AuthorLillian Pierson, P.E.
- Why use Python for working with data
- Filtering and selecting data
- Concatenating and transforming data
- Data visualization best practices
- Visualizing data
- Creating a plot
- Creating statistical data graphics
- Performing basic math and linear algebra
- Correlation analysis
- Multivariate analysis
- Data sourcing via web scraping
- Introduction to natural language processing
- Collaborative analytics with Plotly
Skill Level Intermediate
- [Lillian] Have you ever wanted to be able to copy and paste a bunch of data off a website, or just get the gist of all the content without actually having to read through line by line? Then I'm going to show you how to build a web scraper in Python, so you can have that data written off the web for you automatically, and I'm going to introduce you to a Python library that will even automate that text analysis for you. Hi, I'm Lillian Pierson. I'm a data strategist that specializes in training and advising. Let's get going on Python for Data Science.
Python: Data Analysis (2015)with Michele Vallisneri2h 16m Intermediate
Python Statistics Essential Trainingwith Michele Vallisneri2h 58m Intermediate
1. Introduction to the Data Professions
High-level course road map1m 28s
2. Data Preparation Basics
3. Data Visualization 101
4. Practical Data Visualization
5. Basic Math and Statistics
6. Data Sourcing via Web Scraping
7. Collaborative Analytics with Plotly
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