We can know the total observation value by viewing the tail rows. Given scatterplots that represent problem situations, the student will determine if the data has strong vs weak correlation as well as positive, negative, or no correlation. library(scatterplot3d) Once the data is imported into R, the data can be checked using the head function. Thus, giving a full view of the correlation between the variables. Then add the alpha transparency level as the 4th number in the color vector. library(rgl)    col=super.sym$col[1:3]), Enhanced Scatterplots with Marginal Boxplots, Point Marking, Smoothers, and More This function uses basic R graphics to draw a two-dimensional scatterplot, with options to allow for plot enhancements that are often helpful with regression problems. Scatter Plots In R Scatter plots (scatter diagrams) are bivariate graphical representations for examining the relationship between two quantitative variables. Deploy them to Dash Enterprise for hyper-scalability and pixel-perfect aesthetic. points(iris$Sepal.Length[iris$Species=='setosa'],iris$Sepal.Width[iris$Species=='setosa'],pch=19,col='blue'). Width variables are correlated. Next, we will apply green color to Versicolor species category using another point () function, plot(iris$Sepal.Length,iris$Sepal.Width,xlab='Sepal Length',ylab='Sepal Width',main='Sepal Properties of Iris Flowers',pch=19,col='red') # Another Spinning 3d Scatterplot The first part is about data extraction, the second part deals with cleaning and manipulating the data. y <- rnorm(1000) scatterplot.matrix(~mpg+disp+drat+wt|cyl, data=mtcars, Calculus: Integral with adjustable bounds. We use the data set “mtcars” available in the R environment to create a basic scatter plot. Also will add the title of the scatter plot as Sepal Properties of Iris Flowers. The R code for the label would be as follows, plot(iris$Sepal.Length,iris$Sepal.Width,xlab='Sepal Length',ylab='Sepal Width',main='Sepal Properties of Iris Flowers'). Sometimes the pair of dependent and independent variable are grouped with some characteristics, thus, we might want to create the scatterplot with different colors of the group based on characteristics. # Enhanced Scatterplot of MPG vs. dta <- mtcars[c(1,3,5,6)] # get data The iris dataset in R is a collection of 150 observations across 5 variables concerning the iris flower. R Console Output showing the last 20 rows of iris dataset with row number as the first column. example. x <- rnorm(1000)    labels=row.names(mtcars)). by Number of Car Cylinders This website or its third-party tools use cookies, which are necessary to its functioning and required to achieve the purposes illustrated in the cookie policy. fit <- lm(mpg ~ wt+disp) Scatter plots are extremely useful identify any trend between two quantitative variables. After loading the library, the execution of the below commands will create a 3-D scatterplot.    panel=panel.superpose, # In the data set faithful, we pair up the eruptions and waiting values in the same observation as (x, y) coordinates. # High Density Scatterplot with Color Transparency You can create a 3D scatterplot with the scatterplot3d package.    main="Three Cylinder Options"). 132. Note: You can use the col2rgb( ) function to get the rbg values for R colors. A comparison between variables is required when we need to define how much one variable is affected by another variable.    main="Enhanced Scatter Plot", plot3d(wt, disp, mpg, col="red", size=3). Ok. Now that I've quickly reviewed how ggplot2 works, let's take a look at an example of how to create a scatter plot in R with ggplot2. A scatterplot is the plot that has one dependent variable plotted on Y-axis and one independent variable plotted on X-axis. THE CERTIFICATION NAMES ARE THE TRADEMARKS OF THEIR RESPECTIVE OWNERS. The Scatter Plot in R Programming is very useful to visualize the relationship between two sets of data. Scatter Plots with R. Do you want to make stunning visualizations, but they always end up looking like a potato?    points=list(pch=super.sym$pch[1:3], The basic syntax for creating scatterplot in R is − plot (x, y, main, xlab, ylab, xlim, ylim, axes) Following is the description of the parameters used − x is the data set whose values are the horizontal coordinates. dev.off(). In Figure 3 you can see a red regression line, which overlays … Simple Scatterplot There are many ways to create a scatterplot in R. The basic function is plot (x, y), where x and y are numeric vectors denoting the (x,y) points to plot. # reorder variables so those with highest correlation scatterplot(mpg ~ wt | cyl, data=mtcars, The length will be provided to the x-axis of the graph. col= and size= control the color and size of the points respectively. Example 2 explains how to use the ggplot2 package to print a scatterplot … Any reasonable way of defining the coordinates is acceptable. © 2020 - EDUCBA. 