Python is one of the most common and popular languages used by leading data analysts and statisticians for working with massive datasets and complex data visualizations.
Become a Python Data Analyst introduces Python's most essential tools and libraries that you need to work with the data analysis process, right from preparing data to performing simple statistical analyses and creating meaningful data visualizations.
In this book, we will cover Python libraries such as NumPy, pandas, matplotlib, seaborn, SciPy, and scikit-learn, and apply them in practical data analysis and statistics examples. As you make your way through the chapters, you will learn to efficiently use the Jupyter Notebook to operate and manipulate data using the NumPy and pandas libraries. In the concluding chapters, you will gain experience in building simple predictive models, statistical computation and analysis using rich Python tools, and proven data analysis techniques.
By the end of this book, you will have hands-on experience of performing data analysis with Python.
