| Sumario: | Discover the data analysis capabilities of the Python Pandas software library in this introduction to data wrangling and data analytics. Designed for learners with some core knowledge of Python, you'll explore the basics of importing, exporting, parsing, cleaning, analyzing, and visualizing data. This course is an introduction to Pandas, where you'll learn to filter, group, match, and join data and then move on to advanced functions like analyzing trends and normalizing your data. There is also an introduction to some nifty skills like web scraping, working with API data, fuzzy matching, multiprocessing, and analyzing code performance. Master the basics of Python data wrangling and data analysis Discover the Pandas software library and its use as a data analysis tool Learn to pull data from disparate sources (Excel, CSV, PDF, APIs, etc.) Explore web scraping and how to handle encoding and decoding Understand how to identify and clean data using RegEx and fuzzy matching Sample other data analysis tools like natural language processing and Numpy Learn the data visualization capabilities of Matplotlib and Bokeh Katharine Jarmul runs kjamistan UG, a Python consulting, training and competitive analysis company based in Berlin, Germany. She learned Python in 2008 while working at the Washington Post and is co-author of the O'Reilly title Data Wrangling with Python: Tips and Tools to Make Your Life Easier. Originally from Los Angeles, Jarmul earned an M.A. from American University and an M.S. from Pace University.
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