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.

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Table of Contents (8 chapters)
Preface
Preface
Who this book is for
What this book covers
To get the most out of this book
Get in touch
Free Chapter
1
The Anaconda Distribution and Jupyter Notebook
The Anaconda Distribution and Jupyter Notebook
The Anaconda distribution
Jupyter Notebook
Using the Jupyter Notebook
Summary
2
Vectorizing Operations with NumPy
Vectorizing Operations with NumPy
Introduction to NumPy
NumPy arrays
Using NumPy for simulations
Summary
3
Pandas - Everyone's Favorite Data Analysis Library
Pandas - Everyone's Favorite Data Analysis Library
Introduction to the pandas library
Operations and manipulations of pandas
Answering simple questions about a dataset
Answering further questions
Summary
4
Visualization and Exploratory Data Analysis
Visualization and Exploratory Data Analysis
Introducing Matplotlib
Introduction to pyplot
Object-oriented interface
Common customizations
EDA with seaborn and pandas
Analyzing variables individually
Relationships between variables
Summary
5
Statistical Computing with Python
Statistical Computing with Python
Introduction to SciPy
Hypothesis testing
Summary
6
Introduction to Predictive Analytics Models
Introduction to Predictive Analytics Models
Predictive analytics and machine learning
Understanding the scikit-learn library
Building a regression model using scikit-learn
Regression model to predict house prices
Summary
7
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The Anaconda distribution

Anaconda is a free, easy-to-install package management and environment management Python distribution created for developers and data scientists to make package management and deployment in scientific computing, data science, statistical analysis, and machine learning an easy task. It is software that is produced and distributed by Continuum Analytics and is available for free download at https://www.anaconda.com/download/.

Anaconda is a toolbox, a ready-to-use collection of related tools for doing data analytics with Python. The individual tools are also available for free download, but it is definitely more convenient to get the whole toolbox. This is the main problem that Anaconda solves, saving you the time it takes to look for every individual tool and install them on your system. In addition, Anaconda also takes care of package dependencies and other potential conflicts and problems that are the outcome of installing Python packages individually.

Installing Anaconda

On opening the previously mentioned URL, we are given download options for each operating system. So, here, you must look for the appropriate installer for your operating system. You will see two installers: one is for Python 3.6 and the other is for Python 2.7. In this book, we will be using Python 3.6:

Let's download the latest version of the Anaconda software and save in our Downloads folder.

Here, we choose the 64-bit installer of Anaconda 5.2 for Windows, since we will be working on a Windows environment in this book. Installation for macOS and Linux will also be similar.

Installing Anaconda is very simple; it is no different from any other software you have installed before. Double-click on the .exe file and install the software on your system. The steps are easy and you'll get the normal prompts you see when installing software:

  1. Click on Next in the first installer dialog box.
  2. Then, we have the license agreement, where we can click on I Agree after going through the terms and conditions of the software.
  3. From the options, select Just Me and click Next.
  4. Select the default installation destination folder and click Next.
  5. Next, it asks you for the environment variables and whether you want to register Anaconda as your default Python. Check both boxes and click on Install.
  6. Once the installation is complete, click on Finish in the installer dialog box.
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