Book Image

Beginning Data Science with Python and Jupyter

By : Chris DallaVilla
Book Image

Beginning Data Science with Python and Jupyter

By: Chris DallaVilla

Overview of this book

Getting started with data science doesn’t have to be an uphill battle. This step-by-step video course is ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction. Get to grips with the skills you need for entry-level data science in this hands-on Python and Jupyter course. You’ll learn about some of the most commonly used libraries that are part of the Anaconda distribution, and then explore machine learning models with real datasets to give you the skills and exposure you need for the real world.We'll start with understanding the basics of Jupyter and its standard features. You'll be analyzing an example of a data analytics report. After analyzing a data analytics report, next step is to implement multiple classification algorithms. We’ll then show you how easy it can be to scrape and gather your own data from the open web, so that you can apply your new skills in an actionable context. Finish up by learning to visualize these data interactively. The code bundle for this course is available at https://github.com/TrainingByPackt/Beginning-Data-Science-with-Python-and-Jupyter-eLearning
Table of Contents (3 chapters)
Chapter 3
Web Scraping and Interactive Visualizations
Content Locked
Section 3
Interactive Visualizations
Visualizations are quite useful as a means of extracting information from a dataset. For example, with a bar graph it's very easy to distinguish the value distribution, compared to looking at the values in a table. Of course, as we have seen earlier in this course, they can be used to study patterns in the dataset that would otherwise be quite difficult to identify. They can be further used to help explain a dataset to an unfamiliar party. If included in a blog post, for example, they can boost reader interest levels and be used to break up blocks of text. This video covers: - Visualizations - Interactive Visualization - Pandas DataFrames - Demo on Building and Merging Pandas DataFrames - Data Visualization with Bokeh - Demo on Introduction to Interactive Visualizations with Bokeh - Demo on Exploring Data with Interactive Visualizations