Support list like label based indexing #27
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@@ Coverage Diff @@
## master #27 +/- ##
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- Coverage 82.85% 82.23% -0.62%
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Files 6 6
Lines 729 698 -31
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- Hits 604 574 -30
+ Misses 125 124 -1
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| def test_label_based_indexing_idx(sample_frame_labels): | ||
| key = ['X', 'Y', 'Z'] | ||
| results = [ | ||
| sample_frame_labels.loc[key], |
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Just to be sure, could you please check also .loc[key, :]?
| def test_label_based_col_and_idx(sample_frame_labels): | ||
| key = ['V', 'W'], ['A', 'B'] | ||
| results = [ | ||
| sample_frame_labels.loc[key], |
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I think indexing with .loc[(A, B)] is not necessarily the same as indexing with .loc[A, B]. Could you please check the second option? Actually, I'm surprised that the tuple works here (it works also in pd.DataFrame) because it's not mentioned here: https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.loc.html . I thought it's reserved for multiindex.
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Hm actually it's both the same if you use the brackets internally the object's getitem method will be called (which supports only a single argument) with the argument inside the brackets which in both cases evaluates to a tuple first.
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I'd rather stick to the [A, B] syntax just to be sure that we're independent of any internal stuff and follow the documented API.
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Well as said it's the same, but I agree:
>>> 1, 2 == (1, 2)
True
For the test it is ok though to leave it like this. Else I'd have to retype the key every time...
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Come on, I know that 1, 2 == (1, 2), but foo(1, 2) is not the same as foo((1, 2)).
And I'm not sure what you mean by "every time" here. Anyway, it's your decision what to do here.
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Hmmm yep but .loc[] is not really a function call :P
Yeah I didn't get your second comment then exactly
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@michcio1234 Added the tests you requested :) |
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@kayibal you didn't push them. |
Implements #25