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

Creating a word cloud

As a data analyst, you need to identify the most frequent words and represent them in graphical form to the top management. A word cloud is used to represent a word-frequency plot. It represents the frequency by the size of the word, that is, the more frequent word looks larger in size and less frequent words looks smaller in size. It is also known as a tag cloud. We can create a word cloud using the wordcloud library in Python. We can install it using the following commands:

pip install wordcloud

Or, alternatively, this one:

conda install -c conda-forge wordcloud

Let's learn how to create a word cloud:

  1. Import libraries and load a stopwords list:
# importing all necessary modules
from wordcloud import WordCloud
from wordcloud import STOPWORDS
import matplotlib.pyplot as plt

stopword_list = set(STOPWORDS)

paragraph="""Taj Mahal is one of the beautiful monuments. It is one of the wonders of the world. It was built by Shah Jahan in 1631 in memory of...