O’Reilly – Learning Path: Python for Data Analytics
English | Size: 1.61 GB
Category: Video Training
What is this about?
This is a Learning Path about intermediate-level data analytics tasks that can be performed in Python. It presents a series of practical, hands-on training videos for the novice programmer or data scientist who wants to take their Python skills to the next level and perform data analytics tasks.
Why is it important?
This Learning Path will help bring novice programmers and data scientists to the next level with Python, a scripting language that has become very popular in the data space due to its libraries and ease of use. Learners will receive practical, hands-on training on a range of topics including choosing the correct analytic model for your analytics job; parsing, cleaning and analyzing data using the Python Pandas library; and basic techniques to visualize and present complex data with confidence.
What you’ll learn-and how you can apply it
Common pitfalls of exploratory data analysis, so you can manage, validate, analyze, and present data with confidence.
The basics of importing, exporting, parsing and cleaning data to efficiently manage data projects in Python.
Basics of data visualization, including types of charts, common pitfalls, and best practices in data visualization using various data sources.
How to use matDescriptionlib in the Jupyter Notebook, matDescriptionlib styles, and subDescriptions and small multiples to create customized Descriptions and graphs.
This Learning Path is for you because…
You are a data scientist or programmer with some basic knowledge of Python, matlab, or R, and you need to get productive with Python to do data analytics projects on a single machine, including data validation, data prep, and data visualization and presentation.
Prerequisites:
Some basic knowledge of Python, matlab, or R
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