To create an arrow R, we can use plot function and arrows function. We just need to understand all the coordinate values that should be passed inside the arrows function. For example, if we have two vectors that contains values from 1 to 10 then the arrow can be created by using arrows function as arrows(1,1,10,10).ExampleLive Demo> x y plot(x,y)OutputExample> arrows(1,1,10,10)Output

To check whether a column value is less than or greater than a certain value, we can use with function and the output will be a logical vector representing values with TRUE when the condition is satisfied and FALSE when the condition is not satisfied. For example, if we have a column say x of an R data frame df and we want to check whether any of the values in x is greater than 10 or not then it can be done by using with(df, df$x>10).ExampleConsider the below data frame:Live Demo> set.seed(1002) > x1 y1 z1 df1 df1Outputx1 y1 ... Read More

A data.table object is similar to a data frame object but there are few things that can be specifically applied to a data.table because data.table package functions was defined for a data.table object only. If we want to extract a data.table row as a vector then we can use as.vector function along with as.matrix so that the as.vector can read the row properly.Loading data.table package:> library(data.table)Consider the below vectors and create a data.table object:Example> x1 x2 x3 x4 x5 DT1 DT1Outputx1 x2 x3 x4 x5 1: B C C D E 2: B C D B E 3: B C ... Read More

A dendrogram display the hierarchical relationship between objects and it is created by using hierarchical clustering. In base R, we can use hclust function to create the clusters and the plot function can be used to create the dendrogram. For example, if we want to create the dendrogram for mtcars data then it can be done as shown below:> hc=hclust(dist(mtcars)) > plot(hc)Example1Live Demo> head(mtcars)Outputmpg cyl disp hp drat wt qsec vs am gear carb Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4 Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 ... Read More

To create a row sum and a row product column in an R data frame, we can use rowSums function and the star sign (*) for the product of column values inside the transform function. For example, if we have a data frame df that contains x, y, z then the column of row sums and row product can be created as:transform(df, RowSums=rowSums(df), RowProducts=x*y*z)ExampleConsider the below data frame:Live Demo> set.seed(3251) > x1 y1 z1 a1 b1 df1 df1Outputx1 y1 z1 a1 b1 1 2 4 10 10 5 2 0 9 5 5 8 3 4 7 6 12 9 ... Read More

To create an exponential curve, we can use exp function inside the plot function for the variable that we want to plot. For example, if we have a vector x then the exponential curve for the vector x can be created by using plot(x,exp(x)). We can use the exponential function for the variable that is appropriate based on the objective of the analysis, here we have shown only an example of how it works.Example1Live Demo> x plot(x,exp(x))OutputExample2Live Demo> y plot(y,exp(y))Output

The simple staircase plot can be created by using geom_tile function of ggplot2 package. We just need to use the vector or the column for which we want to create the staircase plot in place of x and y as well. For example, if we have a column say x of an R data frame df then the staircase plot can be created as ggplot(df, aes(x, x))+geom_tile().ExampleConsider the below data frame:Live Demo> x df dfOutputx 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10Loading ggplot2 package and creating staircase ... Read More

When we create a colored barplot using ggplot2 the legend entries are automatically created. If we want to create the plot without those legend entries then theme function can be used. For example, if we have a data frame df that contains x as categorical variable and y as count variable then barplot without legend entries can be created as:ggplot(df, aes(x, y, fill=x))+geom_bar(stat="identity")+theme(legend.position="none")ExampleConsider the below data frame:Live Demo> x y df dfOutputx y 1 A 24 2 B 28 3 C 25 4 D 27 5 E 26Loading ggplot2 package and creating the barplot:> library(ggplot2) > ggplot(df, aes(x, y, fill=x))+geom_bar(stat="identity")Output:Creating ... Read More

The point chart of a categorical has points corresponding to the categories just like the bar chart has bars. If we want to create point chart for categorical variable then we just need to use geom_point function of ggplot2 package. For example, if we have a data frame df that contains categorical column x and frequency column defined sd freq then the point chart for the categories in x can be ggplot(df, aes(x, freq))+geom_point().ExampleConsider the below data frame:Live Demo> set.seed(3521) > x freq df dfOutputx freq 1 B 2 2 C 12 3 A 8 4 D 12 5 C ... Read More

The highest occurring value is called the mode and there can be multiple modes in a variable. If we have multiple modes then we can find the first mode or first highest occurring value by using sort function. For example, if we have a vector x that contains more than two modes then the first mode can be found as:sort(table(df$x), decreasing=TRUE)[1]ExampleConsider the below data frame:Live Demo> set.seed(36521) > x df1 df1Outputx 1 B 2 E 3 A 4 A 5 D 6 E 7 D 8 B 9 B 10 C 11 E 12 D 13 E 14 A 15 ... Read More