Error getting COO of sparse matrix built from concatenation of series with same name

[memeplex]

Code Sample, a copy-pastable example if possible

import pandas as pd

s = pd.Series([1, 2, 3], name="x")
df = pd.concat([s, s**2], axis=1)
df = df.astype(pd.SparseDtype("float", fill_value=0))
df.sparse.to_coo()

Problem description

The above code throws IndexError: 0.

This is a problem either because it is an unsupported case but the error message is cryptic or because it is a supported case.

Expected Output

No error is thrown or an exception explaining that columns with identical names are not supported is thrown.

Output of pd.show_versions()

INSTALLED VERSIONS

commit : None
python : 3.7.5.candidate.1
python-bits : 64
OS : Linux
OS-release : 5.3.0-19-generic
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 0.25.3
numpy : 1.17.4
pytz : 2019.3
dateutil : 2.8.1
pip : 19.3.1
setuptools : 41.1.0
Cython : 0.29.14
pytest : None
hypothesis : None
sphinx : 2.2.1
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.4.1
html5lib : 1.0.1
pymysql : None
psycopg2 : 2.8.4 (dt dec pq3 ext lo64)
jinja2 : 2.10.3
IPython : 7.9.0
pandas_datareader: None
bs4 : 4.8.0
bottleneck : None
fastparquet : None
gcsfs : None
lxml.etree : 4.4.1
matplotlib : 3.1.1
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
s3fs : None
scipy : 1.3.2
sqlalchemy : 1.3.11
tables : None
xarray : None
xlrd : None
xlwt : None
xlsxwriter : None

[TomAugspurger]

We should pass a list to find_common_type in

> /Users/taugspurger/sandbox/pandas/pandas/core/arrays/sparse/accessor.py(291)to_coo()
    289         from scipy.sparse import coo_matrix
    290
--> 291         dtype = find_common_type(self._parent.dtypes)
    292         if isinstance(dtype, SparseDtype):
    293             dtype = dtype.subtype

rather than the Series. So dtype = find_common_type(list(self._parent.dtypes)) may fix it.