Pandas for Data Science
This course is part of Programming for Python Data Science: Principles to Practice.
Course Cost
Free course
Beginner
Skill Level
40 Hours
Self-paced lessons
This course teaches how to effectively use Python's Pandas library for data science tasks. Students will learn to clean, sort, and store data using Pandas, understanding when and how to leverage this powerful library. The curriculum covers file operations, data cleaning techniques, and advanced data manipulation methods. By the end, learners will be proficient in using Pandas for various data science projects, preparing them for more complex software development in Python.
What you'll learn
Understand when and how to use Pandas for data science projects
Master file operations and data cleaning techniques in Pandas
Learn to manipulate and optimize data using Pandas best practices
Gain proficiency in working with tabular data using Series and DataFrames
Develop skills in combining datasets from different sources
Understand efficient querying techniques for large datasets
Apply Pandas to real-world data science problems and projects
Prepare for more advanced Python programming in data science
Skills you'll gain
This course includes:
2.3 Hours PreRecorded video
1 quiz,8 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
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There are 4 modules in this course
This course provides a comprehensive introduction to using Pandas for data science in Python. Students will learn how to read and write data from various file formats, clean and manipulate large datasets, and perform advanced data operations. The curriculum covers Pandas Series and DataFrames, indexing and subsetting techniques, handling missing data, and combining datasets from different sources. Practical skills are emphasized through hands-on exercises and programming assignments, preparing students for real-world data science tasks.
Intro to Pandas For Data Science + Strings and I/O
Module 1 · 16 Hours to complete
Module 2: Tabular Data with Pandas
Module 2 · 6 Hours to complete
Module 3: Loading and Cleaning Data
Module 3 · 8 Hours to complete
Module 4: Data Manipulation
Module 4 · 10 Hours to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Programming for Python Data Science: Principles to Practice
Payment options
Financial Aid
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Faculties
These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.
Frequently asked Questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.








