DataFrame.iloc raises ValueError: buffer source array is read-only when applied to read-only indices

[lesteve]

Snippet reproducing the problem:

import numpy as np
import pandas as pd

df = pd.DataFrame({'data': np.ones(100, dtype='float64')})
indices = np.array([1, 3, 6])
indices.flags.writeable = False
df.iloc[indices]

This seems like a variation of #10043 (fixed by #10070). The difference here is that the indices is read-only not the numpy arrays inside the DataFrame. For completeness this problem was seen in scikit-learn as a by-product of debugging scikit-learn/scikit-learn#9483. We can very likely work-around the problem on the scikit-learn side by copying the indices if they are read-only.

Full stack-trace:

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-6-fb86e43fb729> in <module>()
      5 indices = np.array([1, 3, 6])
      6 indices.flags.writeable = False
----> 7 df.iloc[indices]

/volatile/le243287/miniconda3/lib/python3.6/site-packages/pandas/core/indexing.py in __getitem__(self, key)
   1326         else:
   1327             key = com._apply_if_callable(key, self.obj)
-> 1328             return self._getitem_axis(key, axis=0)
   1329 
   1330     def _is_scalar_access(self, key):

/volatile/le243287/miniconda3/lib/python3.6/site-packages/pandas/core/indexing.py in _getitem_axis(self, key, axis)
   1736         # a list of integers
   1737         elif is_list_like_indexer(key):
-> 1738             return self._get_list_axis(key, axis=axis)
   1739 
   1740         # a single integer

/volatile/le243287/miniconda3/lib/python3.6/site-packages/pandas/core/indexing.py in _get_list_axis(self, key, axis)
   1713         """
   1714         try:
-> 1715             return self.obj.take(key, axis=axis, convert=False)
   1716         except IndexError:
   1717             # re-raise with different error message

/volatile/le243287/miniconda3/lib/python3.6/site-packages/pandas/core/generic.py in take(self, indices, axis, convert, is_copy, **kwargs)                                                                                                 
   1926         new_data = self._data.take(indices,
   1927                                    axis=self._get_block_manager_axis(axis),
-> 1928                                    convert=True, verify=True)
   1929         result = self._constructor(new_data).__finalize__(self)
   1930 

/volatile/le243287/miniconda3/lib/python3.6/site-packages/pandas/core/internals.py in take(self, indexer, axis, verify, convert)
   4009         new_labels = self.axes[axis].take(indexer)
   4010         return self.reindex_indexer(new_axis=new_labels, indexer=indexer,
-> 4011                                     axis=axis, allow_dups=True)
   4012 
   4013     def merge(self, other, lsuffix='', rsuffix=''):

/volatile/le243287/miniconda3/lib/python3.6/site-packages/pandas/core/internals.py in reindex_indexer(self, new_axis, indexer, axis, fill_value, allow_dups, copy)
   3895             new_blocks = [blk.take_nd(indexer, axis=axis, fill_tuple=(
   3896                 fill_value if fill_value is not None else blk.fill_value,))
-> 3897                 for blk in self.blocks]
   3898 
   3899         new_axes = list(self.axes)

/volatile/le243287/miniconda3/lib/python3.6/site-packages/pandas/core/internals.py in <listcomp>(.0)
   3895             new_blocks = [blk.take_nd(indexer, axis=axis, fill_tuple=(
   3896                 fill_value if fill_value is not None else blk.fill_value,))
-> 3897                 for blk in self.blocks]
   3898 
   3899         new_axes = list(self.axes)

/volatile/le243287/miniconda3/lib/python3.6/site-packages/pandas/core/internals.py in take_nd(self, indexer, axis, new_mgr_locs, fill_tuple)
   1044             fill_value = fill_tuple[0]
   1045             new_values = algos.take_nd(values, indexer, axis=axis,
-> 1046                                        allow_fill=True, fill_value=fill_value)
   1047 
   1048         if new_mgr_locs is None:

/volatile/le243287/miniconda3/lib/python3.6/site-packages/pandas/core/algorithms.py in take_nd(arr, indexer, axis, out, fill_value, mask_info, allow_fill)
   1469     func = _get_take_nd_function(arr.ndim, arr.dtype, out.dtype, axis=axis,
   1470                                  mask_info=mask_info)
-> 1471     func(arr, indexer, out, fill_value)
   1472 
   1473     if flip_order:

pandas/_libs/algos_take_helper.pxi in pandas._libs.algos.take_2d_axis0_float64_float64 (pandas/_libs/algos.c:110417)()

/volatile/le243287/miniconda3/lib/python3.6/site-packages/pandas/_libs/algos.cpython-36m-x86_64-linux-gnu.so in View.MemoryView.memoryview_cwrapper (pandas/_libs/algos.c:124730)()

/volatile/le243287/miniconda3/lib/python3.6/site-packages/pandas/_libs/algos.cpython-36m-x86_64-linux-gnu.so in View.MemoryView.memoryview.__cinit__ (pandas/_libs/algos.c:120965)()

ValueError: buffer source array is read-only

Pandas version information:

INSTALLED VERSIONS ------------------https://github.com/scikit-learn/scikit-learn/issues/9483 commit: None python: 3.6.2.final.0 python-bits: 64 OS: Linux OS-release: 4.4.0-83-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_GB.UTF-8 LOCALE: en_GB.UTF-8

pandas: 0.20.3
pytest: 3.1.3
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.26
numpy: 1.13.1
scipy: 0.19.1
xarray: None
IPython: 6.1.0
sphinx: 1.6.2
patsy: 0.4.1
dateutil: 2.6.1
pytz: 2017.2
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.0.2
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: 4.6.0
html5lib: 0.9999999
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: None

[chris-b1]

It'd be nice if this were addressed in Cython, xref cython/cython#1605

But until then could do something similar to #10070