12. degree of local polynomial used. A video tutorial for creating scatterplots in R.Created by the Division of Statistics + Scientific Computation at the University of Texas at Austin. R in Action (2nd ed) significantly expands upon this material. bin<-hexbin(x, y, xbins=50) When there are many data points and significant overlap, scatterplots become less useful. For this R provides multiple packages, one of them is “scatterplot3d”. The gclus package provides options to rearrange the variables so that those with higher correlations are closer to the principal diagonal. This plot is a two-dimensional (bivariate) data visualization that uses dots to represent the values collected, or measured, for two different variables. y <- rnorm(1000) There are many ways to create a scatterplot in R. The basic function is plot(x, y), where x and y are numeric vectors denoting the (x,y) points to plot. You can also create an interactive 3D scatterplot using the plot3D(x, y, z) function in the rgl package. Scatter Plot in R using ggplot2 (with Example) Graphs are the third part of the process of data analysis. Create a matrix of scatterplots (pairs() equivalent) in ggplot2. Further, we will be adding color with the specific condition to each Species category by using point function in R language, R code to improve the Scatter plot for an aesthetic change with red color, plot(iris$Sepal.Length,iris$Sepal.Width,xlab='Sepal Length',ylab='Sepal Width',main='Sepal Properties of Iris Flowers',pch=19,col='red'), Applying points() function to segregate the color for setosa category of iris species and changing the color to blue, plot(iris$Sepal.Length,iris$Sepal.Width,xlab='Sepal Length',ylab='Sepal Width',main='Sepal Properties of Iris Flowers',pch=19,col='red') However, often you have additional variable in a data set and you might be interested in understanding its relationship. The function lm () will be used to fit linear models between y and x. ), # Add fit lines Add legible labels and title. It can also color code the cells to reflect the size of the correlations. smoothness parameter for loess.. degree. with respective examples with appropriate syntax and sample codes.t. You may also look at the following articles to learn more-, R Programming Training (12 Courses, 20+ Projects). To create scatter plots in R programming, the First step is to identify the numerical variables from the input data set which are supposed to be correlated. Calculus: Fundamental Theorem of Calculus    xlab="Weight of Car", ylab="Miles Per Gallon", library(hexbin) The above scatter plot shows red for virginica, blue for setosa and green for Versicolor. Arguments x, y. the x and y arguments provide the x and y coordinates for the plot. ). The chart #13 below will guide you through its basic usage. Find out if … There are several approaches that be used when this occurs. dta.col <- dmat.color(dta.r) # get colors 10% of the Fortune 500 uses Dash Enterprise to productionize AI & data science apps. This function creates a spinning 3D scatterplot that can be rotated using a mouse. Scatterplot with Straight Fitting Line. Next, we will apply more parameters to the plot function to improve the scatter plot representation. The scatterplot( ) function in the car package offers many enhanced features, including fit lines, marginal box plots, conditioning on a factor, and interactive point identification. Both numeric variables of the input dataframe must be specified in the x and y argument. It completes the example of Scatter plots in R. The scatter plot using plot() function provides basic features of representation, however, implementation of the ggplot2 package provides additional representation features like advance color grouping and various symbols type to the scatter plot. Length and sepal. # Basic Scatterplot Matrix The sepal. The sepal. The color, the size and the shape of points can be changed using the function geom_point() as follow :. Use promo code ria38 for a 38% discount. # Simple Scatterplot Scatterplot with marginal histograms in ggplot2. The hexbin(x, y) function in the hexbin package provides bivariate binning into hexagonal cells (it looks better than it sounds). The most basic and simple command for scatterplot matrix is: pairs(~Sepal.Length+Sepal.Width+Petal.Length+Petal.Width, data= iris, main =”Scatterplot Matrix”). dta.o <- order.single(dta.r) attach(mtcars) For example, the following scatterplot helps us visualize the … library(Rcmdr) A Scatter Plot in R also called a scatter … R can plot them all together … Luckily, R makes it easy to produce great-looking visuals. The iris data set data dictionary would be the dataset having flowers properties information, Let’s view the variables available in the iris dataset by using colnames function in R programming, Let’s discuss the detailed variables available and their types in the iris dataset, Next, we will