30 lines
1.4 KiB
Python
30 lines
1.4 KiB
Python
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import ebay_api
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import numpy as np
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'''
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file used to compile methods from ebay_api.py for curating training data
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'''
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curate = ebay_api.CurateData()
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raw_data = curate.import_raw()
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training = curate.to_training(raw_data) # NOTE have to reference PictureURL list here if you want to expand. Other column is string in subsequent dfs
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# or use dropd.PictureURL.split(' ')
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class_training = curate.class_training(training)
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nvl_training = curate.nvl_training(training)
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extracted_df = curate.extract_contents(nvl_training)
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dropd = curate.drop_nvl_cols(extracted_df)
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def expand_nvlclass(class_training, dropd):
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'''
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takes image url list from each cell and expands them into separate/duplicate
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instances. Modifies both class training and dropd dfs. Appends custom
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image url dict {'source':'destination'}.
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'''
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#interm_s =class_training.PictureURL.apply(lambda x: len(x))
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#expanded_class_training = class_training.loc[np.repeat(class_training.index.values, interm_s)].reset_index(drop=True)
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expanded_class_training = class_training.explode('PictureURL').reset_index(drop=True)
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expanded_dropd = dropd.loc[np.repeat(dropd.index.values, interm_s)].reset_index(drop=True) # TODO CHANGE this to use explode(). picture list needs preservation
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# prior to creating dropd and extracted. maybe run extraced_df after dropd or after running nvl_training
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#interm_s = interm_s.astype(str).applymap(lambda x: x.split(',')*4)
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