Python Data Analysis
Master Python data analysis: Learn to process tabular data, work with CSV files, and organize complex datasets.
Master Python data analysis: Learn to process tabular data, work with CSV files, and organize complex datasets.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Introduction to Scripting in Python Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.7
(884 ratings)
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English
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What you'll learn
Master Python dictionary operations and data structures
Process and analyze tabular data efficiently
Work with CSV files for data import and export
Organize and sort complex datasets
Apply data analysis techniques to real-world problems
Skills you'll gain
This course includes:
3.22 Hours PreRecorded video
2 assignments
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FullTime access
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There are 4 modules in this course
This comprehensive Python course focuses on data analysis fundamentals. Students learn to work with dictionaries, process tabular data, and handle CSV files effectively. The curriculum covers advanced topics like nested data structures, data sorting, and practical analysis of real-world datasets. Through hands-on projects including baseball data analysis, learners develop essential skills in organizing and analyzing complex data structures.
Dictionaries
Module 1 · 1 Hours to complete
Tabular Data and Nested Data Structures
Module 2 · 1 Hours to complete
Tabular Data and CSV Files
Module 3 · 3 Hours to complete
Organizing Data
Module 4 · 2 Hours to complete
Fee Structure
Instructors
Professor and Researcher
Scott Rixner is a Professor of Computer Science at Rice University, where his research primarily focuses on virtualization, operating systems, and computer architecture. He is particularly interested in memory systems and networking, exploring the intersection of hardware and software to enhance system performance. Rixner has developed Python interpreters for various platforms, including embedded systems and web browsers, and holds 11 patents related to his work, which has been integrated into several open-source projects.In addition to his research, Rixner plays a significant role in curriculum development at Rice University, having chaired committees for both the Department of Computer Science and the School of Engineering. He is also involved in leading the MCS@Rice and MDS@Rice online degree programs. Rixner earned his Ph.D. in Electrical Engineering from MIT in 2001, following a Master’s and Bachelor’s degree in Computer Science and Electrical Engineering from the same institution in 1995.
Innovator in Computer Graphics and Game Design
Joe Warren is a Professor in the Department of Computer Science at Rice University, where he specializes in computer graphics and geometric modeling. He has made significant contributions to the field, authoring the book Subdivision Methods for Geometric Design and publishing extensively on various topics within computer graphics. Warren has a strong passion for computer gaming, both as a player and an educator; he has taught courses on game creation and design for over a decade, collaborating with industry professionals in Houston. An alumnus of Rice University, he completed his undergraduate studies there before earning his Ph.D. from Cornell University in 1986. Since then, he has been a dedicated faculty member at Rice, serving as the Chair of the Department from 2008 to 2013.
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4.7 course rating
884 ratings
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