Pandas Basics and GroupBy: Intro to Python Data Science
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 3.5 hours | Size: 1.19 GB
What you'll learn
Learn the Basics of Python´s most powerful Data Science Library Pandas
Learn how to import, inspect, analyze and visualize Data with Pandas
Understand the Power of Groupby Operations
Master and apply GroupBy Operations on your Data.
Learn how to work with real Datasets
Test your skills with Coding Exercises and Quizzes
Requirements
Ideally some basic programming experience (not necessarily Python)
Description
Make your first steps with Pandas and become a successful Data Scientist!
The powerful Pandas Library makes Python to the language of choice for Data Scientists, Researchers and Finance Professionals.
More and more Data Projects are switched from Excel to Python/Pandas.
These groups typically spend more than 50% of their day-to-day work with importing, manipulating and analysing Data with Pandas.
The first part of this course is meant to be a gentle introduction into Pandas. It shows you all steps to get familiar and comfortable with Pandas. From Installing the Python Environment, to importing your first Dataset into Pandas until more advanced visualizations, everything is explained!
In the second part of this course we dive deep into GroupBy operations, one of the most powerful and exciting tools in Pandas. Here you will also learn and master more advanced and more complex concepts that will improve your day-to-day work with Pandas significantly!
Throughout the course we are working with real Datasets and real tasks and challenges. (Titanic Passengers and Summer Olympics Medals from 1896 until till today)
And, last but not least, you will be able to test and apply your new skills with Quizzes and instructed and interactive Coding Exercises.
Who this course is for:
Data Science Beginners
Intermediate Data Scientists who want to really understand and master GroupBy Operations in Pandas
Everyone who want to switch Data Projects from Excel to more powerful tools.
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