Programming Articles - Page 903 of 3363

The covariance is a mathematical measurement to quantify the variation between of two variables together. That means it tells us how two variables under consideration vary together. If we have two vectors and we want to find the covariance between them then we can use the command mentioned below −cov(“First_Vector”,”Second_Vector”)Example 1Following snippet creates a sample data frame −x1

To apply t test on each row of an R data frame, we can use apply function along with t.test function. For Example, if we have a data frame called DF and we want to apply t test on each row of DF then we can use the command given below −apply(DF,1,t.test)Check out the below Example to understand how it works.ExampleFollowing snippet creates a sample data frame −x

The one sample Kolmogorov-Smirnov test is used to check whether a data set follows certain distribution of not.For Example, if we have a vector called X and we want to know whether values in X follow normal distribution or not then we can use the command given below −ks.test(X,"pnorm")Check out the below Examples to understand how it works.Example 1Following snippet creates a sample data frame −x1

To increase the distance between boxplots created by using ggplot2, we can reduce the widths of the boxplots and hence the distance between the plots will be automatically increased. This will be required when we have large number of categories for which the boxplots are created.Check out the below given example to understand how it can be done.ExampleFollowing snippet creates a sample data frame −Group

The matrices stored in an array cannot directly have zero at lower triangular or upper triangular positions because assignment in arrays is not straight forward. Therefore, to set lower triangular matrices to zero stored in an R array, we can use for loop.Check out the below given example to understand how it can be done.ExampleFollowing snippet creates a sample array −Array

To display X-axis labels with dash in base R plot, we can use axis function and define the labels manually. For this purpose, we can first create the plot without X-axis labels by using the argument xaxt="n" and then use the axis function.Check out the below example to understand how it can be done.ExampleIn order to display X-axis labels with dash in base R plot, use the following code −plot(5, 5)OutputIf you execute all the above given codes as a single program, it generates the following output −In order to display X-axis labels with dash in base R plot, add ... Read More

To combine list elements of different sizes in R, we can use expand.grid function. For Example, if we have a list called LIST that contains elements of different sizes then we can combine those items by using the command given below −expand.grid(LIST)Example 1To combine list elements of different sizes in R, use the following snippet −List1

To find the groupwise cumulative mean, we can use cummean function of dplyr package.For example, if we have a data frame called df that contains a categorical column say Group and a numerical column say Response then the groupwise cumulative mean can be found by using the command given below −df%>%group_by(Group)%>%mutate(CM=cummean(Response))Example 1Following snippet creates a sample data frame −Group

To combine data frames stored in a list in R, we can use full_join function of dplyr package inside Reduce function.For Example, if we have a list called LIST that contains some data frames then we can combine those data frames by using the below command −Reduce(full_join,LIST)Check out the Example given below to understand the Output of this command.ExampleFollowing snippet creates a sample data frame −df1

To create barplot for some top values in an R data frame, we can subset the required top values inside the barplot function.For example, if we have a data frame called df that contains a categorical column say C and a numerical column for frequency defined as F then the barplot for top five values can be created by using the below mentioned command −barplot(df$F[1:5],names.arg=df$C[1:5])ExampleFollowing snippet creates a sample data frame −Category