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Arimoro Olayinka Imisioluwa
Welcome to this project-based course Data Manipulation with dplyr in R. In this project, you will learn how to manipulate data with the dplyr package in R.
Read more
Welcome to this project-based course Data Manipulation with dplyr in R. In this project, you will learn how to manipulate data with the dplyr package in R.
Read more
Welcome to this project-based course Data Manipulation with dplyr in R. In this project, you will learn how to manipulate data with the dplyr package in R.
By the end of this 2-hour long project, you will understand how to use different dplyr verbs such as the select verb, filter verb, arrange verb, mutate verb, summarize verb, and the group_by verb to manipulate the gapminder dataset. Also, you will learn how to combine different dplyr verbs to manipulate the gapminder dataset to get the desired result.
Note, you do not need to be an expert data analyst, data scientist or statistical analyst to be successful in this guided project, just a familiarity with the R language will suffice. If you do not have a prior experience with R, I recommend that you should take the Getting Started with R project before taking this project.
Register for this course and see more details by visiting:
OpenCourser.com/course/sd7x2z/data
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What's inside
Syllabus
Project Overview
Welcome to this project-based course Data Manipulation with dplyr in R. In this project, you will learn how to manipulate data with the dplyr package in R.
By the end of this 2-hour long project, you will understand how to use different dplyr verbs such as the select verb, filter verb, arrange verb, mutate verb, summarize verb, and the group_by verb to manipulate the gapminder dataset. Also, you will learn how to combine different dplyr verbs to manipulate the gapminder dataset to get the desired result.
Note, you do not need to be an expert data analyst, data scientist or statistical analyst to be successful in this guided project, just a familiarity with the R language will suffice. If you do not have a prior experience with R, I recommend that you should take the Getting Started with R project before taking this project.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops beginner skills in data manipulation with dplyr in R
Designed for learners already familiar with the R language
Employs a hands-on approach with practical examples
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Save Data Manipulation with dplyr in R to your list so you can find it easily later:
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Reviews summary
Dplyr mastery class
Learners say that this course is an excellent way to master dplyr for data analysis in R. The instructor is knowledgeable and explains concepts clearly, and the course provides plenty of practice opportunities. Students particularly appreciate the template provided by the instructor, which helps them follow along and apply what they learn. Although one learner had difficulty understanding the instructor's accent, they still found the course to be valuable.
Helpful template provided
"Great at explaining, very useful template to follow up with the instructor!"
Plenty of practice opportunities
"Excellent practice with dplyr, perfect for technical assessments for jr data analysts to practice with."
"My third class with this instructor and I am always happy with what I learn. His explination is easy to understand with plenty of practice."
Knowledgeable and clear instructor
"Excellent instructor!!! You will learn important things quickly!!!"
"Excellent practice with dplyr, perfect for technical assessments for jr data analysts to practice with."
"My third class with this instructor and I am always happy with what I learn."
Instructor's accent may be difficult to understand
"I had a little bit hard time understanding the instructor's accent, but it doesn't affect the knowledge gaining."
