Book Image

Become a Python Data Analyst

By : Alvaro Fuentes
Book Image

Become a Python Data Analyst

By: Alvaro Fuentes

Overview of this book

Python is one of the most common and popular languages preferred 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 necessary 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 NumPy and the pandas library. In the concluding chapters, you will gain experience in building simple predictive models and carrying out 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 performing data analysis with Python.
Table of Contents (8 chapters)

Relationships between variables

The relationships between different variables can be visualized using the namespace plot from matplotlib. The scatter plot is used for visualizing relationships between two numerical variables, and the box plot is used for visualizing relationships between one numerical variable and one categorical variable. The complex conditional plot will be used to visualize many variables in a single visualization.

Scatter plot

To produce a scatter plot with pandas, all you have to do is to use the plot namespace. Within the plot namespace, you have a scatter() method and pass an x value and a y value:

We see here that we have a positive relationship between the 1stFlrSF of the house and the SalePrice...