Book Image

Python Data Analysis - Third Edition

By : Avinash Navlani, Ivan Idris
5 (1)
Book Image

Python Data Analysis - Third Edition

5 (1)
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)
Section 1: Foundation for Data Analysis
Section 2: Exploratory Data Analysis and Data Cleaning
Section 3: Deep Dive into Machine Learning
Section 4: NLP, Image Analytics, and Parallel Computing

Installing NLTK and SpaCy

NLTK is one of the popular and essential Python packages for natural language processing. It offers all the basic, as well as advanced, NLP operations. It comprises common algorithms such as tokenization, stemming, lemmatization, part-of-speech, and named entity recognition. The main features of the NLTK library are that it's open-source, easy to learn, easy to use, has a prominent community, and has well-organized documentation. The NLTK library can be installed using the pip install command running on the command line as follows:

pip install nltk

NLTK is not a pre-installed library in Anaconda. We can directly install nltk in the Jupyter Notebook. We can use an exclamation point (!) before the command in the cell:

!pip install nltk

SpaCy is another essential and powerful Python package for NLP. It offers a common NLP algorithm as well as advanced functionalities. It is designed for production purposes and develops applications for a large volume of data...