Numpy 1.11.2 fails as a pandas dependency.

Numpy fails to serve as a dependency for pandas.

I was trying to use pandas (installed the binaries and dependencies using conda, then using pip, then built then using no-binaries option); still getting error.

Numpy is available (1.11.2). I understand some interface is not provided by numpy anymore. Python version I am using is 2.7.11. List of packages installed are bellow.

Error message: C:…Miniconda2\lib\site-packages\numpy\core__init__.py:14: Warning: Numpy built with MINGW-W64 on Windows 64 bits is experimental, and only available for testing. You are advised not to use it for production.

CRASHES ARE TO BE EXPECTED - PLEASE REPORT THEM TO NUMPY DEVELOPERS from . import multiarray Traceback (most recent call last): File “io.py”, line 2, in <module> from data import support File “…\support.py”, line 3, in <module> import pandas File “…Miniconda2\lib\site-packages\pandas__init__.py”, line 18, in <module> raise ImportError(“Missing required dependencies {0}”.format(missing_dependencies)) ImportError: Missing required dependencies [‘numpy’]

Code that generates the error is really simple:

import cPickle as pickle
import pandas
from sklearn import preprocessing

def loadDataset(filename = '../../../../data_scaled.csv'):
    data_scaled = pandas.read_csv(filename)
    data_scaled = pandas.DataFrame(data_scaled)
    data_scaled.drop('Unnamed: 0', 1, inplace=True)
    return data_scaled

def scale(data):
    df = data.copy()
    df.drop('IDELSA', 1, inplace=True, errors='ignore')
    column_names = df.columns
    scaler = preprocessing.StandardScaler()
    df = scaler.fit_transform(df)
    df = pandas.DataFrame(df)
    df.columns = column_names

    return [df, scaler]


def scale_min_max(data, min_p=0, max_p=1):
    df = data.copy()
    df.drop('IDELSA', 1, inplace=True)
    column_names = df.columns
    scaler = preprocessing.MinMaxScaler(feature_range=[min_p,max_p])
    df = scaler.fit_transform(df)
    df = pandas.DataFrame(df)
    df.columns = column_names

    return [df, scaler]


def openFile(filename):
    with open(filename, "rb") as input_file:
        f = pickle.load(input_file)
    return f


def save_object(obj, filename):
    with open(filename, 'wb') as output:
        pickle.dump(obj, output, pickle.HIGHEST_PROTOCOL)

packages installed (conda and pip) C:>pip list appdirs (1.4.0) backports-abc (0.4) backports.ssl-match-hostname (3.4.0.2) BeautifulSoup (3.2.1) beautifulsoup4 (4.5.1) Bottleneck (1.1.0) bs4 (0.0.1) cffi (1.8.3) colorama (0.3.7) conda (4.2.9) cryptography (1.5.2) cycler (0.10.0) Cython (0.24.1) deap (1.0.2) decorator (4.0.9) enum34 (1.1.6) hyperopt (0.0.2) idna (2.1) imbalanced-learn (0.1.8) inflection (0.3.1) ipaddress (1.0.17) ipykernel (4.3.1) ipython (4.1.2) ipython-genutils (0.1.0) ipywidgets (4.1.1) Jinja2 (2.8) jsonschema (2.4.0) jupyter (1.0.0) jupyter-client (4.2.2) jupyter-console (4.1.1) jupyter-core (4.1.0) MarkupSafe (0.23) matplotlib (1.5.3) menuinst (1.3.2) mistune (0.7.2) more-itertools (2.2) nbconvert (4.1.0) nbformat (4.0.1) ndg-httpsclient (0.3.3) nose (1.3.7) notebook (4.1.0) numexpr (2.6.1) numpy (1.11.2) Optunity (1.1.1) pandas (0.19.0) path.py (0.0.0) pickleshare (0.5) pip (8.1.2) plotly (1.12.2) py (1.4.31) pyasn1 (0.1.9) pycosat (0.6.1) pycparser (2.14) pycrypto (2.6.1) pycuda (2016.1.2+cuda7518) pydot (1.2.2) Pygments (2.1.1) pyOpenSSL (0.14) pyparsing (2.1.9) pyreadline (2.1) pytest (2.9.2) python-dateutil (2.5.1) pytools (2016.2.1) pytz (2016.3) PyYAML (3.11) pyzmq (15.2.0) qtconsole (4.2.1) requests (2.11.1) ruamel-yaml (-VERSION) scikit-learn (0.18) scipy (0.18.1) selenium (2.53.6) setuptools (20.3) simplegeneric (0.8.1) singledispatch (3.4.0.3) six (1.10.0) Theano (0.8.2) tornado (4.3) TPOT (0.4.1) tqdm (4.8.3) traitlets (4.2.1) update-checker (0.12) urllib3 (1.18) wheel (0.29.0)

[MuffintopBikini]

I’m having the exact same issue.

[aniketanvit]

Same issue…