Querying and Converting Data Types in R from Pluralsight

Get started with R and learn how to work with different data types. Understand the most powerful data format, the Data Frame, and learn how to query this format.

Have you ever wanted to learn how R is used to handle the most common data types? The knowledge you will gain here is foundational for any aspiring R programmer. In this course, Querying and Converting Data Types in R, you will develop an understanding of all of these data types and how they are processed, converted, and filtered. First, you will explore general data analysis concepts and take a look at the data frame and its main alternatives. Next, you will learn the major data types in R: numeric, integer, factor, character, boolean, and date and time. Finally, you will discover how these data types are used in a data frame. The query and filtering methods largely depend on the data types available in that data frame. When you are finished with this course, you will have your first set of skills that will be invaluable in your further learning path. In fact, the skills taught here are so important in data science, that most of it can be used in other languages (Python, Matlab) and programs (SPSS).

What's inside

Syllabus

Course Overview

Understanding Dataset Structures and Formats

Selecting and Converting Data Types

Querying and Filtering Data

Course Summary and Further Resources

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Gets to the core of R programming by teaching querying and converting data types in R

Taught by instructors who are recognized for their expertise in this area

Builds essential skills in querying and filtering data, creating a solid base for learners new to R

Covers essential data types like numeric, factor, character, and date and time, providing a firm understanding of the range of data types in R

Skills taught extend beyond R: this course helps you develop skills and knowledge that are generalizable to Python, Matlab, and SPSS, making it applicable across multiple analytics tools and languages

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Querying and Converting Data Types in R with these activities:

Review Basic Probability Concepts

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Refreshes foundational probability knowledge necessary for this course to enhance comprehension of more complex concepts later on.

Browse courses on Probability

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Review the concept of probability and sample spaces.
Go over basic probability rules, such as addition and multiplication rules.
Practice solving probability problems involving simple events.

Connect with an Experienced R Programmer

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Provides access to guidance and support from an expert in the field, enhancing learning outcomes.

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Identify potential mentors through online platforms or professional networks.
Reach out to potential mentors and express your interest in learning more about R data types.
Schedule a meeting or conversation to discuss your learning goals and seek guidance.

Participate in a Study Group on Data Types in R

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Fosters collaborative learning and enhances understanding through discussions and problem-solving with peers.

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Join or organize a study group with classmates.
Discuss concepts related to data types in R, such as their properties and conversion methods.
Work together to solve problems and clarify any misunderstandings.

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Explore Data Manipulation in R using Tidyverse

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Provides practical experience with essential data manipulation techniques in R, enhancing comprehension of the course's data manipulation concepts.

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Follow online tutorials on installing and using the Tidyverse package.
Practice using functions like `filter()`, `select()`, and `mutate()` to manipulate datasets.
Explore examples of data cleaning and transformation using Tidyverse tools.

Create a Cheat Sheet for R Data Types

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Solidifies understanding of data types by requiring the creation of a resource that summarizes their characteristics and conversion methods.

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Compile a table summarizing the different data types in R, their properties, and conversion functions.
Include examples of how to convert data between different types.
Share the cheat sheet with peers or online forums for review and feedback.

Solve Practice Problems on Data Types in R

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Reinforces understanding of different data types in R by providing targeted practice in identifying and converting data types.

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Complete online quizzes or exercises that test your ability to identify different data types in R.
Practice converting data types using functions like `as.numeric()`, `as.character()`, and `as.factor()`.
Work through examples of data manipulation scenarios that involve converting data types.

Build a Data Cleaning Tool using R

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Applies knowledge of data types and manipulation techniques to a practical project, enhancing problem-solving and critical thinking skills.

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Design and plan the data cleaning tool, considering the types of data it will handle and the desired output.
Implement the tool using R functions and data manipulation techniques.
Test and refine the tool using different datasets to ensure accuracy and efficiency.

Attend a Workshop on Advanced Data Manipulation in R

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Provides exposure to advanced data manipulation techniques and best practices, extending the knowledge gained in this course.

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Identify and register for a workshop that focuses on advanced data manipulation in R.
Attend the workshop and actively participate in discussions and exercises.
Apply the techniques learned in the workshop to your own data analysis projects.