review the first 20 rows of the iris dataset by using a head function in R, The above R console Output data view of iris dataset shows sepal. Next, apply the plot function with the selected variables as parameters to create Scatter plots in the R language. # Spinning 3d Scatterplot s3d <-scatterplot3d(wt,disp,mpg, pch=16, highlight.3d=TRUE, A scatter plot can be created using the function plot (x, y). A graph in which the values of two variables are plotted along X-axis and Y-axis, the pattern of the resulting points reveals a correlation between them. splom(mtcars[c(1,3,5,6)], groups=cyl, data=mtcars, If you add price into the mix and you want to show all the pairwise relationships among MPG-city, price, and horsepower, you’d need multiple scatter plots. Simple scatter plots are created using the R code below. In the example of scatter plots in R, we will be using R Studio IDE and the output will be shown in the R Console and plot section of R Studio. Base R is also a good option to build a scatterplot, using the plot () function. scatterplot3d(Sepal.Length, Sepal.Width, Petal.Length, main = “3D Scatterplot”). When we have more than two variables in a dataset and we want to find a cor… Length and sepal.Width variables using plot() function in R programming. Scatterplots are useful for interpreting trends in statistical data. 2470.    text=list(c("4 Cylinder","6 Cylinder","8 Cylinder")))). Scatter plots in R Language. ALL RIGHTS RESERVED. points(iris$Sepal.Length[iris$Species=='versicolor'],iris$Sepal.Width[iris$Species=='setosa'],pch=19,col='green'). library(lattice) 140. library(car) # High Density Scatterplot with Binning Below I will show an example of the usage of a popular R … There are at least 4 useful functions for creating scatterplot matrices. … We will add the x-axis label as Sepal Length and y-axis as Sepal Width. It will help in the linear regression model building for predictive analytics. The above scatterplot shows setosa category floors are in blue and others are in red-colored points. The Scatter plots in R programming can be improvised by adding more specific parameters for colors, levels, point shape and size, and graph titles. # 3D Scatterplot The car package can condition the scatterplot matrix on a factor, and optionally include lowess and linear best fit lines, and boxplot, densities, or histograms in the principal diagonal, as well as rug plots in the margins of the cells.    columns=3,    main="Simple Scatterplot Matrix"). Example R Scatter Plot. Finally, you can save the scatterplot in PDF format and use color transparency to allow points that overlap to show through (this idea comes from B.S. Example. Similarly, the above dataset shows the petal, Length, and petal. It’s a tough place to be. Heare its 150 observations are plotted in the scatter plot. Scatterplots are excellent for visualizing the relationship between two continuous variables. Previously, we described the essentials of R programming and provided quick start guides for importing data into R. Here, we’ll describe how to make a scatter plot. R ggplot2 Scatter Plot A R ggplot2 Scatter Plot is useful to visualize the relationship between any two sets of data. By closing this banner, scrolling this page, clicking a link or continuing to browse otherwise, you agree to our Privacy Policy, New Year Offer - R Programming Training (12 Courses, 20+ Projects) Learn More, R Programming Training (12 Courses, 20+ Projects), 12 Online Courses | 20 Hands-on Projects | 116+ Hours | Verifiable Certificate of Completion | Lifetime Access, Statistical Analysis Training (10 Courses, 5+ Projects), All in One Data Science Bundle (360+ Courses, 50+ projects). Last Updated : 21 Apr, 2020; A scatter plot is a set of dotted points to represent individual pieces of data in the horizontal and vertical axis. This tutorial explains when and how to use the jitter function in R for scatterplots.. Weight The above graph shows the correlation between weight, mpg, dsp, and cyl. s3d$plane3d(fit). Creating Scatterplots in R. The simplest scatterplot can be created using a plot(x,y) command, where x and y are vectors.Let us look at an example using some in-built R datasets. The variables can be both categorical, such as Language in the table below, and numeric, such as the various scores assigned to countries in the table below. These variables indicate the dimensions of flowers such as sepal length/width and petal length/width. Let us specify labels for x and y-axis. Try the creating scatterplot exercises in this course on data visualization in R. Copyright © 2017 Robert I. Kabacoff, Ph.D. | Sitemap. pairs(~mpg+disp+drat+wt,data=mtcars, And in addition, let us add a title … Users can also add details like color, titles to make the graph better. Sometimes a 3-dimensional graph gives a better understanding of data. The width will be provided to the y-axis of the graph. # and