Question: Complete the below function which takes a frame of features and a list of columns to work on. The function should scale the passed in

Complete the below function which takes a frame of features and

Complete the below function which takes a frame of features and a list of columns to work on. The function should scale the passed in features (using the specified columns) using a sklearn StandardScaler. The function should return a frame with the scaled data instead of the original data (column ordering does not matter). def scale_data(features, columns): Scale numeric columns. Args: features: A pandas DataFrame. columns: A list of column names to scale. Returns: A pandas DataFrame with scaled versions of the specified columns. return Notimplemented print("Scaled Covid-19 features:") scaled_features = scale_data(covid_features,_['titer', 'age', 'height', 'weight', "blood_oxygen']) if (not isinstance(scaled_features, type(Notimplemented))): covid_features = scaled_features scaled_features

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