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