Technical requirements
We will leverage the pandas, ydata_profiling, dtale, autoviz, sweetviz, matplotlib, and seaborn libraries in Python for this chapter. The code and notebooks for this chapter are available on GitHub at https://github.com/PacktPublishing/Exploratory-Data-Analysis-with-Python-Cookbook.
We will work within a virtual environment to avoid possible conflicts between some existing installations such as Jupyter Notebook and the installation of packages to be used in this chapter. In Python, a virtual environment is an isolated environment that has its own set of installed libraries, dependencies, and configurations. It is created to avoid conflicts between different versions of packages and libraries that are installed on a system. When we create a virtual environment, we can install specific versions of packages and libraries without affecting the global installation on our system.
The following steps and commands can be used to set this up:
- Open the command...