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 Data Manipulation with dplyr in R with these
activities:
Read Statistical Rethinking
Show steps
Reinforce your understanding of Bayesian statistics by reading “Statistical Rethinking
View
Statistical Rethinking
on Amazon
Show steps
-
Purchase and read the book “Statistical Rethinking”
-
Complete the exercises and problems in each chapter
-
Discuss and share your insights and questions in a study group or online forum
Join a Study Group
Show steps
Form a study group with peers to discuss course materials, share knowledge, and support each other’s learning
Browse courses on
Collaboration
Show steps
-
Find classmates who share your interests or learning goals
-
Establish regular meeting times and a communication platform
-
Actively participate in discussions, share insights, and work together on assignments
-
Provide feedback and support to your group members
Manipulate data with dplyr in R
Show steps
Practice manipulating data with the dplyr package in R to improve your proficiency
Browse courses on
Data Manipulation
Show steps
-
Set up R and load the necessary libraries
-
Work through online tutorials or exercises on using dplyr
-
Apply the dplyr functions to analyze and manipulate sample datasets
Four other activities
Expand to see all activities and additional details
Show all seven activities
Attend a Data Science Workshop
Show steps
Gain hands-on experience and learn from experts by attending a data science workshop
Browse courses on
Data Science
Show steps
-
Research and find a workshop that aligns with your interests and skill level
-
Apply and register for the workshop
-
Actively participate in the workshop, ask questions, and network with other attendees
Explore Advanced dplyr Techniques
Show steps
Expand your knowledge by exploring advanced techniques in dplyr to enhance your data manipulation skills
Browse courses on
Dplyr
Show steps
-
Find online resources or video tutorials that cover advanced dplyr functions
-
Practice applying these techniques to real-world datasets
-
Experiment with different approaches to optimize your data manipulation pipelines
Data Analysis Portfolio
Show steps
Create a portfolio of data analysis projects to showcase your skills and deepen your understanding
Browse courses on
Data Analysis
Show steps
-
Identify datasets or projects that align with your interests and course topics
-
Plan and execute your data analysis, including data cleaning, exploration, and modeling
-
Prepare a portfolio that visually and clearly presents your findings, insights, and conclusions
Create a Data Visualization Story
Show steps
Develop your communication skills by creating a data visualization that tells a compelling story
Browse courses on
Data Visualization
Show steps
-
Identify a dataset that interests you
-
Explore and analyze the data to identify key insights and trends
-
Choose appropriate visualization techniques to effectively convey your findings
-
Prepare a presentation or write a report that combines your visualization with a clear narrative
Read Statistical Rethinking
Show steps
Reinforce your understanding of Bayesian statistics by reading “Statistical Rethinking
View
Statistical Rethinking
on Amazon
Show steps
Show steps
Show steps
- Purchase and read the book “Statistical Rethinking”
- Complete the exercises and problems in each chapter
- Discuss and share your insights and questions in a study group or online forum
Join a Study Group
Show steps
Form a study group with peers to discuss course materials, share knowledge, and support each other’s learning
Browse courses on
Collaboration
Show steps
Show steps
Show steps
- Find classmates who share your interests or learning goals
- Establish regular meeting times and a communication platform
- Actively participate in discussions, share insights, and work together on assignments
- Provide feedback and support to your group members
Manipulate data with dplyr in R
Show steps
Practice manipulating data with the dplyr package in R to improve your proficiency
Browse courses on
Data Manipulation
Show steps
Show steps
Show steps
- Set up R and load the necessary libraries
- Work through online tutorials or exercises on using dplyr
- Apply the dplyr functions to analyze and manipulate sample datasets
Four other activities
Expand to see all activities and additional details
Show all seven activities
Attend a Data Science Workshop
Show steps
Gain hands-on experience and learn from experts by attending a data science workshop
Browse courses on
Data Science
Show steps
Show steps
Show steps
- Research and find a workshop that aligns with your interests and skill level
- Apply and register for the workshop
- Actively participate in the workshop, ask questions, and network with other attendees
Explore Advanced dplyr Techniques
Show steps
Expand your knowledge by exploring advanced techniques in dplyr to enhance your data manipulation skills
Browse courses on
Dplyr
Show steps
Show steps
Show steps
- Find online resources or video tutorials that cover advanced dplyr functions
- Practice applying these techniques to real-world datasets
- Experiment with different approaches to optimize your data manipulation pipelines
Data Analysis Portfolio
Show steps
Create a portfolio of data analysis projects to showcase your skills and deepen your understanding
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Identify datasets or projects that align with your interests and course topics
- Plan and execute your data analysis, including data cleaning, exploration, and modeling
- Prepare a portfolio that visually and clearly presents your findings, insights, and conclusions
Create a Data Visualization Story
Show steps
Develop your communication skills by creating a data visualization that tells a compelling story
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Identify a dataset that interests you
- Explore and analyze the data to identify key insights and trends
- Choose appropriate visualization techniques to effectively convey your findings
- Prepare a presentation or write a report that combines your visualization with a clear narrative
Career center
Learners who complete Data Manipulation with dplyr in R will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts utilize their knowledge of data manipulation tools and techniques to extract meaningful insights from raw data. This course provides a solid foundation in using the dplyr package in R, which is a powerful tool for data manipulation. By learning how to use dplyr's various verbs, such as select, filter, arrange, mutate, summarize, and group_by, you will gain the skills necessary to effectively clean, transform, and analyze data. These skills are essential for Data Analysts, as they allow them to prepare data for analysis, identify trends and patterns, and communicate their findings to stakeholders.
