equals
    check_index_type=False,
usr/local/lib/python3.6/site-packages/pandas/util/testing.py:1365: in assert_frame_equal
    obj='DataFrame.iloc[:, {idx}]'.format(idx=i))
usr/local/lib/python3.6/site-packages/pandas/util/testing.py:1233: in assert_series_equal
    check_dtype=check_dtype)
usr/local/lib/python3.6/site-packages/pandas/util/testing.py:1104: in assert_numpy_array_equal
    _raise(left, right, err_msg)
usr/local/lib/python3.6/site-packages/pandas/util/testing.py:1098: in _raise
    raise_assert_detail(obj, msg, left, right)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

obj = 'numpy array', message = 'numpy array values are different (1.5625 %)'
left = '[11.0, 11.0, 0.6741190563917439, 0.5824186145698143, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0...11.0, 3.6948223189339444, 11.0, 11.0, 0.9882327401467452, 11.0, 11.0, 0.4017878927186427, 11.0, 11.0, 11.0, 11.0, ...]'
right = '[11.0, 11.0, 0.6741190563917439, 0.5824186145698143, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0...11.0, 3.6948223189339444, 11.0, 11.0, 0.9882327401467457, 11.0, 11.0, 0.4017878927186427, 11.0, 11.0, 11.0, 11.0, ...]'
diff = None

    def raise_assert_detail(obj, message, left, right, diff=None):
        if isinstance(left, np.ndarray):
            left = pprint_thing(left)
        elif is_categorical_dtype(left):
            left = repr(left)
    
        if PY2 and isinstance(left, string_types):
            # left needs to be printable in native text type in python2
            left = left.encode('utf-8')
    
        if isinstance(right, np.ndarray):
            right = pprint_thing(right)
        elif is_categorical_dtype(right):
            right = repr(right)
    
        if PY2 and isinstance(right, string_types):
            # right needs to be printable in native text type in python2
            right = right.encode('utf-8')
    
        msg = """{obj} are different
    
    {message}
    [left]:  {left}
    [right]: {right}""".format(obj=obj, message=message, left=left, right=right)
    
        if diff is not None:
            msg += "\n[diff]: {diff}".format(diff=diff)
    
>       raise AssertionError(msg)
E       AssertionError: numpy array are different
E       
E       numpy array values are different (1.5625 %)
E       [left]:  [11.0, 11.0, 0.6741190563917439, 0.5824186145698143, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 2.7657836903278294, 11.0, 0.6269835457505835, 11.0, 11.0, 11.0, 11.0, 0.7684067219327364, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 4.407111064251769, 11.0, 4.787422927990427, 11.0, 11.0, 11.0, 11.0, 4.280242924762624, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 2.038627600467736, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 2.3744423562342654, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 0.20738617268908488, 11.0, 11.0, 11.0, 11.0, 4.358957962726718, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 3.6948223189339444, 11.0, 11.0, 0.9882327401467452, 11.0, 11.0, 0.4017878927186427, 11.0, 11.0, 11.0, 11.0, ...]
E       [right]: [11.0, 11.0, 0.6741190563917439, 0.5824186145698143, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 2.7657836903278294, 11.0, 0.6269835457505835, 11.0, 11.0, 11.0, 11.0, 0.7684067219327364, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 4.407111064251769, 11.0, 4.787422927990427, 11.0, 11.0, 11.0, 11.0, 4.280242924762624, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 2.038627600467736, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 2.3744423562342654, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 0.207386172689084, 11.0, 11.0, 11.0, 11.0, 4.358957962726718, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 11.0, 3.6948223189339444, 11.0, 11.0, 0.9882327401467457, 11.0, 11.0, 0.4017878927186427, 11.0, 11.0, 11.0, 11.0, ...]

usr/local/lib/python3.6/site-packages/pandas/util/testing.py:1035: AssertionError
_____________________ test___rfloordiv__[sparse_nan_data] ______________________
[gw7] linux -- Python 3.6.6 /usr/local/bin/python

data = {'col1': [45.35039845130123, 72.01610496520077, 86.76524545079926, 77.65593101109458, 24.166235692456127, 32.039925501...2717829184296, 86.8633794277037, 30.485115473223058, 98.41367757584875, 84.76899537555335, 40.2922619524976, ...], ...}

