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Emmanuel Segui
In this 1-hour long project-based course, you will learn how to pivot data into wide and long format, split and combine cells and columns, handling missing values, select groups of observations and variables, and join data from different tables.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Register for this course and see more details by visiting:
OpenCourser.com/course/rlbwaw/transforming
What's inside
Syllabus
Project Overview
By the end of this project, you will be able to pivot data into wide and long format, split and combine cells and columns, handling missing values, select groups of observations and variables, and join data from different tables.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Offers practical, immediately applicable skills
Helps learners explore data formatting techniques
Suitable for learners based in North America
May not be as relevant for learners outside North America
Content examined may be standard in industry
Taught by recognized instructor Emmanuel Segui
Save this course
Save Transforming Data in R to your list so you can find it easily later:
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Reviews summary
Good for beginners
Learners say that this course is good for beginners. Also instructors are great.
This course is for beginners in R
"It is an easy project therefore only for rookies in R!"
The instructor is great
"I started knowing nothing about R and ended up the project knowing many things and doing it with confident..The instructor is great"
Cannot download tidyverse
"cannot download tidyverse which is the first task!"
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 Transforming Data in R with these
activities:
Review Data Wrangling with Python
Show steps
Review the foundations of data wrangling to enhance your understanding of data manipulation techniques.
View
Python for Data Analysis: Data Wrangling with...
on Amazon
Show steps
-
Read chapters 1-3 of 'Data Wrangling with Python'.
-
Complete the exercises at the end of each chapter.
Attend a Data Wrangling Workshop
Show steps
Expand your knowledge by attending a workshop focused on data wrangling techniques.
Browse courses on
Data Wrangling
Show steps
-
Search for a data wrangling workshop in your area.
-
Register for the workshop and attend the sessions.
Practice Data Cleaning Drills
Show steps
Complete hands-on exercises to solidify your data cleaning skills.
Browse courses on
Data Cleaning
Show steps
-
Find a dataset with missing values and duplicate rows.
-
Clean the dataset by removing duplicates and filling missing values.
Three other activities
Expand to see all activities and additional details
Show all six activities
Create a Data Manipulation Tutorial
Show steps
Create a visual tutorial or written guide to reinforce your understanding of data manipulation techniques.
Browse courses on
Data Manipulation
Show steps
-
Choose a specific data manipulation technique to focus on.
-
Create a step-by-step guide explaining the technique.
-
Record a video or write a blog post to share your tutorial.
Volunteer for a Data Cleaning Project
Show steps
Gain practical experience by volunteering for a project that involves data cleaning.
Browse courses on
Data Cleaning
Show steps
-
Identify a non-profit organization or research institution that needs assistance with data cleaning.
-
Contact the organization and offer your services.
-
Work with the organization to clean and prepare their data for analysis.
Contribute to an Open-Source Data Manipulation Library
Show steps
Deepen your understanding of data manipulation by contributing to an open-source library.
Browse courses on
Data Manipulation
Show steps
-
Identify an open-source data manipulation library that interests you.
-
Find an issue or feature that you can contribute to.
-
Submit a pull request with your changes.
Review Data Wrangling with Python
Show steps
Review the foundations of data wrangling to enhance your understanding of data manipulation techniques.
View
Python for Data Analysis: Data Wrangling with...
on Amazon
Show steps
Show steps
Show steps
- Read chapters 1-3 of 'Data Wrangling with Python'.
- Complete the exercises at the end of each chapter.
Attend a Data Wrangling Workshop
Show steps
Expand your knowledge by attending a workshop focused on data wrangling techniques.
Browse courses on
Data Wrangling
Show steps
Show steps
Show steps
- Search for a data wrangling workshop in your area.
- Register for the workshop and attend the sessions.
Practice Data Cleaning Drills
Show steps
Complete hands-on exercises to solidify your data cleaning skills.
Browse courses on
Data Cleaning
Show steps
Show steps
Show steps
- Find a dataset with missing values and duplicate rows.
