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PERF: optimize DataFrame.sparse.from_spmatrix performance #32825

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Merged
merged 18 commits into from
Mar 22, 2020
Merged

PERF: optimize DataFrame.sparse.from_spmatrix performance #32825

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3ffe7f2
PERF: fix SparseArray._simple_new object initialization
jorisvandenbossche Mar 19, 2020
93bf825
Initial implementation
rth Mar 19, 2020
e21701b
Merge remote-tracking branch 'upstream/master' into opt-sparse-init
rth Mar 19, 2020
e095e7f
Improve docstring
rth Mar 19, 2020
11afe40
Add what's new
rth Mar 19, 2020
eda0732
Update doc/source/whatsnew/v1.1.0.rst
rth Mar 19, 2020
40f4cd6
Improve what's new
rth Mar 19, 2020
508fda5
Add random state
rth Mar 19, 2020
0053817
Add inline comment about sort_indices
rth Mar 19, 2020
42792a3
Use absolute import
rth Mar 19, 2020
c8f7abc
Update pandas/_libs/sparse.pyx
rth Mar 19, 2020
e541b0d
Rename variable
rth Mar 19, 2020
0a0bafc
Merge remote-tracking branch 'upstream/master' into opt-sparse-init
rth Mar 20, 2020
ce6619e
Use DataFrame._from_arrays(..., verify_integrity=False)
rth Mar 20, 2020
e063c8a
checkout upstream/master -- asv_bench/benchmarks/sparse.py
rth Mar 20, 2020
8efe3ad
Merge remote-tracking branch 'upstream/master' into opt-sparse-init
rth Mar 22, 2020
20c3685
Link to PR's by Joris in what's new
rth Mar 22, 2020
d750eb4
Use ensure_index when the columns/index is provided by the user
rth Mar 22, 2020
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Add random state
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@rth
rth committed Mar 19, 2020
commit 508fda51f97b372eb157bc42983200fb49e5fda7
3 changes: 1 addition & 2 deletions asv_bench/benchmarks/sparse.py
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Expand Up @@ -45,8 +45,7 @@ def time_sparse_array(self, dense_proportion, fill_value, dtype):
class SparseDataFrameConstructor:
def setup(self):
N = 1000
self.arr = np.arange(N)
self.sparse = scipy.sparse.rand(N, N, 0.005)
self.sparse = scipy.sparse.rand(N, N, 0.005, random_state=0)
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@jorisvandenbossche jorisvandenbossche Mar 20, 2020

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given what we said in the other PR, you can remove this random state again (it's covered by the global setup function which will be run for every benchmark)

def time_from_scipy(self):
pd.DataFrame.sparse.from_spmatrix(self.sparse)
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