DOC - Clean Up Chequing Account Dataset #20
Description
Reformat entries in Chequing Account Dataset so that it is uniform and standardised across all columns. (Eg: All zeros should be zeros non None or N/A, missing values should be N/A etc.). Also need to scale data for each feature using min/max scaler.
- Normalize numerical features using Min-Max scaling
Columns: eg: Monthly Fee, Cashback %, FX Fee, Interest Rate
Use MinMaxScaler from sklearn.preprocessing.
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Convert categorical features -> One-hot encode the Account_Type column using pd.get_dummies.
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Ensure clean and complete data: Handle missing values (fill, drop, or impute), Remove duplicates, validate data types.
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Export or return the cleaned dataset for model use.