DataFrame.sparse.from_spmatrix seems inefficient with large (but very sparse) matrices?
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd
from scipy.sparse import csr_matrix
mil = 1000000
big_csr_diag_1s = csr_matrix((mil, mil), dtype="float")
# Following line takes around 15 seconds to run
big_csr_diag_1s.setdiag(1)
# At this point, big_csr_diag_1s is just a completely-sparse matrix with the only
# nonzero values being values of 1 on its diagonal (and there are 1 million of
# these values; I don't think this should be *too* bad to store in a sparse data
# structure).
# The following line runs for at least 5 minutes (I killed it after that point):
pd.DataFrame.sparse.from_spmatrix(big_csr_diag_1s)
```
#### Problem description

It seems like the [scipy csr matrix](https://docs.scipy.org/doc/scipy/reference/generated/scipy.sparse.csr_matrix.html) is being converted to dense somewhere in `pd.DataFrame.sparse.from_spmatrix()`, which results in that function taking a large amount of time (on my laptop, at least).

I _think_ this seems indicative of an efficiency problem, but if constructing the sparse DataFrame in this way really is expected to take a huge amount of time then I can close this issue. Thanks!

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.8.1.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.15.0-76-generic
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.0.1
numpy            : 1.18.1
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 45.2.0.post20200210
Cython           : 0.29.15
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : None
IPython          : 7.12.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : None
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
numba            : None

</details>
