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R Programming Articles
Page 80 of 174
How to create a random sample with values 0 and 1 in R?
It is known that the random sample can be created by using sample function in R. If we want to create a random sample with values 0 and 1 only then there are three different ways to pass them inside the sample function −Creating a vector of 0 and 1Using 0:1Using c(1,2) directly inside the function.Also, we can set replace argument to TRUE or FALSE based on our requirement.Examplesx2
Read MoreHow to multiply two vectors in R as in mathematics?
In mathematics, when two vectors are multiplied the output is a scalar quantity which is the sum of the product of the values. For example, if we have two vectors x and y each containing 1 and 2 then the multiplication of the two vectors will be 5. In R, we can do it by using t(x)%*%y.Example1x1
Read MoreHow to multiply a matrix with a vector in R?
When we multiply a matrix with a vector the output is a vector. Suppose we have a matrix M and vector V then they can be multiplied as M%*%V. To understand the step-by-step multiplication, we can multiply each value in the vector with the row values in matrix and find out the sum of that multiplication.Example1M1
Read MoreHow to perform homogeneity of variance test for two-way anova in R?
In general, we can say that the homogeneity of variance test is the type of test that compares the variance of two or more variables and finds the significant difference between or among them if exists. For a two-way anova, one of the most commonly used homogeneity of variance test is Levene’s Test and it can be easily done with the help of leveneTest function of car package in base R.Consider the below data frame −Exampleset.seed(151) x1F) group 6 0.6593 0.6835 13
Read MoreHow to count the number of occurrences of all unique values in an R data frame?
A data frame in R can have infinite number of unique values and it can also contain many repeated values. Therefore, finding the number of all unique values in the data frame can help us to understand the diversity in the data but this most done in situations where we expect to have repeated elements otherwise it would not make sense. To count the number of occurrences of all unique values, we can use table function along with the unlist as shown in the below examples.Consider the below data frame −Examplex1
Read MoreHow to calculate the number of elements greater than a certain value in a vector in R?
In data analysis, sometimes we need to count the number of values that are greater than or less than a certain value, and this certain value could be a threshold. For example, we might have a vector that contain values for blood pressure of people and we might want check how many values are greater than 120. In this type of situation, we can use length function as shown in the below examples.Examplex11])Output[1] 9 Examplex25])Output[1] 93Examplex35])Output[1] 42Examplex40])Output[1] 108Examplex51])Output[1] 107Examplex65])Output[1] 31Examplex71])Output[1] 21Examplex84])Output[1] 19Examplex9118])Output[1] 11Examplex105000])Output[1] 68
Read MoreHow to generate Bernoulli random variable in R?
Each value in Bernoulli random variable represents success or a failure for a single trial that makes it different from Binomial random variable because a Binomial random variable represents number of success or failure for a number of trials. To generate a Bernoulli random variable, we can use rbinom function but we need to pass 1 for size argument.Examplerbinom(120,1,0.71)Output[1] 1 1 1 1 1 1 0 0 0 1 1 1 1 1 1 1 1 1 1 0 0 0 1 1 1 0 0 0 1 1 1 1 1 1 1 0 1 [38] 1 0 1 1 1 0 0 1 0 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 0 [75] 1 1 0 1 1 1 1 1 0 0 1 0 1 1 1 0 1 1 1 1 1 1 0 1 1 1 0 1 1 0 1 1 1 1 1 1 0 [112] 0 0 1 1 0 1 1 1 1Examplerbinom(120,1,0.1)Output[1] 0 0 0 0 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 1 1 0 [38] 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [75] 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [112] 0 0 0 0 0 0 0 0 0Examplerbinom(120,1,0.91)Output[1] 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [38] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [75] 1 1 0 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 0 1 0 1 1 1 1 1 1 1 1 1 1 1 [112] 1 1 1 1 1 1 1 1 1Examplerbinom(120,1,0.999)Output[1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [38] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [75] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [112] 1 1 1 1 1 1 1 1 1Examplerbinom(120,1,0.099)Output[1] 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [38] 1 0 0 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 [75] 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 [112] 0 0 0 0 0 0 0 0 0Examplerbinom(200,1,0.50)Output[1] 1 1 1 0 1 1 0 1 0 1 1 0 1 0 0 0 0 1 1 1 0 1 1 0 0 0 1 0 1 1 1 1 0 0 1 1 0 [38] 1 1 0 0 1 1 1 1 0 0 1 0 0 1 1 1 1 1 0 1 0 0 0 1 1 0 0 0 1 1 0 1 0 1 1 1 1 [75] 0 1 1 1 1 1 0 1 0 1 1 1 0 0 0 1 1 0 1 0 0 1 0 0 1 1 1 1 0 1 0 1 0 0 0 0 0 [112] 0 0 0 1 1 0 1 0 0 1 1 1 1 1 1 0 1 0 1 1 0 0 1 1 1 0 0 1 1 1 0 0 1 1 1 0 0 [149] 1 0 1 1 0 0 1 1 0 0 0 1 1 1 1 0 0 1 0 1 1 1 0 0 0 0 1 1 0 1 0 1 0 1 1 0 0 [186] 1 1 1 0 1 1 0 0 0 1 1 1 0 1 1Examplerbinom(200,1,0.51)Output[1] 1 1 1 1 0 0 0 1 0 0 1 0 1 0 1 1 0 0 1 1 0 1 0 