    @pytest.mark.parametrize("data", test_data_values, ids=test_data_keys)
    def test___rfloordiv__(data):
        modin_df = pd.DataFrame(data)
        pandas_df = pandas.DataFrame(data)
    
>       inter_df_math_helper(modin_df, pandas_df, "__rfloordiv__")

modin/pandas/test/test_dataframe.py:299: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

modin_df =          col33      col34      col35    ...          col30      col31      col32
0          NaN  23.181605  87.475885 ...90  26.737976
255  88.840191  62.418131  42.345827    ...      38.167143  87.250508  78.063869

[256 rows x 64 columns]
pandas_df =          col33      col34      col35    ...          col30      col31      col32
0          NaN  23.181605  87.475885 ...90  26.737976
255  88.840191  62.418131  42.345827    ...      38.167143  87.250508  78.063869

[256 rows x 64 columns]
op = '__rfloordiv__'

    def inter_df_math_helper(modin_df, pandas_df, op):
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df)
        else:
            modin_result = getattr(modin_df, op)(modin_df)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4)
        else:
            modin_result = getattr(modin_df, op)(4)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4.0)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4.0)
        else:
            modin_result = getattr(modin_df, op)(4.0)
            df_equals(modin_result, pandas_result)
    
        frame_data = {
            "{}_other".format(modin_df.columns[0]): [0, 2],
            modin_df.columns[0]: [0, 19],
            modin_df.columns[1]: [1, 1],
        }
        modin_df2 = pd.DataFrame(frame_data)
        pandas_df2 = pandas.DataFrame(frame_data)
    
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df2)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df2)
        else:
            modin_result = getattr(modin_df, op)(modin_df2)
            df_equals(modin_result, pandas_result)
    
        list_test = random_state.randint(RAND_LOW, RAND_HIGH, size=(modin_df.shape[1]))
        try:
            pandas_result = getattr(pandas_df, op)(list_test, axis=1)
        except Exception as e:
            with pytest.raises(type(e)):
>               getattr(modin_df, op)(list_test, axis=1)
E               Failed: DID NOT RAISE <class 'ValueError'>

modin/pandas/test/test_dataframe.py:110: Failed
______________________ test___floordiv__[dense_nan_data] _______________________
[gw2] linux -- Python 3.6.6 /usr/local/bin/python

data = {'col1': [92.29539458679021, nan, nan, nan, 78.50721123857032, nan, ...], 'col10': [39.476437324251044, nan, nan, nan,...nan, nan, 67.82636383275062, nan, ...], 'col12': [72.13146856907872, nan, nan, nan, 36.890913096920066, nan, ...], ...}

    @pytest.mark.parametrize("data", test_data_values, ids=test_data_keys)
    def test___floordiv__(data):
        modin_df = pd.DataFrame(data)
        pandas_df = pandas.DataFrame(data)
    
>       inter_df_math_helper(modin_df, pandas_df, "__floordiv__")

modin/pandas/test/test_dataframe.py:291: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

modin_df =          col33      col34      col35    ...          col30      col31      col32
0    74.258330  59.757155  49.562614 ...aN        NaN
255        NaN        NaN        NaN    ...            NaN        NaN        NaN

[256 rows x 64 columns]
pandas_df =          col33      col34      col35    ...          col30      col31      col32
0    74.258330  59.757155  49.562614 ...aN        NaN
255        NaN        NaN        NaN    ...            NaN        NaN        NaN

[256 rows x 64 columns]
op = '__floordiv__'

    def inter_df_math_helper(modin_df, pandas_df, op):
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df)
        else:
            modin_result = getattr(modin_df, op)(modin_df)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4)
        else:
            modin_result = getattr(modin_df, op)(4)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4.0)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4.0)
        else:
            modin_result = getattr(modin_df, op)(4.0)
            df_equals(modin_result, pandas_result)
    
        frame_data = {
            "{}_other".format(modin_df.columns[0]): [0, 2],
            modin_df.columns[0]: [0, 19],
            modin_df.columns[1]: [1, 1],
        }
        modin_df2 = pd.DataFrame(frame_data)
        pandas_df2 = pandas.DataFrame(frame_data)
    
