BUG: tuple-of-tuples indexing results in NumPy VisibleDeprecationWarning #35437
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simonjayhawkins
added
Bug
Indexing
Comment on lines
+142
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+143
| with warnings.catch_warnings(): | ||
| warnings.simplefilter("ignore", category=np.VisibleDeprecationWarning) |
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Getting these can be somewhat expensive. Does this slow down DataFrame.__getitem__ or Series.__getitem__ at all?
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it's not free, but not significant for ser[[tup]]
1187 function calls (1183 primitive calls) in 0.002 seconds
Ordered by: internal time
ncalls tottime percall cumtime percall filename:lineno(function)
4/2 0.000 0.000 0.001 0.000 base.py:289(__new__)
281 0.000 0.000 0.000 0.000 {built-in method builtins.isinstance}
14 0.000 0.000 0.000 0.000 {built-in method numpy.array}
4 0.000 0.000 0.000 0.000 {pandas._libs.lib.infer_dtype}
94 0.000 0.000 0.000 0.000 generic.py:10(_check)
1 0.000 0.000 0.002 0.002 {built-in method builtins.exec}
5 0.000 0.000 0.000 0.000 common.py:221(asarray_tuplesafe)
2 0.000 0.000 0.000 0.000 common.py:97(is_bool_indexer)
2 0.000 0.000 0.000 0.000 {method 'reduce' of 'numpy.ufunc' objects}
1 0.000 0.000 0.000 0.000 indexing.py:1257(_validate_read_indexer)
7 0.000 0.000 0.000 0.000 warnings.py:458(__enter__)
6 0.000 0.000 0.000 0.000 _dtype.py:321(_name_get)
1 0.000 0.000 0.000 0.000 {pandas._libs.algos.take_1d_int64_int64}
20 0.000 0.000 0.000 0.000 common.py:1460(is_extension_array_dtype)
1 0.000 0.000 0.000 0.000 algorithms.py:1586(take_nd)
1 0.000 0.000 0.000 0.000 {method 'get_indexer' of 'pandas._libs.index.IndexEngine' objects}
23 0.000 0.000 0.000 0.000 base.py:256(is_dtype)
1 0.000 0.000 0.002 0.002 series.py:910(_get_with)
1 0.000 0.000 0.000 0.000 base.py:2951(get_indexer)
144 0.000 0.000 0.000 0.000 {built-in method builtins.getattr}
20 0.000 0.000 0.000 0.000 base.py:413(find)
7 0.000 0.000 0.000 0.000 warnings.py:181(_add_filter)
1 0.000 0.000 0.000 0.000 generic.py:4493(_reindex_with_indexers)
2 0.000 0.000 0.000 0.000 cast.py:441(maybe_promote)
1 0.000 0.000 0.002 0.002 series.py:868(__getitem__)
1 0.000 0.000 0.002 0.002 indexing.py:1078(_getitem_axis)
21 0.000 0.000 0.000 0.000 common.py:1600(_is_dtype_type)
2 0.000 0.000 0.000 0.000 base.py:5718(_maybe_cast_data_without_dtype)
7 0.000 0.000 0.000 0.000 dtypes.py:1113(is_dtype)
1 0.000 0.000 0.000 0.000 managers.py:1267(_slice_take_blocks_ax0)
2 0.000 0.000 0.000 0.000 cast.py:1559(construct_1d_object_array_from_listlike)
3 0.000 0.000 0.000 0.000 {built-in method numpy.empty}
3 0.000 0.000 0.000 0.000 generic.py:377(_get_axis)
1 0.000 0.000 0.001 0.001 indexing.py:1208(_get_listlike_indexer)
1 0.000 0.000 0.000 0.000 blocks.py:1233(take_nd)
76 0.000 0.000 0.000 0.000 {built-in method builtins.issubclass}
9 0.000 0.000 0.000 0.000 common.py:1565(_get_dtype)
6 0.000 0.000 0.000 0.000 _dtype.py:24(_kind_name)
9 0.000 0.000 0.000 0.000 common.py:530(is_categorical_dtype)
7 0.000 0.000 0.000 0.000 dtypes.py:901(is_dtype)
9 0.000 0.000 0.000 0.000 common.py:492(is_interval_dtype)
1 0.000 0.000 0.000 0.000 algorithms.py:1457(_get_take_nd_function)
7 0.000 0.000 0.000 0.000 warnings.py:165(simplefilter)
what's the best approach?
jreback
requested changes
Jul 28, 2020
to prevent nested tuples in the index? |
|
I'll close this for now to clear the queue, I'll revisit once on top of 1.1.0 regressions. There could be lots to do here to avoid 7 repeated calls to np.asarray and maintain state for the indexer checks. |
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black pandasgit diff upstream/master -u -- "*.py" | flake8 --diff