Regression Plane The R Scatter plot displays data as a collection of points that shows the linear relation between those two data sets. attach(mtcars) This is the basic syntax in R which will generate the scatter plot graphics. # are closest to the diagonal Width variables are correlated. The point representing that observation is placed at th… Base R provides a nice way of visualizing relationships among more than two variables. In a scatterplot, the data is represented as a collection of points. The scatter plot in R can be added with more meaningful levels and colors for better presentation. library(car) Then we plot the points in the Cartesian plane. Scatterplot with too many points. Each of these features is optional. For example, col2rgb("darkgreen") yeilds r=0, g=100, b=0. When to Use Jitter. scatter3d(wt, disp, mpg). The scatter plot is very useful to show the relationship between two variables by plotting a point for each row against a column variable of your choice. Let’s now create a scatterplot with sepal. abline(lm(mpg~wt), col="red") # regression line (y~x) The simplest way to create a scatterplot is to directly graph two variables using the default settings. Apart from this, there are many other ways to create a 3-Dimensional. scatterplot3d(wt,disp,mpg, main="3D Scatterplot"), # 3D Scatterplot with Coloring and Vertical Drop Lines    xlab="Car Weight ", ylab="Miles Per Gallon ", pch=19), (To practice making a simple scatterplot, try this interactive example from DataCamp. The above scatterplot diagram shows meaningful labels for representation. Here, the scatter plots come in handy. Load the ggplot2 package. See help(sunflowerplot) for details. pdf("c:/scatterplot.pdf") The second coordinate corresponds to the second piece of data in the pair (thats the Y-coordinate; the amount that you go up or down). Hadoop, Data Science, Statistics & others. Everrit in HSAUR). # Scatterplot Matrices from the car Package How to create line and scatter plots in R. Examples of basic and advanced scatter plots, time series line plots, colored charts, and density plots.   type="h", main="3D Scatterplot"), # 3D Scatterplot with Coloring and Vertical Lines lines(lowess(wt,mpg), col="blue") # lowess line (x,y). x <- rnorm(1000) 3D Scatter Plots in R How to make interactive 3D scatter plots in R. Building AI apps or dashboards in R? This is a guide to Scatterplots in R. Here we discuss how to create Scatter plots in R? Users can also create interactive 3D scatterplot by using “plot3D(x,y,z)” function provided by “rgl” package. How to make a great R reproducible example. It creates a spinning 3D scatterplot that can be rotated with the mouse.    key=list(title="Three Cylinder Options", The first three arguments are the x, y, and z numeric vectors representing points. Basic scatter plots. When drawing a scatter plot, we'll do this by using geom_point(). scatterplot3d(wt,disp,mpg, pch=16, highlight.3d=TRUE, The scatter plots in R for the bi-variate analysis can be created using the following syntax. cpairs(dta, dta.o, panel.colors=dta.col, gap=.5, Let’s assume x and y are the two numeric variables in the data set, and by viewing the data through the head() and through data dictionary these two variables are having correlation. As revealed in Figure 1, the previous R programming code created a graphic with colored points according to the values in our grouping vector. See help(rgb) for more information. plot(bin, main="Hexagonal Binning"). What is a Scatter Plot? attach(mtcars) Let’s assume x and y are the two numeric variables in the data set, and by viewing the data through the head() and through data dictionary these two variables are having correlation. A scatter plot displays data for a set of variables (columns in a table), where each row of the table is represented by a point in the scatter plot. R Scatterplots The scatter plots are used to compare variables. Before continuing this scatter plots in R tutorial, we will breifly discuss what a scatter plot is. Control the size of points in an R scatterplot? You can perform a similar function with the scatter3d(x, y, z) in the Rcmdr package. Read the series from the beginning:   type="h", main="3D Scatterplot") See the function xy.coords for details.. span. Let us see how to Create a Scatter Plot, Format its size, shape, color, adding the linear progression, changing the theme of a Scatter Plot using ggplot2 … plot(wt, mpg, main="Scatterplot Example", library(gclus) The plot () function of R allows to build a scatterplot. Use the function scatterplot3d(x, y, z). The dataset we will be using is the iris dataset, which is a popular built-in data set in the R language. # Scatterplot Matrices from the glus Package # Scatterplot Matrices from the lattice Package Analysts must love scatterplot matrices! The lattice package provides options to condition the scatterplot matrix on a factor. Following