Joining Data in R using dplyr from Coursera

In this course, you will learn practical ways for data manipulation in R. We will talk about different join operations and spend a great deal of our time here joining the sales and customers data sets using the dplyr package. By the end of this 2-hour-long project, you will perform inner join, full (outer) join, right join, left join, cross join, semi join, and anti join using the merge() and dplyr functions.

This project-based course is an intermediate-level course in R. Therefore, to get the most of this project, it is essential to have prior experience using R for basic analysis. I recommend that you complete the project titled: "Data Manipulation with dplyr in R" before you take this current project.

What's inside

Syllabus

Project Overview

You will need to join or merge two or more data sets at different points in your work as a data enthusiast. The dplyr package offers very sophisticated functions to help you achieve the join operation you desire. This project-based course, "Joining Data in R using dplyr" is for R users willing to advance their knowledge and skills. In this course, you will learn practical ways for data manipulation in R. We will talk about different join operations and spend a great deal of our time here joining the sales and customers data sets using the dplyr package. By the end of this 2-hour-long project, you will perform inner join, full (outer) join, right join, left join, cross join, semi join, and anti join using the merge() and dplyr functions. This project-based course is an intermediate-level course in R. Therefore, to get the most of this project, it is essential to have prior experience with using R for basic analysis. I recommend that you should complete the project titled: "Data Manipulation with dplyr in R" before you take this current project.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

This intermediate-level course in R is suitable for users wishing to advance their knowledge and skills with the dplyr package for data manipulation in R

Suitable for those wanting to join or merge two or more data sets using the dplyr package

Covers various join operations such as inner join, full (outer) join, right join, left join, cross join, semi join, and anti join

Prior experience using R for basic analysis is recommended to fully benefit from the project

Career center

Learners who complete Joining Data in R using dplyr will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts collect, analyze, interpret, and present data in order to help companies make informed decisions. This course on Joining Data in R using dplyr can help Data Analysts develop the skills they need to effectively combine and analyze data from multiple sources, which is a key part of their role.

See salaries and explore the career path for Data Analyst

Business Analyst

Business Analysts use data to identify and solve business problems. This course on Joining Data in R using dplyr can help Business Analysts develop the skills they need to effectively analyze data from multiple sources, which is a key part of their role.

See salaries and explore the career path for Business Analyst

Data Scientist

Data Scientists use data to build models and predict future outcomes. This course on Joining Data in R using dplyr can help Data Scientists develop the skills they need to effectively combine and analyze data from multiple sources, which is a key part of their role.

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Statistician

Statisticians use data to draw conclusions about the world around us. This course on Joining Data in R using dplyr can help Statisticians develop the skills they need to effectively analyze data from multiple sources, which is a key part of their role.

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Operations Research Analyst

Operations Research Analysts use data to improve the efficiency of organizations. This course on Joining Data in R using dplyr can help Operations Research Analysts develop the skills they need to effectively analyze data from multiple sources, which is a key part of their role.

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Financial Analyst

Financial Analysts use data to make investment decisions. This course on Joining Data in R using dplyr can help Financial Analysts develop the skills they need to effectively analyze data from multiple sources, which is a key part of their role.

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Risk Analyst

Risk Analysts use data to identify and mitigate risks. This course on Joining Data in R using dplyr can help Risk Analysts develop the skills they need to effectively analyze data from multiple sources, which is a key part of their role.

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Market Researcher

Market Researchers use data to understand consumer behavior. This course on Joining Data in R using dplyr can help Market Researchers develop the skills they need to effectively analyze data from multiple sources, which is a key part of their role.

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Data Visualization Analyst

Data Visualization Analysts create visual representations of data. This course on Joining Data in R using dplyr can help Data Visualization Analysts develop the skills they need to effectively analyze data from multiple sources, which is a key part of their role.

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Machine Learning Engineer

Machine Learning Engineers build and maintain machine learning models. This course on Joining Data in R using dplyr can help Machine Learning Engineers develop the skills they need to effectively analyze data from multiple sources, which is a key part of their role.

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Software Engineer

Software Engineers design, develop, and maintain software systems. This course on Joining Data in R using dplyr can help Software Engineers develop the skills they need to effectively analyze data from multiple sources, which is a key part of their role.

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Database Administrator

Database Administrators manage and maintain databases. This course on Joining Data in R using dplyr can help Database Administrators develop the skills they need to effectively analyze data from multiple sources, which is a key part of their role.

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Information Security Analyst

Information Security Analysts protect computer systems and networks from unauthorized access. This course on Joining Data in R using dplyr can help Information Security Analysts develop the skills they need to effectively analyze data from multiple sources, which is a key part of their role.

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Data Engineer

Data Engineers build and maintain the infrastructure that is used to store and process data. This course on Joining Data in R using dplyr can help Data Engineers develop the skills they need to effectively combine and analyze data from multiple sources, which is a key part of their role.

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User Experience Researcher

User Experience Researchers study how users interact with products and services. This course on Joining Data in R using dplyr can help User Experience Researchers develop the skills they need to effectively analyze data from multiple sources, which is a key part of their role.

See salaries and explore the career path for User Experience Researcher