Objectives of the training

R is a statistical language dedicated to Data Science and is very rich in features. The proposed set of resources is aimed at anyone who wants to learn how to extract data from various sources (CSV, Excel, SQL database, Web API) with this language and then be able to manipulate and organize them. You will learn how to filter, sort, group, summarize, merge or clean data using different packages.

Targeted audience

Computer scientists

Prerequisite

None.

Trainers

Upcoming information

Course architecture

R Language - The fundamentals of R programming for Data Science

Discovering R
• Presentation of R
• Installation and resources
• The package system
• RStudio IDE and creating a first script

The basics of the R language
• Variables and types
• Formats: vectors
• Formats: matrices
• Formats: DataFrame
• Formats: lists
• Conditions (if ... else)
• The loops
• The functions
• The apply functions

R and the data
• Retrieving data from a CSV file
• Retrieving other data formats: Excel, SQL, API
Statistical analysis and first graphs
• Analysis of numerical variables
• Analysis of categorical variables
• Other statistical analysis methods
Rendering results: overview of possibilities
• Graphs

R language - Access all your data types

Some reminders about R and its environment
• Why R ?
• Installation of the environment
• Resources related to R

Data in CSV format
• Accessing data in CSV format
• Putting it into practice - Data Visualization: bar chart

Data in Excel format
• Accessing data in Excel format
• Practical Guide - Data Visualization: Scatterplot

Data from a SQL database
• Accessing data from an SQL database
• Practical Guide - Data Visualization: Word Cloud

Data from an API
• Accessing data from an API
• Data Visualization Practice: Dynamic Bar Chart for the Web

Data from a NoSQL MongoDB database
• Accessing data from a NoSQL database
• Putting it into practice - Data Visualization: dynamic bar chart for the web

R language - Manipulate your data with the dplyr and tidyr packages

Reminders on how to access different data formats with R
• Access to data in CSV format
• Access to other data formats (Excel, SQL databases, API...)

Manipulation using the dplyr package
• Introduction to the "dplyr" package: syntax and pipe
• Manipulation of observations (rows)
• Manipulation of variables (columns)
• Creation of summary data tables
• Data joins

Introduction to data cleaning with the tidyr package
• Reshaping data
• Completing missing values

Private or personalized training

If you have more than 8 people to sign up for a particular course, it can be delivered as a private session right at your offices. Contact us for more details.

Request a quote

Duration

7.0 hours

Regular fee

$250

Private or personalized training

If you have more than 8 people to sign up for a particular course, it can be delivered as a private session right at your offices. Contact us for more details.

Request a quote

R Language: Data Manipulation for Data Science

Objectives of the training

Targeted audience

Prerequisite

Trainers

Course architecture

Private or personalized training

Private or personalized training

Purchase summary

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