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To effectively analyze and manipulate data, it is important to have the ability to access data stored in various formats. In this course, Importing Common Data File Formats: R Playbook, you will gain the ability to import data from various sources into R....
Read more
To effectively analyze and manipulate data, it is important to have the ability to access data stored in various formats. In this course, Importing Common Data File Formats: R Playbook, you will gain the ability to import data from various sources into R....
Read more
To effectively analyze and manipulate data, it is important to have the ability to access data stored in various formats. In this course, Importing Common Data File Formats: R Playbook, you will gain the ability to import data from various sources into R. First, you will learn how to import data from CSV and delimited text files. Next, you will discover how to import and format data from Microsoft Excel. Then, you will explore how to import data from specialized statistical applications, including SAS, Stata, and Minitab. Finally, you'll learn about the ability to create, save, and reuse objects in R itself. When you are finished with this course, you will have the knowledge of base R functions and various packages to easily work with data from a variety of sources.
Register for this course and see more details by visiting:
OpenCourser.com/course/xc29sg/importing
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Covers foundational principles, which is suitable for beginners
Introduces essential skills and frameworks widely used in industry
Taught by instructors who are recognized experts in the field
Provides a comprehensive overview of data manipulation and analysis in R
May require additional prerequisite knowledge in data analysis or statistics
Exercises and assignments may be limited, so additional practice is recommended
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Career center
Learners who complete Importing Common Data File Formats: R Playbook will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to help organizations make informed decisions. This course can help Data Analysts by providing them with the skills to import data from a variety of sources, including CSV, delimited text, Microsoft Excel, SAS, Stata, and Minitab. This is especially important for Data Analysts who work with data from multiple sources, as it allows them to easily combine and analyze data from different formats.
Data Scientist
Data Scientist
Data Scientists use data to solve business problems and make predictions. This course can help Data Scientists by providing them with the skills to import data from a variety of sources, including CSV, delimited text, Microsoft Excel, SAS, Stata, and Minitab. This is especially important for Data Scientists who work with data from multiple sources, as it allows them to easily combine and analyze data from different formats.
Statistician
Statistician
Statisticians collect, analyze, interpret, and present data. This course can help Statisticians by providing them with the skills to import data from a variety of sources, including CSV, delimited text, Microsoft Excel, SAS, Stata, and Minitab. This is especially important for Statisticians who work with data from multiple sources, as it allows them to easily combine and analyze data from different formats.
Business Analyst
Business Analyst
Business Analysts use data to identify and solve business problems. This course can help Business Analysts by providing them with the skills to import data from a variety of sources, including CSV, delimited text, Microsoft Excel, SAS, Stata, and Minitab. This is especially important for Business Analysts who work with data from multiple sources, as it allows them to easily combine and analyze data from different formats.
Market Researcher
Market Researcher
Market Researchers collect, analyze, and interpret data to understand consumer behavior. This course can help Market Researchers by providing them with the skills to import data from a variety of sources, including CSV, delimited text, Microsoft Excel, SAS, Stata, and Minitab. This is especially important for Market Researchers who work with data from multiple sources, as it allows them to easily combine and analyze data from different formats.
Financial Analyst
Financial Analyst
Financial Analysts use data to analyze financial performance and make investment recommendations. This course can help Financial Analysts by providing them with the skills to import data from a variety of sources, including CSV, delimited text, Microsoft Excel, SAS, Stata, and Minitab. This is especially important for Financial Analysts who work with data from multiple sources, as it allows them to easily combine and analyze data from different formats.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use data to improve the efficiency of operations. This course can help Operations Research Analysts by providing them with the skills to import data from a variety of sources, including CSV, delimited text, Microsoft Excel, SAS, Stata, and Minitab. This is especially important for Operations Research Analysts who work with data from multiple sources, as it allows them to easily combine and analyze data from different formats.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data pipelines. This course can help Data Engineers by providing them with the skills to import data from a variety of sources, including CSV, delimited text, Microsoft Excel, SAS, Stata, and Minitab. This is especially important for Data Engineers who work with data from multiple sources, as it allows them to easily combine and analyze data from different formats.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. This course may be useful for Software Engineers who work with data from a variety of sources, as it can help them to import data from different formats into their applications.
Database Administrator
Database Administrator
Database Administrators manage and maintain databases. This course may be useful for Database Administrators who need to import data from a variety of sources into their databases.
Web Developer
Web Developer
Web Developers design and develop websites. This course may be useful for Web Developers who need to import data from a variety of sources into their websites.
Mobile Developer
Mobile Developer
Mobile Developers design and develop mobile applications. This course may be useful for Mobile Developers who need to import data from a variety of sources into their mobile applications.
Product Manager
Product Manager
Product Managers manage the development and launch of new products. This course may be useful for Product Managers who need to import data from a variety of sources to inform their product decisions.
Consultant
Consultant
Consultants provide advice and guidance to organizations on a variety of topics. This course may be useful for Consultants who need to import data from a variety of sources to support their consulting projects.
Teacher
Teacher
Teachers teach students at all levels of education. This course may be useful for Teachers who need to import data from a variety of sources to support their teaching materials.
For more career information including salaries, visit:
OpenCourser.com/course/xc29sg/importing
Reading list
We've selected ten 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
Importing Common Data File Formats: R Playbook.
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Provides a comprehensive guide to advanced R programming techniques, covering a wide range of topics, including object-oriented programming, data wrangling, and statistical modeling.
Provides a comprehensive guide to data manipulation in R, covering a wide range of topics, including data import, cleaning, transformation, and reshaping.
Save
Provides a collection of recipes for common data manipulation and analysis tasks in R. It covers a wide range of topics, including data import, cleaning, transformation, and visualization.
Provides a comprehensive guide to machine learning with R, covering a wide range of topics, including supervised learning, unsupervised learning, and model evaluation.
Save
Provides a comprehensive introduction to the R programming language, with a focus on data science applications. It covers a wide range of topics, including data import, manipulation, visualization, and modeling.
Provides a detailed and comprehensive guide to the R programming language, with a focus on practical applications. It covers a wide range of topics, including data import, manipulation, visualization, and modeling.
Provides a practical introduction to the R programming language, with a focus on data analysis and visualization. It covers a wide range of topics, including data import, cleaning, transformation, and modeling.
Provides a comprehensive guide to the RStudio integrated development environment (IDE). It covers a wide range of topics, including the RStudio interface, package management, and debugging.
Save
Provides a collection of recipes for creating various types of graphs and plots in R. It covers a wide range of topics, including basic plots, advanced plots, and interactive plots.
Save
Provides a gentle introduction to the R programming language, with a focus on data analysis and visualization. It is suitable for beginners with no prior programming experience.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/xc29sg/importing
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Time
1 hours
Via
Pluralsight
This course belongs to a
collection
called
Importing Data with R. It's comprised of two courses:
- Importing Formatted Text Files: R Playbook
- Importing Common Data File Formats: R Playbook (viewing)
Good to know
Covers foundational principles, which is suitable for beginners
Introduces essential skills and frameworks widely used in industry
Taught by instructors who are recognized experts in the field
Provides a comprehensive overview of data manipulation and analysis in R
May require additional prerequisite knowledge in data analysis or statistics
Exercises and assignments may be limited, so additional practice is recommended
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