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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:> 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 3 ... Read More
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:> 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 B ... 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.Example1> M1 M1Output [, 1] [, 2] [, 3] [, 4] [, 5] [1, ] 1 6 11 16 21 [2, ] 2 7 12 17 22 [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:> library(zoo) > x1 x1Output[1] 2 2 2 5 2 2 5 NA 2 5Replacing NA with ... Read More
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
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.Example1> 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 6Example2> x2 x2Output[1] "w" "j" "p" "y" "r" "m" "y" ... Read More
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:> 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 1 ... Read More
The main statistical parameters that are used to create a boxplot are mean and standard deviation but in general, the boxplot is created with the whole data instead of these values. If we don’t have whole data but mean and standard deviation are available then the boxplot can be created by finding all the limits of a boxplot using mean as a measure of central tendency.ExampleConsider the below data frame:> df dfOutputmean sd Category 1 24 1.1 A 2 25 2.1 B 3 27 1.5 C 4 24 1.8 DLoading ggplot2 package and creating the boxplot of each category in ... Read More
We can say that orthogonal is a synonym of perpendicular. If the inner product (inner product is generalization of dot product) of two polynomials is zero then we call them orthogonal polynomials. In R, we can find the orthogonal product by using poly function as shown in the below examples.Example1> x xOutput[1] 1.53798786 -0.85463326 2.39444451 0.82559418 -2.22197322 -1.04243823 [7] -0.04693054 -0.68691236 -1.63040923 -1.42408865Example> orthogonal_x orthogonal_xOutput 1 2 [1, ] 0.41743651 -0.01687537 [2, ] -0.12158589 -0.21414848 [3, ] 0.61038362 0.54027924 [4, ] ... Read More
Suppose we have a positive integer value; we have to find its corresponding column title as appear in a spread sheet. So [1 : A], [2 : B], [26 : Z], [27 : AA], [28 : AB] etc.So, if the input is like 29, then the output will be AC.To solve this, we will follow these steps −while n is non-zero, do −n := n − 1res := res + n mod 26 + ASCII of 'A'n := n / 26reverse the array resreturn resLet us see the following implementation to get better understanding −Example#include using namespace std; class ... Read More