Data Scientist
Data Scientist
Data Scientists use their expertise in data manipulation and analysis to solve complex business problems. This course provides a valuable introduction to data manipulation with dplyr in R, which is a widely-used tool in the field of data science. By completing this course, you will gain proficiency in using dplyr to perform data cleaning, transformation, and aggregation tasks. These skills are highly sought after by Data Scientists, as they enable them to efficiently extract insights from large and complex datasets.
Statistician
Statistician
Statisticians use their knowledge of data manipulation and analysis to design and conduct statistical studies. This course provides a solid foundation in using dplyr in R, which is a powerful tool for data manipulation and statistical analysis. By learning how to use dplyr's various verbs, you will gain the skills necessary to prepare data for analysis, perform statistical tests, and interpret the results. These skills are essential for Statisticians, as they allow them to conduct rigorous statistical analyses and draw meaningful conclusions from data.
Business Analyst
Business Analyst
Business Analysts use their skills in data manipulation and analysis to identify inefficiencies and opportunities within organizations. This course provides a valuable introduction to data manipulation with dplyr in R, which is a widely-used tool for data analysis in the business world. By completing this course, you will gain proficiency in using dplyr to perform data cleaning, transformation, and aggregation tasks. These skills are highly sought after by Business Analysts, as they enable them to efficiently analyze data and make informed recommendations to improve business outcomes.
Market Researcher
Market Researcher
Market Researchers use their knowledge of data manipulation and analysis to understand consumer behavior and market trends. This course provides a solid foundation in using dplyr in R, which is a powerful tool for data manipulation and analysis in the field of marketing research. By learning how to use dplyr's various verbs, you will gain the skills necessary to prepare data for analysis, perform statistical tests, and interpret the results. These skills are essential for Market Researchers, as they allow them to conduct rigorous market research studies and make informed decisions about marketing strategies.
Financial Analyst
Financial Analyst
Financial Analysts use their skills in data manipulation and analysis to evaluate investment opportunities and make recommendations to clients. This course provides a valuable introduction to data manipulation with dplyr in R, which is a widely-used tool for data analysis in the financial industry. By completing this course, you will gain proficiency in using dplyr to perform data cleaning, transformation, and aggregation tasks. These skills are highly sought after by Financial Analysts, as they enable them to efficiently analyze financial data and make informed investment decisions.
Epidemiologist
Epidemiologist
Epidemiologists use their knowledge of data manipulation and analysis to investigate the causes and spread of diseases. This course provides a solid foundation in using dplyr in R, which is a powerful tool for data manipulation and analysis in the field of epidemiology. By learning how to use dplyr's various verbs, you will gain the skills necessary to prepare data for analysis, perform statistical tests, and interpret the results. These skills are essential for Epidemiologists, as they allow them to conduct rigorous epidemiological studies and make informed recommendations to prevent and control diseases.
Actuary
Actuary
Actuaries use their skills in data manipulation and analysis to assess and manage risk. This course provides a valuable introduction to data manipulation with dplyr in R, which is a widely-used tool for data analysis in the insurance industry. By completing this course, you will gain proficiency in using dplyr to perform data cleaning, transformation, and aggregation tasks. These skills are highly sought after by Actuaries, as they enable them to efficiently analyze insurance data and make informed decisions about risk management.
Software Engineer
Software Engineer
Software Engineers use their knowledge of data manipulation and analysis to develop and maintain software applications. This course may be useful for Software Engineers who are interested in learning how to use dplyr in R to improve the efficiency and effectiveness of their data analysis tasks. By completing this course, you will gain proficiency in using dplyr to perform data cleaning, transformation, and aggregation tasks. These skills can be valuable for Software Engineers who work with data-intensive applications.
Data Engineer
Data Engineer
Data Engineers use their skills in data manipulation and analysis to build and maintain data pipelines. This course may be useful for Data Engineers who are interested in learning how to use dplyr in R to improve the efficiency and effectiveness of their data engineering tasks. By completing this course, you will gain proficiency in using dplyr to perform data cleaning, transformation, and aggregation tasks. These skills can be valuable for Data Engineers who work with large and complex datasets.