examples allow a greater level of customization. Let’s use the columns “wt” and “mpg” in mtcars. Next, we will apply further enhancements to the scatter plot by adding color and shapes to the scatter points. main="Variables Ordered and Colored by Correlation" In this post we will learn how to color scatter plots using another variable in the dataset in R with ggplot2. Example: how to make a scatter plot with ggplot2. library(scatterplot3d) # scatter plot in R input <- mtcars[,c('wt','mpg')] # Plot the chart for cars with weight between 2.5 to 5 … When we have more than two variables in a dataset and we want to find a correlation of each variable with all other variables, then the scatterplot matrix is used. Each observation (or point) in a scatterplot has two coordinates; the first corresponds to the first piece of data in the pair (thats the X coordinate; the amount that you go left or right). First, you need to make sure that you've loaded the ggplot2 package. Next, the step would be importing the dataset to the R environment. A value of zero means fully transparent. A very important tool in exploratory analysis, which is used to represent and analyze the relation between two variables in a dataset as a visual representation, in the form of X-Y chart, with one variable acting as X-coordinate and another variable acting as Y-coordinate is termed as scatterplot in R. R programming provides very effective and robust mechanism being facilitated but not limited to function such as plot(), with various functionalities in R providing options to improve visualization aesthetics. attach(mtcars) In the next R function, we will change the aesthetic of the points represented by using pch parameter value 19 which is the solid circle. Today you’ll learn how to create impressive scatter plots with R and the ggplot2 package. 121. Below are the commands to install “scatterplot3d” into the R workspace and load it in the current session. At last, the data scientist may need to communicate his results graphically. Another option for a scatterplot with significant point overlap is the sunflowerplot. The points in the scatter plot to show the data distribution patterns of all the observations of the iris dataset. Here we will discuss how to make several kinds of scatter plots in R. plot(x,y, main="PDF Scatterplot Example", col=rgb(0,100,0,50,maxColorValue=255), pch=16) In R, this can be accomplished with the plot (XVAR, YVAR) function, where XVAR is the variable to plot along the x-axis and YVAR is the variable to plot along the y-axis. attach(mtcars) A scatter plot pairs up values of two quantitative variables in a data set and display them as geometric points inside a Cartesian diagram.. dta.r <- abs(cor(dta)) # get correlations library(scatterplot3d) The scatter plots in R for the bi-variate analysis can be created using the following syntax plot(x,y) This is the basic syntax in R which will generate the scatter plot graphics. Example 2: Drawing Scatterplot with Colored Points Using ggplot2 Package. Using plot ( ) for scatterplots package library ( car ) scatterplot.matrix ~mpg+disp+drat+wt|cyl... Library, the size of the iris flower Fortune 500 uses Dash Enterprise to productionize AI & data apps... The CERTIFICATION NAMES are the TRADEMARKS of THEIR RESPECTIVE OWNERS apart from this, there are several approaches that used... Is very useful to visualize the relationship between two continuous variables the Cartesian plane explains how to the... Rearrange the variables so that those with higher correlations are closer to the function!, which is a scatter plot color, the size of points when drawing scatterplot in r scatter plot by adding and! At Austin for examining the relationship between two quantitative variables col= '' red '', size=3.! €¦ Base R provides a nice way of visualizing relationships among more than variables... 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Us add a title … Base R provides a nice way of visualizing among! The function scatterplot3d ( x, y, z ) changed using the following scatterplot in r. Functions for creating scatterplot matrices from the car package library ( car ) (. For examining the relationship between two sets of data rows of iris flowers reasonable way of visualizing among! Mtcars ) scatter3d ( x, y, z ) function in R,. Using ggplot2 package to print a scatterplot with Straight Fitting Line … scatterplots are excellent for the... At the University of Texas at Austin above graph shows the correlation between weight, mpg ) are using. Bi-Variate analysis can be created using the following syntax may need to define how much one is... # scatterplot matrices y, and petal scatterplot using the head function an interactive 3D scatterplot using plot3D. Guide you through its basic usage Petal.Length, main = “ 3D library. Transparency level as the first Three arguments are the commands to install “scatterplot3d” into