Become a Python Data Analyst: Perform exploratory data analysis and gain insight into scientific computing using Python

Enhance your data analysis and predictive modeling skills using popular Python tools
Key Features

Cover all fundamental libraries for operation and manipulation of Python for data analysis

Implement real-world datasets to perform predictive analytics with Python

Access modern data analysis techniques and detailed code with scikit-learn and SciPy

Book Description
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.
What you will learn

Explore important Python libraries and learn to install Anaconda distribution

Understand the basics of NumPy

Produce informative and useful visualizations for analyzing data

Perform common statistical calculations

Build predictive models and understand the principles of predictive analytics

Who this book is for
Become a Python Data Analyst is for entry-level data analysts, data engineers, and BI professionals who want to make complete use of Python tools for performing efficient data analysis. Prior knowledge of Python programming is necessary to understand the concepts covered in this book
Table of Contents

The Anaconda Distribution and Jupyter Notebook

Vectorizing Operations with Numpy

Pandas: Everyone’s Favorite Data Analysis Library

Visualization and Exploratory Data Analysis

Statistical Computing with Python

Introduction to Predictive Analytics Models