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The width of the line chart can be increased by using size argument inside geom_line aesthetics of ggplot2. For example, if we have a data frame df that contains two numerical columns x and y, and we want to create a line chart between the two with larger width then it can be done as −ggplot(df)+geom_line(aes(x,y,size=2))ExampleConsider the below data frame − Live Demox
If we want to save a list to a text file then first step would be converting that list to a data frame then write.table function can be used for saving. For example, if we have a list defined as LIST and it has elements each containing 50 values then we can convert it to a data frame as −LIST_df=as.data.frame(do.call(cbind,LIST))Now we can save it as −write.table(LIST_df,"LIST.txt")ExampleConsider the below list − Live Demox1
In European countries, a comma is used to separate the integral part of a number from the decimal part. Thus, we might want to create data or perform calculations with comma as decimal separator. In R, we can do this by just using the code options(OutDec=", "). Once we will type this in R console, all the numerical values with decimals will be printed with commas in place of dots.Example Live Demooptions(OutDec=", ") rnorm(10)Output[1] 0, 14421957 -0, 24152088 -0, 05215867 -0, 40577010 0, 19806357 -1, 49349808 [7] 0, 91085263 0, 43550033 2, 64009603 1, 17177332Example Live Demornorm(50)Output[1] -0, 56186368 -2, 11404777 0, ... Read More
The probability density distribution is the synonym of probability density function. It is a function that defines the density of a continuous random variable. In R, we can use density function to create a probability density distribution from a set of observations.Example Live Demox1
If we have a categorical column that has two or more categories and a numerical column then we might want to divide the one category numerical value from other category numerical value. This can be done by using divide sign / but we need to use the proper subset of the values.ExampleConsider the below data frame − Live Demox1
To find the correlation of groups, we can use cor function but it cannot be directly used.For this purpose, we first need to set they key for group column of data table object. For example, if we have a data.table DT with one numerical column defined as x and one group column defined as Group having 4 groups as a, b, c, and d then the correlation of numerical values for groups a and b can be found as −setkey(DT, Group) cor(DT["a"]$x, DT["b"]$x)Loading data.table package −library(data.table)ExampleConsider the below data.table object −xRead More
The upper triangular matrix can be replaced with lower triangular matrix by transposing the whole matrix and extracting upper triangular matrix from it then storing it in the original matrix. For example, if we have a matrix M then upper triangular matrix of M can be replaced with lower triangular matrix by using the below code −M1[upper.tri(M1)]
If we have duplicate rows in an R data frame then we can remove them by using unique function with data frame object name. And if we want to order the data frame with duplicate rows based on a numerical column then firstly unique rows should be found then order function can be used for sorting as shown in the below examples.ExampleConsider the below data frame − Live Demox1
We can create table of frequencies of a vector element by using table function and the ordering can be done by using sort function. If we want to order the frequencies in decreasing order then decreasing argument can be used. For example, if we have a vector x then the table of ordered frequencies can be created as sort(table(x)).Example Live Demox1
SVM is a supervised machine learning algorithm which can be used for both classification or regression challenges but mostly we use it for classification. The classification using svm can be done for two or more categories as well. In R, we can use simply use svm function of e1071 package.ExampleConsider the iris data − Live Demostr(iris)Output'data.frame': 150 obs. of 5 variables: $ Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ... $ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ... $ Petal.Length: num 1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 ... Read More