pd.cut fails on readonly arrays

[shoyer]

Code Sample, a copy-pastable example if possible

import pandas as pd
import numpy as np

bins = np.arange(0, 100, 10)
bins.flags.writeable = False
pd.cut(np.arange(100), bins)

Results in:

ValueError                                Traceback (most recent call last)
<ipython-input-71-60b85be1194d> in <module>()
----> 1 pd.cut(np.arange(100), bins)

~/conda/envs/xarray-py36/lib/python3.6/site-packages/pandas/core/reshape/tile.py in cut(x, bins, right, labels, retbins, precision, include_lowest)
    134                               precision=precision,
    135                               include_lowest=include_lowest,
--> 136                               dtype=dtype)
    137
    138     return _postprocess_for_cut(fac, bins, retbins, x_is_series,

~/conda/envs/xarray-py36/lib/python3.6/site-packages/pandas/core/reshape/tile.py in _bins_to_cuts(x, bins, right, labels, precision, include_lowest, dtype, duplicates)
    225         return result, bins
    226
--> 227     unique_bins = algos.unique(bins)
    228     if len(unique_bins) < len(bins) and len(bins) != 2:
    229         if duplicates == 'raise':

~/conda/envs/xarray-py36/lib/python3.6/site-packages/pandas/core/algorithms.py in unique(values)
    354
    355     table = htable(len(values))
--> 356     uniques = table.unique(values)
    357     uniques = _reconstruct_data(uniques, dtype, original)
    358

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.Int64HashTable.unique (pandas/_libs/hashtable.c:16341)()

~/conda/envs/xarray-py36/lib/python3.6/site-packages/pandas/_libs/hashtable.cpython-36m-darwin.so in View.MemoryView.memoryview_cwrapper (pandas/_libs/hashtable.c:45205)()

~/conda/envs/xarray-py36/lib/python3.6/site-packages/pandas/_libs/hashtable.cpython-36m-darwin.so in View.MemoryView.memoryview.__cinit__ (pandas/_libs/hashtable.c:41440)()

ValueError: buffer source array is read-only

Problem description

This is essentially the same problem as #10043 and #17192, due to Cython issue cython/cython#1605

Expected Output

Should not error.

Output of pd.show_versions()

In [73]: pd.show_versions()

INSTALLED VERSIONS

commit: None
python: 3.6.3.final.0
python-bits: 64
OS: Darwin
OS-release: 16.7.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.20.3
pytest: 3.2.1
pip: 9.0.1
setuptools: 36.4.0
Cython: 0.26
numpy: 1.13.1
scipy: 0.19.1
xarray: 0.10.0
IPython: 6.1.0
sphinx: 1.6.3
patsy: None
dateutil: 2.6.1
pytz: 2017.2
blosc: None
bottleneck: 1.2.1
tables: None
numexpr: None
feather: None
matplotlib: 2.0.2
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 0.999
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: None

[hexgnu]

Hey everybody, I submitted a pull request fixing this the best I can.

Unfortunately it seems that Cython doesn't handle this super well so the running solution is to check whether something is writeable or not and then to fall back onto ndarray if needed.

[allComputableThings]

FYI: It looks like Cython closed the source issue with const arrays in February.
cython/cython#1605