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df2)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df2)
        else:
            modin_result = getattr(modin_df, op)(modin_df2)
            df_equals(modin_result, pandas_result)
    
        list_test = random_state.randint(RAND_LOW, RAND_HIGH, size=(modin_df.shape[1]))
        try:
            pandas_result = getattr(pandas_df, op)(list_test, axis=1)
        except Exception as e:
            with pytest.raises(type(e)):
>               getattr(modin_df, op)(list_test, axis=1)
E               Failed: DID NOT RAISE <class 'ValueError'>

modin/pandas/test/test_dataframe.py:110: Failed
______________________ test___floordiv__[sparse_nan_data] ______________________
[gw1] linux -- Python 3.6.6 /usr/local/bin/python

data = {'col1': [45.35039845130123, 72.01610496520077, 86.76524545079926, 77.65593101109458, 24.166235692456127, 32.039925501...2717829184296, 86.8633794277037, 30.485115473223058, 98.41367757584875, 84.76899537555335, 40.2922619524976, ...], ...}

    @pytest.mark.parametrize("data", test_data_values, ids=test_data_keys)
    def test___floordiv__(data):
        modin_df = pd.DataFrame(data)
        pandas_df = pandas.DataFrame(data)
    
>       inter_df_math_helper(modin_df, pandas_df, "__floordiv__")

modin/pandas/test/test_dataframe.py:291: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

modin_df =          col33      col34      col35    ...          col30      col31      col32
0          NaN  23.181605  87.475885 ...90  26.737976
255  88.840191  62.418131  42.345827    ...      38.167143  87.250508  78.063869

[256 rows x 64 columns]
pandas_df =          col33      col34      col35    ...          col30      col31      col32
0          NaN  23.181605  87.475885 ...90  26.737976
255  88.840191  62.418131  42.345827    ...      38.167143  87.250508  78.063869

[256 rows x 64 columns]
op = '__floordiv__'

    def inter_df_math_helper(modin_df, pandas_df, op):
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df)
        else:
            modin_result = getattr(modin_df, op)(modin_df)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4)
        else:
            modin_result = getattr(modin_df, op)(4)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4.0)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4.0)
        else:
            modin_result = getattr(modin_df, op)(4.0)
            df_equals(modin_result, pandas_result)
    
        frame_data = {
            "{}_other".format(modin_df.columns[0]): [0, 2],
            modin_df.columns[0]: [0, 19],
            modin_df.columns[1]: [1, 1],
        }
        modin_df2 = pd.DataFrame(frame_data)
        pandas_df2 = pandas.DataFrame(frame_data)
    
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df2)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df2)
        else:
            modin_result = getattr(modin_df, op)(modin_df2)
            df_equals(modin_result, pandas_result)
    
        list_test = random_state.randint(RAND_LOW, RAND_HIGH, size=(modin_df.shape[1]))
        try:
            pandas_result = getattr(pandas_df, op)(list_test, axis=1)
        except Exception as e:
            with pytest.raises(type(e)):
>               getattr(modin_df, op)(list_test, axis=1)
E               Failed: DID NOT RAISE <class 'ValueError'>

modin/pandas/test/test_dataframe.py:110: Failed
_________________________ test___rfloordiv__[int_data] _________________________
[gw4] linux -- Python 3.6.6 /usr/local/bin/python

data = {'col1': array([94, 30, 39, 47, 50, 42, 97, 54, 87, 48, 89, 79, 56, 76, 14, 26, 67,
       79, 63, 93, 29, 35, 66, 85,...2, 67, 73, 24, 94, 66,  1,
       88, 48, 69, 25, 71, 98, 26, 88, 17, 53,  0, 60,  2, 67, 40, 36, 50,
       14]), ...}

    @pytest.mark.parametrize("data", test_data_values, ids=test_data_keys)
    def test___rfloordiv__(data):
        modin_df = pd.DataFrame(data)
        pandas_df = pandas.DataFrame(data)
    
>       inter_df_math_helper(modin_df, pandas_df, "__rfloordiv__")

modin/pandas/test/test_dataframe.py:299: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

modin_df =      col33  col34  col35  col36  col37  ...    col28  col29  col30  col31  col32
0       51     79     61     16     6...    66      2
255     69     93     62     74     37  ...       56     33     55     29     54

[256 rows x 64 columns]
pandas_df =      col33  col34  col35  col36  col37  ...    col28  col29  col30  col31  col32
0       51     79     61     16     6...    66      2
255     69     93     62     74     37  ...       56     33     55     29     54

