TST: refactored test_factorize #32311
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SaturnFromTitan
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pandas/tests/base/test_ops.py
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| exp_arr = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4], np.intp) | ||
| codes, uniques = n.factorize(sort=False) | ||
| tm.assert_numpy_array_equal(codes, exp_arr) | ||
| # CI: on linux 32bit the dtype is int32, otherwise int64 |
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This seems like a bug itself; is there an open issue for it? If not can you open one?
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Could be related to #31856
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I think I addressed all your comments @WillAyd |
| expected_codes = [expected_uniques_list.index(val) for val in obj] | ||
| expected_codes = np.asarray(expected_codes, dtype=np.intp) |
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Can you not just use np.take here instead?
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you can use expected_uniques.take is better
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I don't think I can use take here. I want to construct an array containing the indices in expected_uniques of the values of obj.
# given
obj = Series([1, 2, 1, 3, 5])
expected_uniques = obj.unique() # array([1, 2, 3, 5])
# needed
expected_codes = array([0, 1, 0, 2, 3])
I could only use take if already have the indices and need the values. I basically need the reverse of take.
I guess I could use where somehow, but it will probably be more complex than just using vanilla python list.index()
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I think you can just use pd.factorize then
In [7]: import pandas as pd
In [8]: obj = pd.Series([1, 2, 1, 3, 5])
In [10]: pd.factorize(obj)
Out[10]: (array([0, 1, 0, 2, 3]), Int64Index([1, 2, 3, 5], dtype='int64'))There was a problem hiding this comment.
I'm testing factorize here, so I need an alternative implementation 😄
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ok you can actually use .get_loc but a simple impl is better; can you add a comment explaining what you are doing (factorizing)
| expected_codes = [expected_uniques_list.index(val) for val in obj] | ||
| expected_codes = np.asarray(expected_codes, dtype=np.intp) |
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you can use expected_uniques.take is better
| expected_codes = [expected_uniques_list.index(val) for val in obj] | ||
| expected_codes = np.asarray(expected_codes, dtype=np.intp) |
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ok you can actually use .get_loc but a simple impl is better; can you add a comment explaining what you are doing (factorizing)
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@jreback took care of your comment and CI is green now |
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Thanks @SaturnFromTitan |
TST: refactored test_factorize (pandas-dev#32311)
part of #23877
black pandasgit diff upstream/master -u -- "*.py" | flake8 --diff