Database Administrator
Database Administrator
Database Administrators use their knowledge of data manipulation and analysis to manage and maintain databases. This course may be useful for Database Administrators who are interested in learning how to use dplyr in R to improve the efficiency and effectiveness of their data management tasks. By completing this course, you will gain proficiency in using dplyr to perform data cleaning, transformation, and aggregation tasks. These skills can be valuable for Database Administrators who work with large and complex databases.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use their skills in data manipulation and analysis to develop and implement mathematical models for financial analysis. This course may be useful for Quantitative Analysts who are interested in learning how to use dplyr in R to improve the efficiency and effectiveness of their data analysis tasks. By completing this course, you will gain proficiency in using dplyr to perform data cleaning, transformation, and aggregation tasks. These skills can be valuable for Quantitative Analysts who work with large and complex financial datasets.
Biostatistician
Biostatistician
Biostatisticians use their knowledge of data manipulation and analysis to design and conduct statistical studies in the field of biology. This course may be useful for Biostatisticians who are interested in learning how to use dplyr in R to improve the efficiency and effectiveness of their data analysis tasks. By completing this course, you will gain proficiency in using dplyr to perform data cleaning, transformation, and aggregation tasks. These skills can be valuable for Biostatisticians who work with large and complex biological datasets.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use their skills in data manipulation and analysis to optimize decision-making processes. This course may be useful for Operations Research Analysts who are interested in learning how to use dplyr in R to improve the efficiency and effectiveness of their data analysis tasks. By completing this course, you will gain proficiency in using dplyr to perform data cleaning, transformation, and aggregation tasks. These skills can be valuable for Operations Research Analysts who work with large and complex datasets.
Risk Manager
Risk Manager
Risk Managers use their skills in data manipulation and analysis to assess and manage risk. This course may be useful for Risk Managers who are interested in learning how to use dplyr in R to improve the efficiency and effectiveness of their data analysis tasks. By completing this course, you will gain proficiency in using dplyr to perform data cleaning, transformation, and aggregation tasks. These skills can be valuable for Risk Managers who work with large and complex datasets.
For more career information including salaries, visit:
OpenCourser.com/course/sd7x2z/data
Reading list
We've selected nine books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Data Manipulation with dplyr in R.
Save
Provides a comprehensive overview of the dplyr package in R, which is essential for data manipulation. It covers all the important verbs such as select, filter, arrange, mutate, summarize, and group_by, and provides numerous examples to illustrate their usage. This book valuable reference for anyone who wants to learn data manipulation in R.
Provides a gentle introduction to R programming. It covers all the essential topics such as data structures, control flow, and functions. This book is an excellent resource for beginners who want to learn R.
Save
Provides a gentle introduction to R for beginners. It covers all the essential topics such as data structures, control flow, and functions. This book is an excellent resource for beginners who want to learn R.
Save
Provides a comprehensive overview of advanced R topics such as object-oriented programming, data structures, and high-performance computing. This book is an excellent resource for anyone who wants to learn advanced R programming.
Provides a comprehensive reference for the R language. It covers all the essential topics such as data structures, control flow, and functions. This book is an excellent resource for anyone who wants to learn R.
Save
Provides a gentle introduction to R programming. It covers all the essential topics such as data structures, control flow, and functions. This book is an excellent resource for beginners who want to learn R.
Save
Provides a collection of recipes for common R graphics tasks. It covers a wide range of topics such as data visualization, statistical graphics, and web graphics. This book valuable resource for anyone who wants to learn how to create beautiful graphics in R.
Provides a comprehensive introduction to R for data science. It covers all the essential topics such as data import and export, data cleaning, data visualization, and statistical modeling. This book is an excellent resource for anyone who wants to learn R for data science.
Provides a comprehensive introduction to machine learning with R. It covers all the essential topics such as supervised learning, unsupervised learning, and ensemble learning. This book is an excellent resource for anyone who wants to learn machine learning with R.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/sd7x2z/data
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Effort
2 hours
Level
Introductory
Via
Coursera
Institution
Coursera Project Network
Instructor
Arimoro Olayinka Imisioluwa
Language
English
Good to know
Develops beginner skills in data manipulation with dplyr in R
Designed for learners already familiar with the R language
Employs a hands-on approach with practical examples
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