[256 rows x 64 columns]
op = '__rfloordiv__'

    def inter_df_math_helper(modin_df, pandas_df, op):
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df)
        else:
            modin_result = getattr(modin_df, op)(modin_df)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4)
        else:
            modin_result = getattr(modin_df, op)(4)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4.0)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4.0)
        else:
            modin_result = getattr(modin_df, op)(4.0)
            df_equals(modin_result, pandas_result)
    
        frame_data = {
            "{}_other".format(modin_df.columns[0]): [0, 2],
            modin_df.columns[0]: [0, 19],
            modin_df.columns[1]: [1, 1],
        }
        modin_df2 = pd.DataFrame(frame_data)
        pandas_df2 = pandas.DataFrame(frame_data)
    
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df2)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df2)
        else:
            modin_result = getattr(modin_df, op)(modin_df2)
            df_equals(modin_result, pandas_result)
    
        list_test = random_state.randint(RAND_LOW, RAND_HIGH, size=(modin_df.shape[1]))
        try:
            pandas_result = getattr(pandas_df, op)(list_test, axis=1)
        except Exception as e:
            with pytest.raises(type(e)):
>               getattr(modin_df, op)(list_test, axis=1)
E               Failed: DID NOT RAISE <class 'ValueError'>

modin/pandas/test/test_dataframe.py:110: Failed
______________________ test___rfloordiv__[dense_nan_data] ______________________
[gw5] linux -- Python 3.6.6 /usr/local/bin/python

data = {'col1': [92.29539458679021, nan, nan, nan, 78.50721123857032, nan, ...], 'col10': [39.476437324251044, nan, nan, nan,...nan, nan, 67.82636383275062, nan, ...], 'col12': [72.13146856907872, nan, nan, nan, 36.890913096920066, nan, ...], ...}

    @pytest.mark.parametrize("data", test_data_values, ids=test_data_keys)
    def test___rfloordiv__(data):
        modin_df = pd.DataFrame(data)
        pandas_df = pandas.DataFrame(data)
    
>       inter_df_math_helper(modin_df, pandas_df, "__rfloordiv__")

modin/pandas/test/test_dataframe.py:299: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

modin_df =          col33      col34      col35    ...          col30      col31      col32
0    74.258330  59.757155  49.562614 ...aN        NaN
255        NaN        NaN        NaN    ...            NaN        NaN        NaN

[256 rows x 64 columns]
pandas_df =          col33      col34      col35    ...          col30      col31      col32
0    74.258330  59.757155  49.562614 ...aN        NaN
255        NaN        NaN        NaN    ...            NaN        NaN        NaN

[256 rows x 64 columns]
op = '__rfloordiv__'

    def inter_df_math_helper(modin_df, pandas_df, op):
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df)
        else:
            modin_result = getattr(modin_df, op)(modin_df)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4)
        else:
            modin_result = getattr(modin_df, op)(4)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4.0)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4.0)
        else:
            modin_result = getattr(modin_df, op)(4.0)
            df_equals(modin_result, pandas_result)
    
        frame_data = {
            "{}_other".format(modin_df.columns[0]): [0, 2],
            modin_df.columns[0]: [0, 19],
            modin_df.columns[1]: [1, 1],
        }
        modin_df2 = pd.DataFrame(frame_data)
        pandas_df2 = pandas.DataFrame(frame_data)
    
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df2)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df2)
        else:
            modin_result = getattr(modin_df, op)(modin_df2)
            df_equals(modin_result, pandas_result)
    
        list_test = random_state.randint(RAND_LOW, RAND_HIGH, size=(modin_df.shape[1]))
        try:
            pandas_result = getattr(pandas_df, op)(list_test, axis=1)
        except Exception as e:
            with pytest.raises(type(e)):
>               getattr(modin_df, op)(list_test, axis=1)
E               Failed: DID NOT RAISE <class 'ValueError'>

modin/pandas/test/test_dataframe.py:110: Failed
________________________ test___rfloordiv__[float_data] ________________________
[gw6] linux -- Python 3.6.6 /usr/local/bin/python

data = {'col1': array([4.04591833e+01, 1.54958233e+01, 5.41896501e+01, 8.42917583e+01,
       5.24753939e+01, 3.59835962e+00,...334956, 68.02361963,
       60.55892736, 98.46654945, 28.88154063, 78.61429819, 23.46398883,
       43.56079776]), ...}

