Closed
Description
cc @TomAugspurger another one ...
Passing a sparse matrix to the SparseDataFrame constructor can generate a flood of warning message (I think because each column of the sparse matrix is converted to a SparseSeries, triggering the warning each time):
In [2]: import scipy.sparse
In [3]: sparse = scipy.sparse.rand(10, 10, 0.5)
In [4]: pd.SparseDataFrame(sparse)
/home/joris/miniconda3/envs/dev37/bin/ipython:1: FutureWarning: SparseDataFrame is deprecated and will be removed in a future version.
Use a regular DataFrame whose columns are SparseArrays instead.
See http://pandas.pydata.org/pandas-docs/stable/user_guide/sparse.html#migrating for more.
#!/home/joris/miniconda3/envs/dev37/bin/python
/home/joris/scipy/pandas/pandas/core/sparse/frame.py:230: FutureWarning: SparseSeries is deprecated and will be removed in a future version.
Use a Series with sparse values instead.
>>> series = pd.Series(pd.SparseArray(...))
See http://pandas.pydata.org/pandas-docs/stable/user_guide/sparse.html#migrating for more.
sparse_index=BlockIndex(N, blocs, blens))
/home/joris/scipy/pandas/pandas/core/sparse/frame.py:230: FutureWarning: SparseSeries is deprecated and will be removed in a future version.
Use a Series with sparse values instead.
>>> series = pd.Series(pd.SparseArray(...))
See http://pandas.pydata.org/pandas-docs/stable/user_guide/sparse.html#migrating for more.
sparse_index=BlockIndex(N, blocs, blens))
/home/joris/scipy/pandas/pandas/core/sparse/frame.py:230: FutureWarning: SparseSeries is deprecated and will be removed in a future version.
Use a Series with sparse values instead.
>>> series = pd.Series(pd.SparseArray(...))
See http://pandas.pydata.org/pandas-docs/stable/user_guide/sparse.html#migrating for more.
sparse_index=BlockIndex(N, blocs, blens))
/home/joris/scipy/pandas/pandas/core/sparse/frame.py:230: FutureWarning: SparseSeries is deprecated and will be removed in a future version.
Use a Series with sparse values instead.
>>> series = pd.Series(pd.SparseArray(...))
See http://pandas.pydata.org/pandas-docs/stable/user_guide/sparse.html#migrating for more.
sparse_index=BlockIndex(N, blocs, blens))
/home/joris/scipy/pandas/pandas/core/sparse/frame.py:230: FutureWarning: SparseSeries is deprecated and will be removed in a future version.
Use a Series with sparse values instead.
>>> series = pd.Series(pd.SparseArray(...))
See http://pandas.pydata.org/pandas-docs/stable/user_guide/sparse.html#migrating for more.
sparse_index=BlockIndex(N, blocs, blens))
/home/joris/scipy/pandas/pandas/core/sparse/frame.py:230: FutureWarning: SparseSeries is deprecated and will be removed in a future version.
Use a Series with sparse values instead.
>>> series = pd.Series(pd.SparseArray(...))
See http://pandas.pydata.org/pandas-docs/stable/user_guide/sparse.html#migrating for more.
sparse_index=BlockIndex(N, blocs, blens))
/home/joris/scipy/pandas/pandas/core/sparse/frame.py:230: FutureWarning: SparseSeries is deprecated and will be removed in a future version.
Use a Series with sparse values instead.
>>> series = pd.Series(pd.SparseArray(...))
See http://pandas.pydata.org/pandas-docs/stable/user_guide/sparse.html#migrating for more.
sparse_index=BlockIndex(N, blocs, blens))
/home/joris/scipy/pandas/pandas/core/sparse/frame.py:230: FutureWarning: SparseSeries is deprecated and will be removed in a future version.
Use a Series with sparse values instead.
>>> series = pd.Series(pd.SparseArray(...))
See http://pandas.pydata.org/pandas-docs/stable/user_guide/sparse.html#migrating for more.
sparse_index=BlockIndex(N, blocs, blens))
/home/joris/scipy/pandas/pandas/core/sparse/frame.py:230: FutureWarning: SparseSeries is deprecated and will be removed in a future version.
Use a Series with sparse values instead.
>>> series = pd.Series(pd.SparseArray(...))
See http://pandas.pydata.org/pandas-docs/stable/user_guide/sparse.html#migrating for more.
sparse_index=BlockIndex(N, blocs, blens))
Out[4]:
0 1 2 3 4 5 6 7 8 9
0 0.856466 0.482052 0.289636 NaN 0.369485 NaN 0.907167 NaN NaN 0.531253
1 NaN NaN 0.305235 NaN NaN NaN 0.744132 0.001257 NaN 0.406300
2 NaN NaN 0.638244 NaN NaN NaN 0.436574 NaN NaN 0.225573
3 0.881299 NaN 0.645047 0.203569 NaN 0.341134 NaN 0.553526 0.539011 0.682595
4 0.481258 NaN NaN 0.919469 NaN 0.101564 NaN NaN NaN NaN
5 0.244346 0.282246 NaN NaN NaN NaN NaN NaN 0.412830 NaN
6 0.051837 NaN 0.101553 0.512826 0.985031 0.679645 0.248445 NaN 0.081652 NaN
7 0.048519 NaN 0.621497 0.483698 NaN NaN NaN 0.548918 NaN 0.716907
8 NaN 0.801704 NaN NaN NaN 0.611459 0.669670 NaN 0.835271 0.336365
9 0.302106 NaN 0.672587 0.609117 0.570041 0.662911 0.684364 NaN NaN 0.795059