A 3D-array is a 3-dimensional array and it is actually a collection of 2D arrays. We can create a 3D-array of a data frame in R by using simplify2array function, this function will break the data frame into arrays that will form a 3D-array.Example1Consider the below data frame:Live Demo> set.seed(254) > x y z a b c df1 df1Outputx y z a b c 1 0 4 6 9 5 5 2 0 5 1 4 2 1 3 0 6 1 4 5 6 4 1 6 3 5 4 12 5 1 9 8 6 6 11 6 ... Read More

To create a frequency table of a string vector, we just need to use table function. For example, if we have a vector x that contains randomly sampled 100 values of first five English alphabets then the table of vector x can be created by using table(x). This will generate a table along with the name of the vector.Example1Live Demo> x1 x1Output[1] "d" "d" "a" "c" "a" "a" "c" "a" "d" "c" "a" "d" "d" "b" "c" "a" "b" "c" "d" [20] "b"Example> table(x1)Outputx1 a b c d 6 3 5 6Example2Live Demo> x2 x2Output[1] "w" "j" "p" "y" "r" ... Read More

A QR code is a barcode which is used to read the information about the object on which it is printed. This helps us to detect the useful information relevant to the object so that we can proceed with the next step depending on the operation. In R, we can create QR code by using qrcode_gen function of qrcode package.Example1Loading qrcode package:> library(qrcode)Creating a QR code for tutorialspoint:> qrcode_gen('www.tutorialspoint.com')Output:Example2> qrcode_gen('www.tutorix.com')Output:Example3> qrcode_gen('www.r-project.org')Output:

The easiest way to create a duplicate column in an R data frame is setting the new column with $ sign and if we want to have a different name then we can simply pass a new name. For example, if we have a data frame df that contains a column x and we want to have a new column x1 having same values as in x then it can be done as df$x1 set.seed(254) > x y z a b c df dfOutputx y z a b c 1 A 0.8709244 9 0.072625990 5.125432 26.84561 2 B 1.7993156 3 ... Read More

The linear interpolation is a method of fitting a curve using linear polynomials and it helps us to create a new data points but these points lie within the range of the original values for which the linear interpolation is done. Sometimes these values may go a little far from the original values but not too far. In R, if we have some missing values then na.approx function of zoo package can be used to replace the NA with linear interpolation method.Example1Loading zoo package:Live Demo> library(zoo) > x1 x1Output[1] 2 2 2 5 2 2 5 NA 2 5Replacing NA ... Read More

A data collection process is one of the initial and very important tasks in a data analysis project and sometimes we miss something. Therefore, we need to collect that data later and add it to the originally collected data. This mistake can be done for matrix data as well, hence we might need to add a new column to original matrix and this can be done by using cbind function.Example1Live Demo> M1 M1Output [, 1] [, 2] [, 3] [, 4] [, 5] [1, ] 1 6 11 16 21 [2, ] 2 7 12 17 22 [3, ... Read More

To add a picture to a plot in base R, we first need to read the picture in the appropriate format and then rasterImage function can be used. The most commonly used format for picture in R is PNG. A picture in PNG format can be added to a plot by supplying the values in the plot where we want to add the picture.ExampleLoading png package:> library(png)Reading png file:> Picture plot(1:10,ty="n")Output:Adding the picture in png file to the above plot:Example> rasterImage(Picture,3,3,7,7)Output:Example> plot(1:10,ty="n") > rasterImage(Picture,5,5,7,7)Output:

Finding group-wise mean is a common thing but if we go for step-by-step analysis then sum of values are also required when we have a categorical variable in our data set. This can be easily done with the help of group_by and summarise_each function of dplyr package.ExampleConsider the below data frame:Live Demo> Group Salary Emp EmpOutputGroup Salary 1 D 28256 2 B 31092 3 A 23147 4 C 28209 5 B 37676 6 C 33374 7 D 44864 8 B 40152 9 A 25843 10 A 40946 11 D 23321 12 A 42854 13 C 36960 14 A 35285 15 ... Read More

Most of the times, unlisting is used to find the mean of list elements but we can also use double-square brackets for the same purpose. The double-square brackets are basically used to access the values in the elements of the list, thus mean function works with those values directly. Look at the below example to understand how it works.ExampleConsider the below list:Live Demo> x xOutput[1] 3 3 3 5 3 1 4 7 5 4 5 9 9 7 4 3 6 2 4 3 3 4 7 4 4 [26] 4 5 3 4 4 3 5 7 2 ... Read More

How to extract the names of vector values from a named vector in R?The names of vector values are created by using name function and the names can be extracted by using the same function. For example, if we have a vector called x that contains five values(1 to 5) and their names are defined as first, second, third, fourth and fifth then the names of values in x can be extracted by using names(x)[x==1].Example1Live Demo> x1 names(x1) x1Outputone two three four 1 2 3 4Example> names(x1)[x1==1]Output[1] "one"Example> names(x1)[x1==2]Output[1] "two" Example> names(x1)[x1==3]Output[1] "three"Example> names(x1)[x1==4]Output[1] "four" Example2Live Demo> x2 x2Output [1] ... Read More