R Programming : Data Analysis and Visualisations using R
Learn how to use the R programming language for Data Analysis and Data visualization!(GGPlot2, Statistical, Packages)
Note: 4.4/5 (35 notes) 9,798 students
Instructor(s): Chetan Pujari
Last update: 2022-03-04
What you’ll learn
- Master the use of the R and R Studio interactive environment
- How to download R programming language and R Studio IDE
- Getting familiar with the Console, Script, Environment, Help, and Plots panels.
- Understanding different data types in R
- How to create, manipulate and work with different data types like Vectors, Matrices, Lists, Arrays, and Data frames.
- Installing and loading the Packages in the R environment.
- Reading and writing various Data Files like CSV, Xls, XML, JSON, xlsx, txt.
- Using various functions associated with the data frames and performing data manipulation on the data frames/files.
- Performing data Transformation and data analysis on the data files and data frames.
- Getting familiar with the packages: ggplot2, tidyverse, dplyr, plotly
- How to load and work upon various datasets which are native to R.
- Performing data visualization by creating various plots.
- learn to draw plots in R studio: Pie Charts, Bar Charts, Box plots, Histograms, Line Graphs, Scatter Plots.
- Learn how to draw some advanced plots like Density charts, Bubble plots, lollipop charts, 3D charts in R studio
- How to perform Data Analysis and Visualization using R in R studio.
- Install External Libraries to Power up R
- Compute Basic Statistics about a Dataset
- Develop your own Functions in R
- No prior knowledge of R or R Studio is required. You will learn all from the basics.
This course will teach you R programming and how to program R in R Studio along with its usage for effective data analysis. You will be able to master the basics of R, including the lists, vectors, and data frames.
The course provides practical knowledge about programming in R, reading and writing data files into R, loading and installing the R packages, loading and working upon various datasets, data transformation techniques, creating and handling various data types, data analysis, and visualization by creating various kinds of plots. R is very actively used for statistical computing and designing. It is one of the most widely used languages in the data science sector.
Some of the big shot industries like Google, LinkedIn, and Facebook, rely on R for many of their operations. Many of the data-driven businesses and companies are using R programming as their core platform and are recruiting trained R programmers. It is a very powerful data visualization tool. So make sure you are up with the software trends.
This course was designed to be focused on the practical side of coding in R – instead of teaching you every function and method out there, I’ll show you how you can read questions and examples and get to the answer by yourself, compounding your knowledge on the different R objects.
This course is truly step-by-step. In every new tutorial, we build on what had already been learned and move one extra step forward.
After every video, you learn a new valuable concept that you can apply right away. And the best part is that you learn through live examples.
By end of this course, you will be able to solve Industry Data Science projects in R starting including model building, model diagnostics, and presenting actionable business insights
Who this course is for
- For the Beginners who want to learn the R programming language to perform data analysis and Visualization. It will be helpful for those who are curious about Data Science, as it is part of data science.
- Data Analysts
- Software Engineering Undergraduates
- Data Scientists
- Data Engineers
- R learners
- If you want to learn R by doing
- If you like exciting challenges
- Download of R and R Studio
- R Studio Interface Introduction
- Variables and datatypes in R
- Basic Mathematics Operations in R
- How to Create & Name Lists in R
- Arrays and Matrices in R
- Using the Data Frame in R
- Reading and Writing Data in R: Part 1
- Reading and Writing Data in R: Part 2
- Data Transformation with R: Part 1(arrange,filter,summarize,select,mutate)
- Data Transformation with R: Part 2(arrange,filter,summarize,select,mutate)
- Data Transformation with R: Part 3(arrange,filter,summarize,select,mutate)
- Data Transformation with R: Part 4(arrange,filter,summarize,select,mutate)
- Plotting Pie Chart in R
- Scatter plots in R
- Advanced data visualization with R
- Bar Plot in R
- Boxplots in R
- Histograms in R
- Line Graphs in R
- Bubble chart in R
- Lollipop Chart in R
- An Interactive 3D Plot in R
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