Basic Analytic Techniques - Using R Tool - Part 1
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The document introduces basic analytic techniques using R, covering data exploration, visualization, and diagnostic analytics. It explains fundamental R functions and how to handle data frames with the built-in iris dataset. Additionally, it provides resources for downloading R and accessing training in business analytics.
Basic Analytic Techniques - Using R Tool - Part 1
- 1. Lesson3 BASIC ANALYTIC TECHNIQUES – USING R Part 1
- 2. ● Get a basic introduction to R ● Understand exploration of data ● Explore data using R ● Visualize data using R ● Understand diagnostic analytics ● Implement diagnostic analytics using R Objective Slide After completing this course, you will be able to: Copyright 2016,Beamsync, All rights reserved.
- 3. Introduction to R • Programming language for graphics and statistical computations • Available freely under the GNU public license • Used in data mining and statistical analysis • Included time series analysis, linear and non linear modeling among others • Very active community and package contributions • Very little programming language knowledge necessary • Can be downloaded from http://www.r-project.org/ • R Studio - optional Copyright 2016,Beamsync, All rights reserved.
- 4. • Packages - • install.packages('package_name') • library(package_name) • Loading data – • data(dataset_name) • read and write functions • getwd() and setwd(dir) • read and write functions use full path name • Example : read.csv(“C:/Rtutorials/Sampledata.csv”). • Assignment operator : “ <- ” • Help - ?function_name Basic R Copyright 2016,Beamsync, All rights reserved.
- 5. • Basic functions for data exploration in R • Data stored as “data frames” • Data frames – tabular representation of data with rows and columns • Every row denotes a particular “case” • Sample data frame (iris data set) Data exploration using R Sepallength Sepalwidth Petallength Petalwidth Species 7.9 3.8 6.4 2 I. virginica 7.7 3 6.1 2.3 I. virginica 5.6 2.5 3.9 1.1 I. versicolor 5.6 2.8 4.9 2 I. virginica 5.5 4.2 1.4 0.2 I. setosa 5.5 3.5 1.3 0.2 I. setosa 7.1 3 5.9 2.1 I. virginica 7 3.2 4.7 1.4 I. versicolor Copyright 2016,Beamsync, All rights reserved.
- 6. • Iris dataset – built in data frame • View data set • iris • View first few rows of the data set • head(iris, n) • View last few rows of the data set • tail(iris, n) Viewing data frame Copyright 2016,Beamsync, All rights reserved.
- 7. • View the dimensions of the data set • dim(iris) • View the number of columns • ncol(iris) • View the number of rows • nrow(iris) Dimensions of data frame Copyright 2016,Beamsync, All rights reserved.
- 8. • View column names/headers • names(iris) • View all attributes • attributes(iris) Attributes of Data frame Copyright 2016,Beamsync, All rights reserved.
- 9. • iris$Petal.Length • iris* , “Petal.Length”+ View column data Copyright 2016,Beamsync, All rights reserved.
- 10. Thank You Beamsync is providing business analytics training in Bangalore along with certification. If you are looking for upcoming training schedules then visit: http://beamsync.com/business-analytics-training-bangalore/