    @pytest.mark.parametrize("data", test_data_values, ids=test_data_keys)
    def test___rfloordiv__(data):
        modin_df = pd.DataFrame(data)
        pandas_df = pandas.DataFrame(data)
    
>       inter_df_math_helper(modin_df, pandas_df, "__rfloordiv__")

modin/pandas/test/test_dataframe.py:299: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

modin_df =          col33      col34      col35    ...          col30      col31      col32
0    94.214248   9.487071  31.696365 ...17  14.351571
255  32.907742  88.382932  83.466852    ...      16.448429  75.436854  11.777942

[256 rows x 64 columns]
pandas_df =          col33      col34      col35    ...          col30      col31      col32
0    94.214248   9.487071  31.696365 ...17  14.351571
255  32.907742  88.382932  83.466852    ...      16.448429  75.436854  11.777942

[256 rows x 64 columns]
op = '__rfloordiv__'

    def inter_df_math_helper(modin_df, pandas_df, op):
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df)
        else:
            modin_result = getattr(modin_df, op)(modin_df)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4)
        else:
            modin_result = getattr(modin_df, op)(4)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4.0)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4.0)
        else:
            modin_result = getattr(modin_df, op)(4.0)
            df_equals(modin_result, pandas_result)
    
        frame_data = {
            "{}_other".format(modin_df.columns[0]): [0, 2],
            modin_df.columns[0]: [0, 19],
            modin_df.columns[1]: [1, 1],
        }
        modin_df2 = pd.DataFrame(frame_data)
        pandas_df2 = pandas.DataFrame(frame_data)
    
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df2)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df2)
        else:
            modin_result = getattr(modin_df, op)(modin_df2)
            df_equals(modin_result, pandas_result)
    
        list_test = random_state.randint(RAND_LOW, RAND_HIGH, size=(modin_df.shape[1]))
        try:
            pandas_result = getattr(pandas_df, op)(list_test, axis=1)
        except Exception as e:
            with pytest.raises(type(e)):
>               getattr(modin_df, op)(list_test, axis=1)
E               Failed: DID NOT RAISE <class 'ValueError'>

modin/pandas/test/test_dataframe.py:110: Failed
________________________ test___floordiv__[float_data] _________________________
[gw0] linux -- Python 3.6.6 /usr/local/bin/python

data = {'col1': array([4.04591833e+01, 1.54958233e+01, 5.41896501e+01, 8.42917583e+01,
       5.24753939e+01, 3.59835962e+00,...334956, 68.02361963,
       60.55892736, 98.46654945, 28.88154063, 78.61429819, 23.46398883,
       43.56079776]), ...}

    @pytest.mark.parametrize("data", test_data_values, ids=test_data_keys)
    def test___floordiv__(data):
        modin_df = pd.DataFrame(data)
        pandas_df = pandas.DataFrame(data)
    
>       inter_df_math_helper(modin_df, pandas_df, "__floordiv__")

modin/pandas/test/test_dataframe.py:291: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

modin_df =          col33      col34      col35    ...          col30      col31      col32
0    94.214248   9.487071  31.696365 ...17  14.351571
255  32.907742  88.382932  83.466852    ...      16.448429  75.436854  11.777942

[256 rows x 64 columns]
pandas_df =          col33      col34      col35    ...          col30      col31      col32
0    94.214248   9.487071  31.696365 ...17  14.351571
255  32.907742  88.382932  83.466852    ...      16.448429  75.436854  11.777942

[256 rows x 64 columns]
op = '__floordiv__'

    def inter_df_math_helper(modin_df, pandas_df, op):
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df)
        else:
            modin_result = getattr(modin_df, op)(modin_df)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4)
        else:
            modin_result = getattr(modin_df, op)(4)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4.0)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4.0)
        else:
            modin_result = getattr(modin_df, op)(4.0)
            df_equals(modin_result, pandas_result)
    
        frame_data = {
            "{}_other".format(modin_df.columns[0]): [0, 2],
            modin_df.columns[0]: [0, 19],
            modin_df.columns[1]: [1, 1],
        }
        modin_df2 = pd.DataFrame(frame_data)
        pandas_df2 = pandas.DataFrame(frame_data)
    
