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There are multiple ways to save a plot created in R. Base R provides, metafile, bitmap, and postscript options to copy and save the plots created in R but we can also save the plots created with ggplot2 as an SVG file with the help of svglite package. The ggsave function of svglite package does this job easily and we can also define the height and width of the plot inside this function.Examplehead(ToothGrowth) len supp dose 1 4.2 VC 0.5 2 11.5 VC 0.5 3 7.3 VC 0.5 4 5.8 VC 0.5 5 6.4 VC 0.5 6 10.0 VC 0.5 library(ggplot2) library(svglite) ScatterPlotImage
Subsetting is not a difficult thing in R but if we make our code short then it is a little tedious task because we will have to introduce code between codes and that creates confusion. Therefore, we must be very careful while writing a code inside another code. To create a line with subsetting the data frame using ggplot function of ggplot2 can be done by using subset function.Exampleggplot(subset(df,x1 %in% c("Sample1","Sample2","Sample3")))+ + geom_line(aes(x2,x3,group=x1,colour=x1))Output
Basic mathematical operations such as addition, subtraction, multiplication, and division are common for matrices and we often do that but if the matrices are stored as a list in R then these basic calculations are done differently as they are not direct objects. To add or multiply the matrices in a list, we can use Reduce function with the plus (+) or multiply (*) sign and the list name.ExampleMatrices_List
Finding row means help us to identity the average performance of a case if all the variables are of same nature and it is also an easy job. But if some of the columns have different type of data then we have to extract columns for which we want to find the row means. Therefore, we can create a new data frame with row means of the required columns using rowMeans function.Examplerow_means_3.4_cols_df
Splitting a continuous variable is required when we want to compare different levels of a categorical variable based on some characteristics of the continuous variable. For example, creating the salary groups from salary and then comparing those groups using analysis of variance or Kruskal-Wallis test. To split a continuous variable into multiple groups we can use cut2 function of Hmisc package −Exampledf$Salary_Group
There are 7 common non printable characters used in general and each character has its own hexadecimal representation.NamecharactersHexa-decimal representationbell\a0x07Escape\e0x1BForm feed\f0x0CLine feed0x0ACarriage return\r0X0DHorizontal tab\t0X09Vertical tab\v0X0BExample 1import java.util.Scanner; import java.util.regex.Matcher; import java.util.regex.Pattern; public class RegexExample1 { public static void main(String[] args) { Scanner sc = new Scanner(System.in); System.out.println("Enter input text: "); String input = sc.nextLine(); String regex = "\x09"; //Creating a pattern object Pattern pattern = Pattern.compile(regex); //Matching the compiled pattern in the String Matcher matcher = ... Read More
The above error means plot is not being created yet hence abline function cannot be used to draw anything on the plot. Therefore, a plot needs to be created first to use abline function for creating a line or any other thing. Mostly, abline is used to create regression line on the plot, thus we need to create a scatterplot first before using abline.Exampleabline(lm(y~x))Output
To create a correlation matrix plot, we can use ggpairs function of GGally package. For example, if we have a data frame called df that contains five columns then the correlation matrix plot can be created as ggpairs(df). A correlation matrix plot using ggpairs display correlation value as well as scatterplot and the distribution of variable on diagonal.Examplelibrary(GGally) ggpairs(df)Output
If all the columns in an R data frame are numeric then it makes sense to find the mean for each of the columns. This calculation will help us to view how different the values of means are for each of the columns but to make sure that they are significantly different, we will need to run a hypothesis test. To find the column means of a data frame or a matrix we can use colMeans function.ExampleConsider the below data frame −set.seed(9) x1
The important part of a boxplot is Y−axis because it helps to understand the variability in the data and hence, we can remove X−axis labels if we know the data description. To create a boxplot using ggplot2 for single variable without X−axis labels, we can use theme function and set the X−axis labels to blank as shown in the below example.Exampleggplot(df,aes(x=factor(0),y))+geom_boxplot()+theme(axis.title.x=element_blank(),axis.text.x=element_blank(),axis.ticks.x=element_blank())Output