Activity 9.01 – Data splitting, scaling, and modeling

You are charged with analyzing the performance of a combined cycle power plant and are given data on the full-load electrical power production along with environmental variables (such as temperature or humidity). In the first part of the activity, you will split the data manually and with sklearn, then you will scale the data, construct a simple linear model, and output the results:

1. For this activity, all you will need is the Pandas library, the modules from sklearn, and numpy. Load them in the first cell of the notebook.
2. Use the power_plant.csv dataset – 'Datasets\\power_plant.csv'. Read the data into a Pandas DataFrame, print out the shape, and list the first five rows.

The independent variables are as follows:

• AT – ambient temperature
• V – exhaust vacuum level
• AP – ambient pressure
• RH – relative humidity

The dependent variable is...