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To check if two vectors are exactly same, we can use identical function.For example, if we have two vectors say x and y then we can find whether both of them are exactly same or not by using the command given below −identical(x,y)Check out the below examples to understand the result of identical function for two vectors.Example 1To check if two vectors are exactly same, use the command given below −x1
To change the outlines color of histogram bars using ggplot2, we can use col argument inside geom_histogram function of ggplot2 package.For Example, if we have a data frame called df that contains a column say X then we can create the histogram of X with different outline color of bars using the below command −ggplot(df,aes(X))+geom_histogram(bins=30,col=I("red"))ExampleFollowing snippet creates a sample data frame −x
To find the ID wise frequency in an R data frame, we can use summarise function of dplyr package after defining the ID with group_by function, also the column for which we want to find the frequency will be placed inside group_by function.Check out the below examples to understand how it can be done.Example 1Following snippet creates a sample data frame −ID
To find the standard deviation for every n number of observations in an R data frame, we can use rollapply function of zoo package.For Example, if we have a data frame called df that contains a column say X containing 100 values then we can create a column with standard deviation of every 10 values by using the below command −df$SD_10
To find the mean of all columns by group, we can use summarise_all function along with mean function after defining the groups with group_by. For example, if we have a data frame called df that contains a grouping column say G and some numerical columns then we can find the mean of all columns by values in grouping column by using the below given command −df%>%group_by(G)%>%summarise_all("mean")Example 1Following snippet creates a sample data frame −Grp
To find the mean of every n values in an R vector, we would first need to convert the vector into matrix with number of rows based for n values then we can use colMeans function.For example, if we have a vector called X that contains hundred values then we can find the mean of every ten value by using the command given below −colMeans(matrix(X,10))Example 1To find the mean of every n values in an R vector, use the command given below −x1
To change the border color of box of a base R plot, we can use box function with col argument where we can pass the color other than black because black is the default color. We first need to create the plot using plot function and then box function will be used as shown in the below examples.Example 1To change the border color of box of a base R plot, use the command given below −plot(1:10) box(col="red")OutputIf you execute the above given command, it generates the following output −Example 2To change the border color of box of a base R ... Read More
To find the most frequent factor value in an R data frame column, we can use names function with which.max function after creating the table for the particular column. This might be required while doing factorial analysis and we want to know which factor occurs the most.Check out the below examples to understand how it can be done.Example 1Following snippet creates a sample data frame −Factor_1
To extract the first row of each matrix stored in a list in R, we can use lapply function. For example, if we have a list called LIST that contains some matrices then we can find the first row of each matrix by using the command given below − lapply(LIST,'[',1,)Check out the below given example to understand how it can be done.ExampleFollowing snippet creates a list of matrices −M1
To extract the outliers of a boxplot, we can use out function along with the boxplot function. For example, if we have a vector called X which contains some outliers then we can extract those outliers by using the command given below − boxplot(df$X, plot=FALSE)$outThis command will not create a plot as plot is set to FALSE.ExampleFollowing snippet creates a sample data frame −df=data.frame(x=rlnorm(25)) dfThe following dataframe is created − x 1 0.5699270 2 3.5812629 3 0.3507882 4 0.1400328 5 0.7239948 6 2.5494114 7 3.1243611 8 5.3207739 9 0.1672539 10 7.6235529 11 0.4950263 12 1.1713592 13 1.6590328 14 ... Read More