Looking at basic statistics

In this section, you will start with the first step in statistical analysis by calculating the basic statistics of your dataset. Even though NumPy has limited built-in statistical functions, we can leverage its usage with SciPy. Before we start, let's describe how our analysis will flow. All of the feature columns and label columns are numerical, but you may have noticed that the Charles River dummy variable (CHAS) column has binary values (0,1), which means that it's actually encoded from categorical data. When you analyze your dataset, you can separate your columns into Categorical and Numerical. In order to analyze them all together, one type should be converted to another. If you have a categorical value and you want to convert it into a numeric value, you can do so by converting each category to a numerical value. This process is called...