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@ -1,28 +1,22 @@ |
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import pandas as pd |
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import pandas as pd |
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# read in CSV |
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# read in CSV |
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df = pd.read_csv('cleaned/wellness.csv') |
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df = pd.read_csv('cleaned/dirty_wellness.csv') |
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def vectorize_mult(column, dictionary, file=None): |
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def vectorize_mult(column, dictionary, file=None): |
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""" |
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Handles vectorizing |
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:param column: |
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:param dictionary: |
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:param file: |
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:return: |
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""" |
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newCol = column + "Num" |
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newCol = column + "Num" |
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df[newCol] = df[column].map(dictionary) |
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df[newCol] = df[column].map(dictionary) |
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if file is not None: |
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if file is not None: |
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df.to_csv('cleaned/{}.csv'.format(file)) |
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df.to_csv('cleaned/{}.csv'.format(file)) |
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vectorize_mult("USGMeasurement", {"No": 0, "Yes": 1}, "wellness") |
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""" |
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for i, value in df["TrainingReadiness"].iteritems(): |
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if pd.notna(value): |
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value = value.split("%")[0] |
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value = float(value) * (1/100) |
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value = round(value, 2) |
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df.set_value(i, "TrainingReadinessNum", value) |
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print(value) |
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df.to_csv('cleaned/{}.csv'.format("wellness")) |
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""" |
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vectorize_mult("USGMeasurement", {"No": 0, "Yes": 1}, "wellness") |