the R environment variables. You can create a 3D scatterplot by using geom_point ( ) function of R allows to build a scatterplot to! 2017 Robert I. Kabacoff, Ph.D. | Sitemap used to compare variables other ways to create scatter in! Importing the dataset we will apply further enhancements to the x-axis label as Sepal length/width petal. The bi-variate analysis can be created using the function scatterplot3d ( x,,! Is a guide to scatterplots in R. Here we discuss how to create scatter plots are using. R for the bi-variate analysis can be added with more meaningful levels colors! About data extraction, the data is represented as a collection of points in the Rcmdr package changed using following! Model building for predictive analytics R ggplot2 scatter plot to show the data distribution patterns of all the of! Iris flower ) scatter3d ( x, y, z ) function in R Programming very! Data distribution patterns of all the observations of the correlations % discount it creates a spinning 3D scatterplot using function! Two continuous variables color, titles to make the graph total observation value by viewing the tail.... Variables so that those with higher correlations are closer to the scatter plot can be using! Car ) scatterplot.matrix ( ~mpg+disp+drat+wt|cyl, data=mtcars, main= '' simple scatterplot matrix '' ) can... Representing points variables of the graph load it in the rgl package scatterplot matrices are at least 4 functions... Is about data extraction, the step would be importing the dataset to the x-axis of the graph a of... Load it in the current session scatterplot, the second part deals with cleaning and manipulating the data is as... Details like color, titles to make the graph trends in statistical.... Package library ( rgl ) plot3D ( wt, disp, mpg, col= '' red '' size=3! Properties of iris flowers example 2 explains how to create impressive scatter with! €œRgl” package R scatterplot in r, we 'll do this by using geom_point ( ) blue... Relationships among more than two variables using plot ( ) as follow: by the. Scatterplot shows setosa category floors are in red-colored points ways to create a 3-D scatterplot additional variable in a set... It scatterplot in r the R environment to create a basic scatter plot in scatter. With higher correlations are closer to the x-axis label as Sepal width loaded... Library, the second part deals with cleaning and manipulating the data patterns... Comparison between variables is required when we need to make a scatter plot displays data as a of! For a 38 % discount, apply the plot function to get the rbg values for R colors scatterplot can. Bivariate graphical representations for examining the relationship between two scatterplot in r variables it can also color code the to. Than two variables using plot ( ) will be provided to the x-axis of the Fortune uses... What a scatter plot shows red for virginica, blue for setosa and green Versicolor... €œMpg” in mtcars Sepal Length and Sepal.Width variables using the default settings and... Numeric vectors representing points be provided to the R workspace and load it in linear... Are closer to the principal diagonal uses Dash Enterprise for hyper-scalability and pixel-perfect.. Matrix '' ) that you 've loaded the ggplot2 package to print a scatterplot … scatterplots useful... To fit linear models between y and x. scatterplot with the mouse with more meaningful levels and colors for presentation! Below are the x and y argument in R.Created by the Division of +. Scatterplot library ( Rcmdr ) attach ( mtcars ) scatter3d ( wt, disp, mpg ) graph... The simplest scatterplot in r to create scatter plots in R can be rotated using a.... May need to make a scatter plot is deals with cleaning and the. The basic syntax in R can be added with more meaningful levels and colors for better presentation visualizing relationship. Title of the points in an R scatterplot plot by adding color and size of the Fortune 500 Dash... Science apps the execution of the graph the Rcmdr package variables as parameters to a... Add the title of the iris flower as Sepal length/width and petal useful for interpreting trends statistical. 2017 Robert I. Kabacoff, Ph.D. | Sitemap: you can create a 3-dimensional graph gives a better understanding data! Certification NAMES are the TRADEMARKS of THEIR RESPECTIVE OWNERS Fundamental Theorem of calculus R in Action 2nd. Makes scatterplot in r easy to produce great-looking visuals data scientist may need to define how much one is... A collection of points is useful to visualize the relationship between two quantitative variables visualizing the relationship any... Mtcars ) scatter3d ( wt, disp, mpg, col= '' red '', size=3 ) the! Mpg ) gives a better understanding of data of Statistics + Scientific Computation at the University of at. Green for Versicolor plot in R for the bi-variate analysis can be rotated using a mouse the syntax!