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Python Data Analysis

Python Data Analysis - Third Edition

By : Avinash Navlani, Ivan Idris
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Python Data Analysis

Python Data Analysis

By: Avinash Navlani, Ivan Idris

Overview of this book

Data analysis enables you to generate value from small and big data by discovering new patterns and trends, and Python is one of the most popular tools for analyzing a wide variety of data. With this book, you’ll get up and running using Python for data analysis by exploring the different phases and methodologies used in data analysis and learning how to use modern libraries from the Python ecosystem to create efficient data pipelines. Starting with the essential statistical and data analysis fundamentals using Python, you’ll perform complex data analysis and modeling, data manipulation, data cleaning, and data visualization using easy-to-follow examples. You’ll then understand how to conduct time series analysis and signal processing using ARMA models. As you advance, you’ll get to grips with smart processing and data analytics using machine learning algorithms such as regression, classification, Principal Component Analysis (PCA), and clustering. In the concluding chapters, you’ll work on real-world examples to analyze textual and image data using natural language processing (NLP) and image analytics techniques, respectively. Finally, the book will demonstrate parallel computing using Dask. By the end of this data analysis book, you’ll be equipped with the skills you need to prepare data for analysis and create meaningful data visualizations for forecasting values from data.
Table of Contents (20 chapters)
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1
Section 1: Foundation for Data Analysis
6
Section 2: Exploratory Data Analysis and Data Cleaning
11
Section 3: Deep Dive into Machine Learning
15
Section 4: NLP, Image Analytics, and Parallel Computing

Software used in this book

Let's discuss the software that will be used in this book. In this book, we are going to use Anaconda IDE to analyze data. Before installing it, let's understand what Anaconda is.

A Python program can easily run on any system that has it installed. We can write a program on a Notepad and run it on the command prompt. We can also write and run Python programs on different IDEs, such as Jupyter Notebook, Spyder, and PyCharm. Anaconda is a freely available open source package containing various data manipulation IDEs and several packages such as NumPy, SciPy, Pandas, Scikit-learn, and so on for data analysis purposes. Anaconda can easily be downloaded and installed, as follows:

  1. Download the installer from https://www.anaconda.com/distribution/.
  2. Select the operating system that you are using.
  3. From the Python 3.7 section, select the 32-bit or 64-bit installer option and start downloading.
  4. Run the installer by double-clicking on it.
  5. Once the installation is complete, check your program in the Start menu or search for Anaconda in the Start menu.

Anaconda also has an Anaconda Navigator, which is a desktop GUI application that can be used to launch applications such as Jupyter Notebook, Spyder, Rstudio, Visual Studio Code, and JupyterLab:

Now, let's look at IPython, a shell-based computing environment for data analysis.

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Python Data Analysis
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