Master Data Analysis with Python - Selecting Subsets of Data
Continue your data analysis journey with Python by mastering the fundamentals of the pandas library
Updated on Nov, 2023
Language - English
Duration -2 hours
Master Data Analysis with Python - Selecting Subsets of Data targets those who want to completely master doing data analysis with pandas. This is the second course in the Master Data Analysis with Python series and provides extremely detailed coverage of how to do any type of subset selection within a pandas Data Frame or Series.
Exercises and a Free Certification Exam
Over 100 exercises with detailed solutions are available for you to practice. Additionally, there is a free challenging certification exam offered for those who want to validate their knowledge gained.
This course is taught by expert instructor Ted Petrou, author of the highly-rated text books Pandas Cookbook and Master Data Analysis with Python. Ted has taught over 1,000 hours of live in-person data science courses that use the pandas library. Pandas is a difficult library to use effectively and is often taught incorrectly with poor practices. Ted is extremely adept at using pandas and is known for developing best practices on how to use the library.
All of the material and exercises are written in Jupyter Notebooks available for you to download. This allows you to read the notes, run the code, and write solutions to the exercises all in a single place.
Become an Expert
This course targets those who have an interest in becoming experts and completely mastering the pandas library for data analysis in a professional environment. This course does not cover all of the pandas library, just a small and fundamental portion of it. If you are looking for a brief introduction of the entire pandas library, this course is not it. It takes many dozens of hours, lots of practice, and rigorous understanding to be successful using pandas for data analysis in a professional environment.
The Master Data Analysis with Python Series
Selecting Subsets of Data is second in the Master Data Analysis with Python series which includes the following sequence of courses:
Intro to Pandas
Selecting Subsets of Data with Pandas
Essential Pandas Commands
Grouping Data with Pandas
Time Series with Pandas
Cleaning Data with Pandas
Joining Data with Pandas
Exploratory Data Analysis
This course assumes no previous pandas experience. The only prerequisite knowledge is to understand the fundamentals of Python.
Who this course is for:
- Those who want to begin a comprehensive path for mastering the pandas library with best practices to analyze data
- Those who want to test their knowledge gained by taking a challenging certification exam
What will you learn in this course:
- Best practices from pandas expert Ted Petrou author of Master Data Analysis with Python
- Select subsets of data from Data Frames with just the brackets, loc, and iloc
- Learn how to simultaneously select rows and columns
- Learn how to filter for specific criteria using Boolean selection
- Learn a more intuitive procedure for filtering data with the query method
- Take a challenging Certification Exam to validate your knowledge gained
What are the prerequisites for this course?
This is the second course of the Master Data Analysis with Python series. You will need to take Master Data Analysis with Python - Intro to Pandas 2022 first.
Check out the detailed breakdown of what’s inside the course
Selecting Subsets of Data from DataFrames with just the brackets
- Intro to Subset Selection 03:14 03:14
- Selecting with Just the Brackets 04:17 04:17
- Exercises 03:21 03:21
Selecting Subsets of Data from DataFrames with loc
Selecting Subsets of Data with iloc
Selecting Subsets of Data from a Series
Boolean Selection Single Conditions
Boolean Selection Multiple Conditions
Boolean Selection More
Filtering with the query Method
I am the author of Pandas Cookbook and Master Data Analysis with Python, highly rated texts on performing real-world data analysis with Pandas.
I am the founder of Dunder Data, a company that teaches the fundamentals of data science and machine learning. I enjoy discovering best practices on how to use and teach data analysis with Python.
I also enjoy creating open-source Python libraries and am author of Dexplot, Bar Chart Race, DataFrame Image, and Jupyter to Medium.
User your certification to make a career change or to advance in your current career. Salaries are among the highest in the world.
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