In this course, you will be introduced to the DataFrame and the Series, the two primary containers of data within pandas. You will learn the components of these objects and a few basic operations and also know what subset selection methods you should
In this course, you will be introduced to the DataFrame and the Series, the two primary containers of data within pandas. You will learn the components of these objects and a few basic operations and also know what methods of subset selection you should avoid. You will begin performing calculations on your data. You will begin by learning how to operate on a single column of data, a pandas Series and learn the difference between methods that aggregate (return a single value) and those that do not. After learning how to operate on a single column of data, you'll learn how to operate on multiple columns at the same time by calling methods on a DataFrame. You'll learn how to change the direction of the operations from vertical to horizontal.You'll also learn about the categorical data type, which is unique to pandas and has the ability to save a tremendous amount of memory. Up to this point in the course, all operations were applied to the entire dataset. You will learn how to apply operations to independent groups within your data instead of the whole. You will also learn how to display the results of grouping in a more human-readable way with pivot tables.Grouping data can be tricky in pandas and potentially be one of the slowest performing operations. You will learn best practices on how to optimize performance along with the newest syntax available.
Skills You Will Gain
Data Analysis
Data Science
Pandas
Pandas DataFrame
Python
Learning Outcomes (At the end of this program you will be able to)
Introduction to the pandas DataFrame and Series
Understanding the different data types available within a DataFrame
Accessing the DataFrame components – the index, columns, and values
Setting a meaningful index in a DataFrame
Completing a five-step process for data exploration
Learn how to select rows and columns simultaneously
Learn how to filter for specific criteria using the boolean selection
Learn a more intuitive procedure for filtering data with the query method
Select subsets of data from DataFrames with just the brackets, loc, and iloc
Prerequisites
It is necessary to understand the fundamentals of the Python programming language.
No prior experience with pandas is needed.
Who Should Attend
Anyone, who wants to learn about fundamental concepts of programming.
Anyone, who wants to learn python programming language.
Anyone, who wants to brush up on their programming and python skills.
Curriculum
Instructors
Frequently Asked Questions
How much do the courses at Starweaver cost?
We offer flexible payment options to make learning accessible for everyone. With our Pay-As-You-Go plan, you can pay for each course individually. Alternatively, our Subscription-Based plan provides you with unlimited access to all courses for a monthly or yearly fee.
Do you offer any certifications upon completion of a course at Starweaver?
Yes, we do offer a certification upon completion of our course to showcase your newly acquired skills and expertise.
Does Starweaver offer any free courses or trials?
No, we don't offer any free courses, but we do offer 5-day trial only on our subscriptions-based plans.
Are Starweaver's courses designed for beginners or advanced students?
Our course is designed with three levels to cater to your learning needs - Core, Intermediate, and Advanced. You can choose the level that best suits your knowledge and skillset to enhance your learning experience.
What payment options are available for Starweaver courses?
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Do you offer refunds?
Yes, we do offer a 100% refund guarantee for our courses within a specified time frame. If you are not satisfied with the course, contact our customer support team to request a refund with your order details. Some restrictions may apply.
*Where courses have been offered multiple times, the “# Students” includes all students who have enrolled. The “%Recommended” shown is also based on this data.
Theodore Petrou
As the founder of Dunder Data, I have dedicated my career to advancing the field of data science and machine learning. My passion for education and expertise in Python programming are reflected in my comprehensive corporate training programs and the influential books I have authored, including Master Data Analysis with Python, Master Machine Learning with Python, Master the Fundamentals of Python, and Pandas Cookbook. Through Dunder Data, I have had the privilege of delivering tailored training to prestigious organizations such as Microsoft, NASA, and the Federal Reserve, and have empowered thousands of students with practical, hands-on knowledge in data science.
With a solid background in both industry and academia, I bring a wealth of experience to the classroom. My journey includes roles as a Quantitative Developer, Lead Data Scientist, and Credit Risk Professional, where I tackled complex problems from predictive modeling to financial analytics. My work has not only focused on developing innovative solutions but also on teaching and mentoring, fostering a deep understanding of data science principles and applications.
In addition to my professional endeavors, my teaching extends to a wide audience through various platforms. I have taught live courses and workshops, providing in-depth insights into Python programming and data science methodologies. My goal is to make sophisticated concepts accessible and engaging, guiding learners through the intricacies of data analysis and machine learning with clarity and enthusiasm.
