Your Next Skill: SQL and Python for statistics and data analysis
Thanks for using Your Next Skill to find resources for learning to use Python and SQL for statistics and data analysis. Below are several different resources--ebooks, online classes, and iOS app downloads--which I think may help you learn data analysis with Python and SQL.
Foundations for Analytics With Python
Part of the Library’s Safari Tech Books collection of ebooks, this book can help you brush up on your Python skills, specifically in relation to data analysis. Also included are examples of the complete Python code needed to perform specific data analysis tasks.\n\nTo access any book in Safari Tech Books, click on “View this electronic item in Safari Tech Books” from the catalog record and enter your library card number and PIN.
Format: eBook - 2016 First editionView Foundations for Analytics With Python
Learn Data Analysis With Python: Lessons in Coding
A practical workbook intended to be useful for learners with a variety of Python experience. Those already using Python for data analysis can scan the table of contents to find new information to improve their skills. Beginners can work their way through all the exercises to learn how to use Python for data analysis.
Format: eBook - 2018View Learn Data Analysis With Python: Lessons in Coding
This book may be more appropriate for folks with less experience than you. However, I’ve included it here because it contains two chapters you might find useful as a quick primer: Chapter 14: Using Python for Data Science and Chapter 16: Using SQL in Data Science.
Format: eBook - 2017 Second editionView Data Science
Learn to Code with Python on the App Store
This free iOS app uses games and challenges to help you learn Python. Although it is not specifically geared toward statistics and data analysis, this app can be a fun way to learn elements of Python and connect to a community of Python learners.
Format: -View Learn to Code with Python on the App Store
Learn SQL on the App Store
Like the Learn to Code with Python app, this free app seeks to make learning SQL fun through games, challenges, and connections to other SQL learners.
Format: -View Learn SQL on the App Store
SQL for Statistics Essential Training
The Seattle Public Library offers patrons free access to Lynda.com’s entire library of streaming courses. Use your library card number and PIN to log in to Lynda.com at https://www.lynda.com/portal/sip?org=spl.org.\n\nThis 50 minute course “provides an overview of basic descriptive statistics and the SQL commands you need to know to summarize data sets, find averages, and calculate variance and standard deviation.” You can either watch the entire course, or check out the table of contents to only view the video section most relevant to you.\n\nYou may also be interested in the Advanced SQL for Data Scientists course, led by the same instructor.\n
Format: -View SQL for Statistics Essential Training
Python Statistics Essential Training
Another Lynda.com tutorial, this 3 hour course “covers several major skills: cleaning, visualizing, and describing data, statistical inference, and statistical modeling.” You may also be interested in the 6 hour Python for Data Science Essential Training or the Python: Data Analysis courses.
Format: -View Python Statistics Essential Training
Probability and Statistics in Data Science using Python
If you really want to dig into Python and data analysis, you may want to try this self-paced, 10 week online course. The course is free (unless you want to pay for a verified certificate) and is taught by professors from The University of California, San Diego. In this course “you will learn the foundations of probability and statistics. You will learn both the mathematical theory, and get a hands-on experience of applying this theory to actual data using Jupyter notebooks.”\n\nVisit https://www.edx.org/course/subject/data-analysis-statistics for a list of all the data analysis and statistic courses available via edX.\n"
Format: -View Probability and Statistics in Data Science using Python