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Data Manipulation with dplyr in R
Arimoro Olayinka Imisioluwa
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
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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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
Coming soon
We're preparing activities for
Data Manipulation with dplyr in R.
These are activities you can do either before, during, or after a course.
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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