Python has many libraries that allow us to apply various statistical concepts discussed in the Theory section. Libraries such as Numpy or Pandas can be used to calculate Measures Of Frequency, Central Tendency, and Variability. Matplotlib allows for the creation of various graphs. A variety of libraries are available for Inferential Statistics. The most important is scipy.stats, which allows users to perform different types of t-Tests and F-Tests. This section has a number of Hypothetical datasets to illustrate the use of these libraries. This section also covers Univariate and Bivariate Analysis. It is covered only in the Theory Section of Data Exploration and Preparation.