Assume you are data analyst. You visited one of the car showrooms in the city to...

 

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Assume you are data analyst. You visited one of the car showrooms in the city to purchase a car. You requested the sales manager the vehicles mileage values and the corresponding speeds data. The sales manager provided the data like Mileages = (41, 43, 39, 48, , 29, 43, , 42, 33, 39, 50} Speed = { 52, , 48, 38, 49, 36, 36, 38, 41, 59, , 42 } You identified some discrepancies in the provided data. To smooth the data for predictions, perform the following operations on the above data. a) Fill the missing values with mean in 'Mileages' and smooth the resultant data with bin depth of 4 using various binning methods and illustrate the steps [6M] b) Fill the missing values with median in 'speed' and apply min-max normalization in the range [1,10] and illustrate the steps [6M] Assume you are data analyst. You visited one of the car showrooms in the city to purchase a car. You requested the sales manager the vehicles mileage values and the corresponding speeds data. The sales manager provided the data like Mileages = (41, 43, 39, 48, , 29, 43, , 42, 33, 39, 50} Speed = { 52, , 48, 38, 49, 36, 36, 38, 41, 59, , 42 } You identified some discrepancies in the provided data. To smooth the data for predictions, perform the following operations on the above data. a) Fill the missing values with mean in 'Mileages' and smooth the resultant data with bin depth of 4 using various binning methods and illustrate the steps [6M] b) Fill the missing values with median in 'speed' and apply min-max normalization in the range [1,10] and illustrate the steps [6M]