Course: Datasets in R
duration: 10 hours |
Language: English (US) |
access duration: 90 days |
Details
Transforming and manipulating massive amounts of data is crucial for all organizations. The R programming language offers a plethora of packages to load, explore, manipulate, and transform data. R is ideal for data analysis, mutation, and cleaning, making it a choice language for statisticians and data scientists. In this course, you'll learn how to write R script files using the RStudio environment. You'll learn how to connect to relational databases using the APIs provided in the Database Interface package (DBI) in R. You'll connect to SQLite data and perform, create, read, update, and delete (CRUD) operations on your database tables. Next, you’ll explore how to solve complex transformations using pipe operator and chaining operations. Finally, you'll practice methods to merge data to prepare for statistical and predictive modeling and identify relationships in your data using charts and graphs.
Result
After completing this course, you have more advanced knowledge of how to use datasets in R.
Prerequisites
No formal prerequisites. However, some basic R knowledge is recommended.
Target audience
Database Administrators, Data analist
Content
Datasets in R
Datasets in R: Loading & Saving Data
Transforming and manipulating massive amounts of data is crucial
- for all organizations. The R programming language offers a plethora
- of packages to load, explore, manipulate, and transform data. R is
- ideal for data analysis, mutation, and cleaning, making it a choice
- language for statisticians and data scientists. In this course,
- you'll learn how to write R script files using the RStudio
- environment. You'll use different panes to debug and evaluate your
- R program, import data in various file formats, and access files
- embedded in an R package and stored on your machine. Additionally,
- you'll learn how to export data to different file formats. Once
- you've completed this course, you'll know how to work R using
- RStudio, import and export data in R, and perform simple data
- transformation and exploration operations.
Datasets in R: Transforming Data
- Organizations store data in various ways. The R programming language offers a straightforward interface to work with data in relational databases and transform it to the format you need for analysis.
- In this course, you'll learn how to connect to relational databases using the APIs provided in the Database Interface package (DBI) in R. You'll connect to SQLite data and perform create, read, update, and delete (CRUD) operations on your database tables.
- You'll also use R functions to mutate and transform data. You'll practice renaming columns, changing variable types, and creating new columns from derived data.
- You'll examine the tidyverse universe of data science packages and work with data in the wide and long formats.
- Once you've completed this course, you'll have a strong foundation in basic data manipulation and transformation using the R programming language.
Datasets in R: Selecting, Filtering, Ordering, & Grouping Data
- Data analysis often requires performing a series of complex transformations. R makes this hassle-free via the forward pipe operator for chaining operations, data selection and filtering based on conditional operations, and grouping and aggregating options to compute summaries. Learn how to carry out all these operations in this course.
- Task you'll carry out include using logical and relational operators to perform conditional filtering, sampling records at random, and computing the top N records based on values in a variable.
- You'll also learn to use the forward pipe operator in the magrittr package and tibbles, the next-generation data frame, to store and transform your data.
- You'll round this course off by performing ordering, grouping, and aggregations on your data.
- When you're finished, you'll have a solid grasp of complex operations on data frames and be able to apply these concepts using the R programming language.
Datasets in R: Joining & Visualizing Data
- Data for the same entity is often stored in multiple locations. Your analysis may require bringing this data together in a single location. Doing this forms a core part of data preprocessing. Another core task is recognizing the relationships in your data.
- In this course, you'll practice methods to merge data to prepare for statistical and predictive modeling and identify relationships in your data using charts and graphs.
- You'll combine data in different data frames (or tibbles) based on the values in common columns. You'll use the merge() function to perform join operations and implement joins using functions from the tidyverse.
- You'll also examine the plotting systems available in R and use the plot() functionality and the ggplot2 package to visualize and explore your data.
- Upon completion of this course, you'll be able to combine your data in a meaningful way and uncover data relationships.
Course options
We offer several optional training products to enhance your learning experience. If you are planning to use our training course in preperation for an official exam then whe highly recommend using these optional training products to ensure an optimal learning experience. Sometimes there is only a practice exam or/and practice lab available.
Optional practice exam (trial exam)
To supplement this training course you may add a special practice exam. This practice exam comprises a number of trial exams which are very similar to the real exam, both in terms of form and content. This is the ultimate way to test whether you are ready for the exam.
Optional practice lab
To supplement this training course you may add a special practice lab. You perform the tasks on real hardware and/or software applicable to your Lab. The labs are fully hosted in our cloud. The only thing you need to use our practice labs is a web browser. In the LiveLab environment you will find exercises which you can start immediately. The lab enviromentconsist of complete networks containing for example, clients, servers,etc. This is the ultimate way to gain extensive hands-on experience.
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