Python: Effective Data Analysis Using Python – Learning to Effectively Analyze Data Using Python
Data analysis, as we know, is the process taking the source data, refining it to get useful information and then making useful predictions from it.
Python features numerous numerical and mathematical toolkits such as: Numpy, Scipy, Scikit learn and SciKit, all used for data analysis and machine learning. With the help of all of these, Python has become the language of choice for data scientists for data analysis, visualization, and machine learning.
We will have a general look at the data analysis and then discuss the Web scraping tools and techniques in detail. We will show you a rich collection of recipes that will come in handy when you scrub a website using Python, addressing your usual and unusual problems while scraping websites by dipping into the capabilities of Python web scraping tools such as Selenium, BeautifulSoup and urllib2. .
We will then discuss the visualization of best practices. Effective visualization helps you to get better insights from your data and help you make better and more informed business decisions.
After completing this Learning Path, you will be well-equipped to extract data from even dynamic and complex websites using Python web scraping tools, and get a better understanding of the data visualization concepts, how to apply them, and how you can overcome any challenge while implementing them.
Table of Contents:
– Chapter 1: Learning Python Data Analysis
– Chapter 2: Getting Started with Python Web Scraping
– Chapter 3: Python Data Visualization Solutions
Manufacturer: Packt Publishing
Language of instruction: English
Moderator: Manasa Vk – Curator
Level of training: Elementary, Secondary
Time of training: 9 hours +
File size: 2450 MB