For data to be useful and meaningful, it must be curated and refined. This Data Wrangling with Python course teaches you the core ideas behind these processes and equips you with knowledge of the most popular tools and techniques in the domain.
The course starts with the absolute basics of Python, focusing mainly on data structures. It then delves into the fundamental tools of data wrangling like NumPy and Pandas libraries. You'll explore useful insights into why you should stay away from traditional ways of data cleaning, as done in other languages, and take advantage of the specialized pre-built routines in Python. This combination of Python tips and tricks will also demonstrate how to use the same Python backend and extract/transform data from an array of sources including the Internet, large database vaults, and Excel financial tables. To help you prepare for more challenging scenarios, you'll cover how to handle missing or wrong data, and reformat it based on the requirements from the downstream analytics tool. This data wrangling course will further help you grasp concepts through real-world examples and datasets.
You Will Learn How To:
- Use a diverse array of sources to extract data.
- Clean, transform and format data efficiently.
- Use python tricks to transform data into useful and meaningful data sets.
-
Who Should Attend
Data Wrangling with Python takes a practical approach to equip beginners with the most essential data analysis tools in the shortest possible time. It contains multiple activities that use real-life business scenarios for you to practice and apply your new skills in a highly relevant context.