- Clean the dataset by removing duplicates and filling missing values.
Three other activities
Expand to see all activities and additional details
Show all six activities
Create a Data Manipulation Tutorial
Show steps
Create a visual tutorial or written guide to reinforce your understanding of data manipulation techniques.
Browse courses on
Data Manipulation
Show steps
Show steps
Show steps
- Choose a specific data manipulation technique to focus on.
- Create a step-by-step guide explaining the technique.
- Record a video or write a blog post to share your tutorial.
Volunteer for a Data Cleaning Project
Show steps
Gain practical experience by volunteering for a project that involves data cleaning.
Browse courses on
Data Cleaning
Show steps
Show steps
Show steps
- Identify a non-profit organization or research institution that needs assistance with data cleaning.
- Contact the organization and offer your services.
- Work with the organization to clean and prepare their data for analysis.
Contribute to an Open-Source Data Manipulation Library
Show steps
Deepen your understanding of data manipulation by contributing to an open-source library.
Browse courses on
Data Manipulation
Show steps
Show steps
Show steps
- Identify an open-source data manipulation library that interests you.
- Find an issue or feature that you can contribute to.
- Submit a pull request with your changes.
Career center
Learners who complete Transforming Data in R will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists leverage data to solve complex problems and drive decision-making in various industries. This course equips you with the essential skills for data transformation, enabling you to clean, prepare, and manipulate data effectively. By gaining proficiency in these techniques, you can strengthen your foundation as a Data Scientist and contribute more effectively to data-driven decision-making.
Data Engineer
Data Engineer
Data Engineers design and maintain data pipelines to ensure data integrity and accessibility. This course introduces techniques for data transformation, providing you with a strong foundation for building and managing data infrastructure. By developing proficiency in these skills, you can enhance your ability to design efficient data pipelines and contribute to the success of data-driven organizations as a Data Engineer.
Data Analyst
Data Analyst
A Data Analyst examines data to uncover trends and insights that assist businesses in making informed decisions. This course provides foundational skills in data wrangling and transformation, enabling you to prepare data for analysis and extract valuable information. By mastering these techniques, you can enhance your data analysis abilities and advance your career as a Data Analyst.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design and implement machine learning models to solve real-world problems. This course provides essential skills in data transformation, enabling you to prepare and manipulate data for machine learning algorithms. By developing proficiency in these techniques, you can enhance your ability to build and deploy machine learning models effectively as a Machine Learning Engineer.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to assess financial risk and make investment decisions. This course provides essential skills in data transformation, empowering you to prepare and analyze financial data effectively. By developing proficiency in these techniques, you can enhance your ability to develop and implement quantitative models and contribute to informed investment decisions as a Quantitative Analyst.
Business Analyst
Business Analyst
Business Analysts play a crucial role in bridging the gap between business requirements and technical solutions. This course provides a solid foundation in data transformation, empowering you to understand and manipulate data from various sources. By mastering these skills, you can enhance your ability to analyze business needs, propose solutions, and drive positive outcomes as a Business Analyst.
Data Architect
Data Architect
Data Architects design and manage data architecture to ensure data integrity and accessibility across an organization. This course provides a foundation in data transformation, enabling you to understand and manipulate data from various sources. By mastering these techniques, you can enhance your ability to design and implement data architectures that meet the evolving needs of organizations as a Data Architect.
Data Visualization Specialist
Data Visualization Specialist
Data Visualization Specialists translate complex data into visually compelling representations. This course provides a foundation in data transformation, enabling you to prepare and manipulate data for effective visualization. By mastering these techniques, you can enhance your ability to create insightful visualizations and communicate data-driven insights effectively as a Data Visualization Specialist.
Statistician
Statistician
Statisticians collect, analyze, and interpret data to uncover patterns and make inferences. This course provides a foundation in data transformation, enabling you to prepare and manipulate data for statistical analysis. By mastering these techniques, you can enhance your ability to conduct rigorous statistical analyses and contribute to evidence-based decision-making as a Statistician.