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df2)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df2)
        else:
            modin_result = getattr(modin_df, op)(modin_df2)
            df_equals(modin_result, pandas_result)
    
        list_test = random_state.randint(RAND_LOW, RAND_HIGH, size=(modin_df.shape[1]))
        try:
            pandas_result = getattr(pandas_df, op)(list_test, axis=1)
        except Exception as e:
            with pytest.raises(type(e)):
>               getattr(modin_df, op)(list_test, axis=1)
E               Failed: DID NOT RAISE <class 'ValueError'>

modin/pandas/test/test_dataframe.py:110: Failed
____________________________ test___pow__[int_data] ____________________________
[gw17] linux -- Python 3.6.6 /usr/local/bin/python

data = {'col1': array([94, 30, 39, 47, 50, 42, 97, 54, 87, 48, 89, 79, 56, 76, 14, 26, 67,
       79, 63, 93, 29, 35, 66, 85,...2, 67, 73, 24, 94, 66,  1,
       88, 48, 69, 25, 71, 98, 26, 88, 17, 53,  0, 60,  2, 67, 40, 36, 50,
       14]), ...}

    @pytest.mark.parametrize("data", test_data_values, ids=test_data_keys)
    def test___pow__(data):
        modin_df = pd.DataFrame(data)
        pandas_df = pandas.DataFrame(data)
    
>       inter_df_math_helper(modin_df, pandas_df, "__pow__")

modin/pandas/test/test_dataframe.py:267: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

modin_df =      col33  col34  col35  col36  col37  ...    col28  col29  col30  col31  col32
0       51     79     61     16     6...    66      2
255     69     93     62     74     37  ...       56     33     55     29     54

[256 rows x 64 columns]
pandas_df =      col33  col34  col35  col36  col37  ...    col28  col29  col30  col31  col32
0       51     79     61     16     6...    66      2
255     69     93     62     74     37  ...       56     33     55     29     54

[256 rows x 64 columns]
op = '__pow__'

    def inter_df_math_helper(modin_df, pandas_df, op):
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df)
        else:
            modin_result = getattr(modin_df, op)(modin_df)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4)
        else:
            modin_result = getattr(modin_df, op)(4)
            df_equals(modin_result, pandas_result)
    
        try:
            pandas_result = getattr(pandas_df, op)(4.0)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(4.0)
        else:
            modin_result = getattr(modin_df, op)(4.0)
            df_equals(modin_result, pandas_result)
    
        frame_data = {
            "{}_other".format(modin_df.columns[0]): [0, 2],
            modin_df.columns[0]: [0, 19],
            modin_df.columns[1]: [1, 1],
        }
        modin_df2 = pd.DataFrame(frame_data)
        pandas_df2 = pandas.DataFrame(frame_data)
    
        try:
            pandas_result = getattr(pandas_df, op)(pandas_df2)
        except Exception as e:
            with pytest.raises(type(e)):
                getattr(modin_df, op)(modin_df2)
        else:
            modin_result = getattr(modin_df, op)(modin_df2)
            df_equals(modin_result, pandas_result)
    
        list_test = random_state.randint(RAND_LOW, RAND_HIGH, size=(modin_df.shape[1]))
        try:
            pandas_result = getattr(pandas_df, op)(list_test, axis=1)
        except Exception as e:
            with pytest.raises(type(e)):
>               getattr(modin_df, op)(list_test, axis=1)
E               Failed: DID NOT RAISE <class 'ValueError'>

modin/pandas/test/test_dataframe.py:110: Failed
------------------ generated html file: /test_dataframe.html -------------------
===== 18 failed, 8764 passed, 52 skipped, 1115 warnings in 492.81 seconds ======
+ pytest --html=test_concat.html --self-contained-html --disable-pytest-warnings modin/pandas/test/test_concat.py
============================= test session starts ==============================
platform linux -- Python 3.6.6, pytest-3.9.3, py-1.7.0, pluggy-0.8.1
rootdir: /, inifile:
plugins: xdist-1.26.1, metadata-1.8.0, html-1.20.0, forked-1.0.1, cov-2.6.1
collected 8 items

modin/pandas/test/test_concat.py ........                                [100%]

-------------------- generated html file: /test_concat.html --------------------
==================== 8 passed, 25 warnings in 0.85 seconds =====================
+ pytest --html=test_io.html --self-contained-html --disable-pytest-warnings modin/pandas/test/test_io.py
============================= test session starts ==============================
platform linux -- Python 3.6.6, pytest-3.9.3, py-1.7.0, pluggy-0.8.1
rootdir: /, inifile:
plugins: xdist-1.26.1, metadata-1.8.0, html-1.20.0, forked-1.0.1, cov-2.6.1
collected 39 items

modin/pandas/test/test_io.py ......s.s......s......s.s..........s...     [100%]

