OneHotEncodingTransformer support for lists and lists of lists #137
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@@ Coverage Diff @@
## master #137 +/- ##
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+ Coverage 98.61% 98.65% +0.04%
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Files 9 9
Lines 434 447 +13
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+ Hits 428 441 +13
Misses 6 6
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rdt/transformers/categorical.py
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| """ | ||
| if isinstance(data, list): | ||
| data = np.array(data) | ||
| if len(data.shape) == 2: |
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Maybe we should put this block one level higher, outside of the isinstance(data, list) block?
This way we would also support 2D numpy arrays as input.
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Sorry, I'm a little confused here, you mean just delete the isinstance line?
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No, I mean removing the indentation of the if len(data.shape) lines one level, so they are always run independently on whether the input was a list or a numpy array.
This way, if the input was already a numpy array, its shape is validated too.
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Oh, you mean this?
if isinstance(data, list):
data = np.array(data)
if isinstance(data, np.ndarray):
if len(data.shape) == 2:
if data.shape[1] != 1:
raise ValueError("Unexpected format.")
data = data[:, 0]
elif len(data.shape) > 2:
raise ValueError("Unexpected format.")
return dataMaybe at this point we might as well just support anything np.ndarray does (although I'll have to write a few test cases to make sure it actually works)? Like this:
data = np.array(data)
if len(data.shape) == 2:
if data.shape[1] != 1:
raise ValueError("Unexpected format.")
data = data[:, 0]
elif len(data.shape) > 2:
raise ValueError("Unexpected format.")
return data
rdt/transformers/categorical.py
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| @@ -236,15 +236,21 @@ def _prepare_data(data): | |||
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| Returns: | |||
| pandas.Series or numpy.ndarray | |||
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| if isinstance(data, list): | |||
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I suspect these lines have made their way here by error :-)
Resolves sdv-dev/CTGAN#87