Financial Analyst
Financial Analyst
Financial Analysts evaluate financial data and make recommendations for investment and financial decisions. This course provides a foundation in data transformation, enabling you to prepare and manipulate financial data effectively. By mastering these techniques, you can enhance your ability to conduct financial analysis and make informed investment decisions as a Financial Analyst.
Risk Analyst
Risk Analyst
Risk Analysts assess and manage financial and operational risks within organizations. This course provides essential skills in data transformation, enabling you to prepare and analyze data for risk assessment. By developing proficiency in these techniques, you can enhance your ability to identify, evaluate, and mitigate risks effectively as a Risk Analyst.
Database Administrator
Database Administrator
Database Administrators ensure the performance, security, and availability of databases. This course provides essential skills in data transformation, enabling you to manipulate and manage data within database systems. By developing proficiency in these techniques, you can enhance your ability to optimize database performance and ensure data integrity as a Database Administrator.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and analytical techniques to improve the efficiency and effectiveness of operations. This course provides essential skills in data transformation, enabling you to prepare and analyze data for operational research models. By developing proficiency in these techniques, you can enhance your ability to develop and implement optimization solutions as an Operations Research Analyst.
Management Consultant
Management Consultant
Management Consultants provide advice and solutions to organizations on various business issues. This course provides a foundation in data transformation, enabling you to understand and manipulate data from various sources. By mastering these techniques, you can enhance your ability to analyze business problems, develop solutions, and drive organizational success as a Management Consultant.
Information Technology Specialist
Information Technology Specialist
Information Technology Specialists provide technical support and manage IT systems within organizations. This course provides a foundation in data transformation, enabling you to understand and manipulate data from various sources. By mastering these techniques, you can enhance your ability to troubleshoot IT issues, manage data, and contribute to the efficient functioning of IT systems as an Information Technology Specialist.
For more career information including salaries, visit:
OpenCourser.com/course/rlbwaw/transforming
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
Transforming Data in R.
Save
Widely-used textbook for introductory data science courses. It covers a wide range of topics, including data visualization, data transformation, and statistical modeling. It great resource for learners who want to gain a broad understanding of data science.
Provides a thorough introduction to the R programming language. It covers topics such as data structures, functions, control flow, and object-oriented programming. It good choice for learners who want to build a solid foundation in R.
Save
Collection of practical recipes for solving common data manipulation and analysis tasks in R. It useful reference for learners who want to quickly find solutions to specific problems.
Focuses specifically on data manipulation techniques in R. It covers topics such as data cleaning, transformation, and reshaping. It good choice for learners who want to specialize in data wrangling.
Save
Covers advanced topics in R, such as functional programming, data visualization, and statistical modeling. It good choice for learners who want to deepen their understanding of R and its capabilities.
Provides a practical introduction to the R programming language. It covers a wide range of topics, including data manipulation, visualization, and statistical modeling. It good choice for learners who want to get started with R quickly.
Save
Provides a practical guide to data science using R. It covers topics such as data exploration, modeling, and visualization. It good choice for learners who want to learn how to apply R to real-world data science problems.
Provides a practical introduction to data science for business professionals. It covers topics such as data mining, machine learning, and statistical modeling. It good choice for learners who want to learn how to use data to drive business decisions.
Provides an introduction to machine learning using R. It covers topics such as supervised learning, unsupervised learning, and model evaluation. It good choice for learners who want to learn how to use R for machine learning.
Provides an introduction to deep learning using R. It covers topics such as neural networks, convolutional neural networks, and recurrent neural networks. It good choice for learners who want to learn how to use R for deep learning.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/rlbwaw/transforming
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Effort
1 hour
Level
Intermediate
Via
Coursera
Institution
Coursera Project Network
Instructor
Emmanuel Segui
Language
English
Good to know
Offers practical, immediately applicable skills
Helps learners explore data formatting techniques
Suitable for learners based in North America
May not be as relevant for learners outside North America
Content examined may be standard in industry
Taught by recognized instructor Emmanuel Segui
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