Data Analysis with RStudio: Understanding the Basics
February 21, 2025
Article
This course is part of Data Analysis with Pandas and Python Specialization
Instructor: Packt - Course Instructors
Included with
(14 reviews)
Recommended experience
Beginner level
This course is for aspiring data analysts and scientists interested in Python and Pandas for data analysis, with no prior programming knowledge.
(14 reviews)
Recommended experience
Beginner level
This course is for aspiring data analysts and scientists interested in Python and Pandas for data analysis, with no prior programming knowledge.
Explain how to navigate and utilize Jupyter Lab for Python programming.
Write Python code, including functions and data structures.
Manipulate and analyze data using Pandas Series and DataFrames.
Apply data cleaning and sorting techniques to prepare datasets for analysis.
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Embark on a comprehensive journey into data analysis with Python and Pandas. Learn to set up Anaconda and Jupyter Lab on macOS and Windows, navigate Jupyter Lab's interface, and execute code cells.
- You'll start by mastering essential Python programming concepts, including data types, operators, variables, functions, and classes. - Then, dive into Pandas to create and manipulate Series and DataFrames. The course covers data importing from sources like CSV, Excel, and SQL databases, along with techniques for sorting, filtering, and data extraction. - Advanced analysis methods, including group-by operations, merging, joining datasets, and pivot tables, are also explored to equip you with the skills for efficient and sophisticated data analysis. Ideal for aspiring data analysts and scientists, no prior programming knowledge is necessary with the included Python crash course.
In this module, we will guide you through the initial setup required for this course, including installing the Anaconda distribution on both macOS and Windows, and creating Python environments using Anaconda Navigator. You'll also learn to unpack the provided course materials, navigate the Jupyter Lab interface, execute code cells, and import necessary libraries to get you started on your data analysis journey.
8 videos2 readings1 assignment
In this module, we will cover the essentials of Python programming, starting with the use of comments to enhance code readability. You'll gain familiarity with Python's basic data types, operators, variables, and built-in functions, laying the groundwork for effective coding. We will delve into custom functions, string methods, lists, indexing and slicing, dictionaries, and classes to build your programming skills. Finally, you will learn to navigate and use Python libraries within Jupyter Lab, a critical skill for data analysis.
12 videos1 assignment
In this module, we will explore the creation and manipulation of Pandas Series objects from different data sources like lists and dictionaries. We will delve into essential methods and attributes of Series, understand the use of parameters and arguments, and learn techniques to import data into Series using 'pd.read_csv'. Additionally, we will cover methods for inspecting, sorting, and extracting Series values, along with advanced operations like broadcasting and applying functions to Series elements.
21 videos1 reading2 assignments
Packt helps tech professionals put software to work by distilling and sharing the working knowledge of their peers. Packt is an established global technical learning content provider, founded in Birmingham, UK, with over twenty years of experience delivering premium, rich content from groundbreaking authors on a wide range of emerging and popular technologies.
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Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.
If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.
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