Career center

Learners who complete Querying and Converting Data Types in R will develop knowledge and skills that may be useful to these careers:

Statistician

Statisticians use their knowledge of statistics to collect, analyze, interpret, and present data. This course is a great introduction to the basics of data analysis in R. You will learn how to work with different data types, query data, and filter data. This knowledge will be essential for your success as a statistician. In particular, the section covering the data frame and its alternatives will be directly relevant to you in this career.

See salaries and explore the career path for Statistician

Data Analyst

Data analysts use their skills in data analysis to help businesses make better decisions. This course will teach you the basics of data analysis in R, including how to work with different data types, query data, and filter data. This knowledge will be essential for your success as a data analyst. In particular, the section covering the data frame and its alternatives will be directly relevant to you in this career.

See salaries and explore the career path for Data Analyst

Data Scientist

Data scientists use their skills in data analysis and machine learning to help businesses solve complex problems. This course is a great introduction to the basics of data analysis in R, including how to work with different data types, query data, and filter data. This knowledge will be essential for your success as a data scientist.

See salaries and explore the career path for Data Scientist

Health Data Analyst

Health data analysts use their skills in data analysis to improve the quality of healthcare. This course will teach you the basics of data analysis in R, which can be a valuable skill for health data analysts. In particular, the section covering the data frame and its alternatives will be directly relevant to you in this career.

See salaries and explore the career path for Health Data Analyst

Business Analyst

Business analysts use their skills in data analysis to help businesses make better decisions. This course will teach you the basics of data analysis in R, which can be a valuable skill for business analysts. In particular, the section covering the data frame and its alternatives will be directly relevant to you in this career.

See salaries and explore the career path for Business Analyst

Epidemiologist

Epidemiologists use their skills in statistics to study the causes of disease. This course will teach you the basics of data analysis in R, which can be a valuable skill for epidemiologists. In particular, the section covering the data frame and its alternatives will be directly relevant to you in this career.

See salaries and explore the career path for Epidemiologist

Biostatistician

Biostatisticians use their skills in statistics to analyze data in the field of biology. This course will teach you the basics of data analysis in R, which can be a valuable skill for biostatisticians. In particular, the section covering the data frame and its alternatives will be directly relevant to you in this career.

See salaries and explore the career path for Biostatistician

Public Health Analyst

Public health analysts use their skills in data analysis to improve the health of communities. This course will teach you the basics of data analysis in R, which can be a valuable skill for public health analysts. In particular, the section covering the data frame and its alternatives will be directly relevant to you in this career.

See salaries and explore the career path for Public Health Analyst

Quantitative Analyst

Quantitative analysts use their skills in mathematics and statistics to develop mathematical models. This course will teach you the basics of data analysis in R, which can be a valuable skill for quantitative analysts. In particular, the section covering data types may be relevant to your work.

See salaries and explore the career path for Quantitative Analyst

Actuary

Actuaries use their skills in mathematics and statistics to develop financial models. This course will teach you the basics of data analysis in R, which can be a valuable skill for actuaries. In particular, the section covering data types may be relevant to your work.

See salaries and explore the career path for Actuary

Market Researcher

Market researchers use their skills in data analysis to help businesses understand their customers. This course will teach you the basics of data analysis in R, which can be a valuable skill for market researchers. In particular, the section covering data types may be relevant to your work.

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Operations Research Analyst

Operations research analysts use their skills in mathematics and statistics to develop mathematical models for business problems. This course will teach you the basics of data analysis in R, which can be a valuable skill for operations research analysts. In particular, the section covering data types may be relevant to your work.

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Software Engineer

Software engineers use their skills in programming to develop software applications. This course will teach you the basics of data analysis in R, which can be a valuable skill for software engineers. In particular, the section covering data types may be relevant to your work, and R can be a valuable tool for software testing.

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Financial Analyst

Financial analysts use their skills in financial analysis to help businesses make better decisions. This course will teach you the basics of data analysis in R, which can be a valuable skill for financial analysts. In particular, the section covering data types may be relevant to your work.

See salaries and explore the career path for Financial Analyst

Data Engineer

Data engineers use their skills in data management to build and maintain data systems. This course will teach you the basics of data analysis in R, which can be a valuable skill for data engineers. In particular, the section covering data types may be relevant to your work.

See salaries and explore the career path for Data Engineer