To decrease the width of bars for plotly bar chart, we can use layout function and set the autosize argument to FALSE.For example, if we have a data frame called that contains a categorical column C and a numerical column Count then bar chart with decreased width of the bars can be created by using the below command −plot_ly(df,x=x,y=y,type="bar")%>%layout(autosize=F)ExampleFollowing snippet creates a sample data frame −x

To convert a table into matrix in R, we can use apply function with as.matrix.noquote function.For example, if we have a table called TABLE then we can convert it into a matrix by using the command given below −apply(as.matrix.noquote(TABLE),2,as.numeric)Example 1Following snippet creates a dataframe −x1

To create a scatterplot with colors as group, we can define the colors in col argument as characters.For Example, if we have two vectors then we can create scatterplot between x and y with red and blue colors for x and y value by using the below mentioned command −plot(x,y,col=as.character(cut(x,2,labels=c("red","blue"))))ExampleFollowing snippet creates a sample data frame −x

To create a rolling mean column by displaying means to corresponding values in R data frame, we can use ave function with rep function.For Example, if we have a data frame called df that contains a numerical column say X then we can create a rolling mean column for every 5 values by using the below mentioned command −df$Rolling_M_5

To combine two columns in R data frame with comma separation, we can use paste function with sep argument.For Example, if we have two columns say X and Y in a data frame called df then we can combine the values of these two columns in a new column with comma separation by using the below mentioned command −df$Combined

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