Categorical Data in the Tidyverse

Engineering and Technology

Short Description

Get ready to categorize! In this course, you will work with non-numerical data, such as job titles or survey responses, using the Tidyverse landscape.

Long Description

In the field of data science, it is common to encounter non-numerical data such as job titles, survey responses, or demographic information. To effectively handle this type of data, R offers a specialized representation known as factors. This course focuses on mastering the manipulation of factors using the tidyverse package forcats. Additionally, we will explore other essential tidyverse packages including ggplot2, dplyr, stringr, and tidyr. Real-world datasets such as the fivethirtyeight flight dataset and Kaggle's State of Data Science and ML Survey will be utilized throughout the course. By the end, you will have the skills to identify and manipulate factor variables, efficiently visualize your data, and effectively communicate your findings. Prepare yourself for an in-depth exploration of data categorization.

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Course Details

Duration: 4 hours
Format: Short Course
Price: USD39.00
Course Link

DataCamp

DataCamp is an online learning platform that offers interactive courses and tutorials for data science and analytics. It provides a wide range of courses covering topics such as Python, R, SQL, machine learning, data visualization, and more. The platform offers a hands-on learning experience through coding exercises and projects, allowing users to practice and apply their skills in real-world scenarios. DataCamp also offers a personalized learning experience with adaptive learning technology that adjusts the course content based on the user's skill level and progress. It is widely used by individuals, professionals, and organizations to enhance their data science skills and stay up-to-date with the latest trends and technologies in the field.

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