1 1 1 0 1 0 0 1 1 0 0 0 1 1 [38] 1 1 1 1 0 1 1 1 1 1 1 1 0 0 1 0 1 0 0 1 1 0 0 0 1 0 0 1 0 1 1 1 0 0 1 1 0 [75] 0 1 1 0 0 1 0 0 0 1 0 1 0 1 1 0 1 1 0 1 0 0 0 1 0 1 1 1 0 1 0 0 1 1 1 1 0 [112] 1 1 1 0 0 0 0 0 0 1 0 0 0 1 1 0 1 1 0 1 0 1 1 1 1 1 0 0 0 1 0 1 0 0 0 0 0 [149] 1 1 0 0 0 1 1 0 1 0 0 0 1 1 0 0 0 0 1 1 1 0 1 0 0 1 0 1 0 0 1 1 1 0 1 1 0 [186] 0 1 0 1 1 0 0 1 1 1 1 0 1 1 0Examplerbinom(200,1,0.75)Output[1] 1 0 0 0 1 1 0 1 0 1 1 0 1 1 1 1 1 1 1 0 1 1 0 1 1 1 1 1 1 1 0 1 0 0 1 1 1 [38] 1 0 0 1 1 0 1 1 0 1 1 1 1 1 0 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 [75] 1 0 1 1 0 1 1 1 0 1 1 1 1 1 0 0 1 1 1 1 1 1 1 0 1 1 1 1 0 1 0 1 1 1 1 1 0 [112] 1 1 1 0 0 1 1 0 1 1 0 1 0 1 1 1 0 1 0 1 1 1 0 1 1 1 1 1 1 0 1 1 1 1 1 1 0 [149] 1 1 1 1 1 1 0 1 1 0 0 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 0 1 1 1 1 1 0 1 1 1 1 [186] 1 1 1 1 1 0 0 0 1 1 1 0 1 1 1Examplerbinom(200,1,0.89)Output[1] 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 [38] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 0 1 0 1 1 1 1 1 1 0 1 1 1 1 1 [75] 1 1 1 1 1 1 1 1 1 0 1 1 1 0 0 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 [112] 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 0 1 1 1 0 1 1 1 1 1 1 1 1 0 0 1 0 1 1 [149] 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 0 0 1 1 1 1 1 1 1 1 1 1 1 [186] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1Examplerbinom(200,1,0.05)Output[1] 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [38] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [75] 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [112] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [149] 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 [186] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0Examplerbinom(200,1,0.15)Output[1] 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 [38] 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 [75] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [112] 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 0 0 0 0 0 0 [149] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 0 0 [186] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0Examplerbinom(200,1,0.20)Output[1] 1 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0 0 0 0 0 [38] 0 0 1 1 0 1 1 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1 1 0 0 0 0 0 1 0 0 0 0 1 0 1 [75] 0 0 1 0 0 0 0 1 0 0 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 [112] 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 1 0 1 0 0 0 1 1 0 0 0 1 0 1 1 0 0 0 0 0 1 [149] 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 1 0 0 1 0 0 0 1 0 0 0 [186] 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0Examplerbinom(200,1,0.25)Output[1] 0 1 1 0 0 0 1 1 0 0 1 1 0 0 0 0 1 0 1 0 0 0 1 0 0 0 0 1 0 0 0 1 1 0 0 0 0 [38] 0 1 0 0 0 0 0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [75] 1 0 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 1 0 0 0 1 [112] 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 [149] 0 0 0 0 1 0 0 0 0 1 0 1 0 0 0 1 0 0 0 1 1 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 [186] 0 1 1 0 0 0 0 0 0 1 0 0 0 0 1Examplerbinom(200,1,0.35)Output[1] 0 1 0 0 0 0 1 0 0 1 0 1 0 0 0 1 1 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 [38] 1 0 1 1 0 0 1 0 0 1 1 1 0 1 1 0 1 1 0 0 0 0 0 0 0 0 1 0 1 0 1 0 1 0 0 1 1 [75] 1 1 0 0 0 1 0 0 1 0 0 0 0 0 1 0 1 0 1 1 0 0 1 1 1 0 0 0 0 1 0 0 1 0 1 0 0 [112] 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 1 1 0 1 1 1 1 0 0 1 0 1 1 0 0 0 0 1 1 [149] 1 0 0 1 1 0 1 0 0 0 1 1 0 1 1 0 1 0 1 1 0 0 0 0 0 0 1 0 0 1 0 1 0 1 0 0 0 [186] 0 1 0 0 0 1 0 0 1 1 0 1 0 0 0
Read MoreHow to make all the elements in a list of equal size in R?
We know that a list can multiple elements of different types as well as of different size. For example, a list that contains two elements then one element may contain fifteen elements and the other might have twenty-five elements. In this situation, we might want to fill the first element with ten more elements so that the size of both the elements become equal. This can be done by using lapply function as shown in the below examples.Consider the below list −Exampleset.seed(101) x1
Read MoreHow to remove rows from data frame in R based on grouping value of a particular column?
If we have a grouping column in an R data frame and we believe that one of the group values is not useful for our analysis then we might want to remove all the rows that contains that value and proceed with the analysis, also it might be possible that the one of the values are repeated and we want to get rid of that. In this situation, we can do subsetting of the data frame using negation and single square brackets.Exampleset.seed(1212) x
Read MoreHow to remove everything before values starting after underscore from column values of an R data frame?
If a column in an R data frame contain string values that are separated with an underscore and stretches the size of the column values that also contain common values then it would be wise to remove underscore sign from all the values at once along with the values that is common. This will help us to read the data properly as well as analysis will become easy. For this purpose, we can use gsub functionConsider the below data frame −Exampleset.seed(191) ID
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