---------------------- generated html file: /test_io.html ----------------------
============== 33 passed, 6 skipped, 150 warnings in 3.33 seconds ==============
+ pytest --html=test_groupby.html --self-contained-html --disable-pytest-warnings modin/pandas/test/test_groupby.py
============================= test session starts ==============================
platform linux -- Python 3.6.6, pytest-3.9.3, py-1.7.0, pluggy-0.8.1
rootdir: /, inifile:
plugins: xdist-1.26.1, metadata-1.8.0, html-1.20.0, forked-1.0.1, cov-2.6.1
collected 7 items

modin/pandas/test/test_groupby.py .......                                [100%]

------------------- generated html file: /test_groupby.html --------------------
==================== 7 passed, 440 warnings in 9.00 seconds ====================
++ git rev-parse --verify --short HEAD
+ sha_tag=8ea3c64
+ aws s3 cp test_dataframe.html s3://modin-jenkins-result/8ea3c64/ --acl public-read
Completed 256.0 KiB/4.1 MiB (517.7 KiB/s) with 1 file(s) remaining
Completed 512.0 KiB/4.1 MiB (830.1 KiB/s) with 1 file(s) remaining
Completed 768.0 KiB/4.1 MiB (1.2 MiB/s) with 1 file(s) remaining  
Completed 1.0 MiB/4.1 MiB (1.6 MiB/s) with 1 file(s) remaining    
Completed 1.2 MiB/4.1 MiB (1.8 MiB/s) with 1 file(s) remaining    
Completed 1.5 MiB/4.1 MiB (2.2 MiB/s) with 1 file(s) remaining    
Completed 1.8 MiB/4.1 MiB (2.6 MiB/s) with 1 file(s) remaining    
Completed 2.0 MiB/4.1 MiB (2.9 MiB/s) with 1 file(s) remaining    
Completed 2.2 MiB/4.1 MiB (3.1 MiB/s) with 1 file(s) remaining    
Completed 2.5 MiB/4.1 MiB (3.4 MiB/s) with 1 file(s) remaining    
Completed 2.8 MiB/4.1 MiB (3.7 MiB/s) with 1 file(s) remaining    
Completed 3.0 MiB/4.1 MiB (4.0 MiB/s) with 1 file(s) remaining    
Completed 3.2 MiB/4.1 MiB (4.3 MiB/s) with 1 file(s) remaining    
Completed 3.5 MiB/4.1 MiB (4.7 MiB/s) with 1 file(s) remaining    
Completed 3.8 MiB/4.1 MiB (5.0 MiB/s) with 1 file(s) remaining    
Completed 4.0 MiB/4.1 MiB (5.0 MiB/s) with 1 file(s) remaining    
Completed 4.1 MiB/4.1 MiB (4.4 MiB/s) with 1 file(s) remaining    
upload: ./test_dataframe.html to s3://modin-jenkins-result/8ea3c64/test_dataframe.html
+ aws s3 cp test_concat.html s3://modin-jenkins-result/8ea3c64/ --acl public-read
Completed 15.5 KiB/15.5 KiB (34.2 KiB/s) with 1 file(s) remaining
upload: ./test_concat.html to s3://modin-jenkins-result/8ea3c64/test_concat.html
+ aws s3 cp test_io.html s3://modin-jenkins-result/8ea3c64/ --acl public-read
Completed 28.4 KiB/28.4 KiB (56.7 KiB/s) with 1 file(s) remaining
upload: ./test_io.html to s3://modin-jenkins-result/8ea3c64/test_io.html
+ aws s3 cp test_groupby.html s3://modin-jenkins-result/8ea3c64/ --acl public-read
Completed 18.9 KiB/18.9 KiB (40.8 KiB/s) with 1 file(s) remaining
upload: ./test_groupby.html to s3://modin-jenkins-result/8ea3c64/test_groupby.html
Test PASSed.
Refer to this link for build results (access rights to CI server needed): 
https://amplab.cs.berkeley.edu/jenkins//job/Modin-PRB/479/
Test PASSed.
Finished: SUCCESS