SparseSeries throws a ValueError exception when printing large arrays · Issue #13144 · pandas-dev/pandas (original) (raw)

import scipy.sparse as sps
import pandas as pd
A = sps.rand(350, 18)
ss = pd.SparseSeries.from_coo(A)
print(ss)

A = sps.rand(350, 17)
ss = pd.SparseSeries.from_coo(A)
print(ss)

The expected output is that both cases print the SparseSeries. However, only the second case is printed properly. The first case throws the following exception:

Traceback (most recent call last):
  File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/sparse/series.py", line 420, in _get_values
    fastpath=True).__finalize__(self)
  File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/sparse/series.py", line 222, in __init__
    self.index = index
  File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/core/generic.py", line 2685, in __setattr__
    return object.__setattr__(self, name, value)
  File "pandas/src/properties.pyx", line 65, in pandas.lib.AxisProperty.__set__ (pandas/lib.c:44748)
  File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/core/series.py", line 274, in _set_axis
    labels = _ensure_index(labels)
  File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/indexes/base.py", line 3409, in _ensure_index
    return Index(index_like)
  File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/indexes/base.py", line 268, in __new__
    cls._scalar_data_error(data)
  File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/indexes/base.py", line 483, in _scalar_data_error
    repr(data)))
TypeError: Index(...) must be called with a collection of some kind, None was passed

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/core/base.py", line 46, in __str__
    return self.__unicode__()
  File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/sparse/series.py", line 306, in __unicode__
    series_rep = Series.__unicode__(self)
  File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/core/series.py", line 984, in __unicode__
    max_rows=max_rows)
  File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/core/series.py", line 1025, in to_string
    dtype=dtype, name=name, max_rows=max_rows)
  File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/core/series.py", line 1052, in _get_repr
    max_rows=max_rows)
  File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/formats/format.py", line 145, in __init__
    self._chk_truncate()
    File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/formats/format.py", line 158, in _chk_truncate
   series = concat((series.iloc[:row_num],
  File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/core/indexing.py", line 1296, in __getitem__
    return self._getitem_axis(key, axis=0)
  File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/core/indexing.py", line 1587, in _getitem_axis
    return self._get_slice_axis(key, axis=axis)
  File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/core/indexing.py", line 1579, in _get_slice_axis
    return self._slice(slice_obj, axis=axis, kind='iloc')
  File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/core/indexing.py", line 99, in _slice
    return self.obj._slice(obj, axis=axis, kind=kind)
  File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/core/series.py", line 578, in _slice
    return self._get_values(slobj)
  File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/sparse/series.py", line 422, in _get_values
    return self[indexer]
  File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/sparse/series.py", line 396, in __getitem__
    return self._get_val_at(self.index.get_loc(key))
  File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/sparse/series.py", line 392, in _get_val_at
    return self.block.values._get_val_at(loc)
  File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/sparse/array.py", line 308, in _get_val_at
    if loc < 0:
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

>>> pd.show_versions()

INSTALLED VERSIONS
------------------
commit: None
python: 3.5.1.final.0
python-bits: 64
OS: Darwin
OS-release: 15.4.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.18.1
nose: None
pip: 8.1.1
setuptools: 20.7.0
Cython: 0.24
numpy: 1.11.0
scipy: 0.17.0
statsmodels: None
xarray: None
IPython: 4.2.0
sphinx: 1.4.1
patsy: None
dateutil: 2.5.2
pytz: 2016.3
blosc: None
bottleneck: None
tables: 3.2.2
numexpr: 2.5.2
matplotlib: 1.5.1
openpyxl: 2.3.2
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
httplib2: 0.9.2
apiclient: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.8
boto: None
pandas_datareader: None