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Definition: In a Fibonacci series, the next number would be the summation of its two previous numbers, series starting from 0 and 1.ExamplesPrint a fibonacci series up to num = 10;Series: 1, 2, 3, 5, 8, next is 13 but greater than 10;Approach to solve this problemStep 1: Define a function that accepts a numbers(num) type is int, till then need to print the series.Step 2: Take two initial numbers for the series, i.e., 0 and 1.Step 3: Start a true for loop and declare a third variable to store previous two values.Step 4: Print the summation of two numbers until ... Read More
To find the extremes of a data frame column that is numeric can be done with the help of min and max function but if we want to get the same in single line code then range function can be used. If there are some infinity values in the column then range.default function will be used as shown in the below example.Exampley1
Examplesnum = 125 => 1 + 2 + 5 = 8num = 101 => 1 + 0 + 1 = 2num = 151 => 1 + 5 + 1 = 7Approach to solve this problemStep 1: Define a function that accepts numbers(num); type is int.Step 2: Start a true loop until num becomes 0 and define res:=0.Step 3: Find modulo and add to res.Step 4: Divide num by 10.Step 5: Return res.Programpackage main import "fmt" func findDigitSum(num int) int { res := 0 for num>0 { res += num % 10 num /= 10 } return res } func main(){ fmt.Println(findDigitSum(168)) fmt.Println(findDigitSum(576)) fmt.Println(findDigitSum(12345)) }Output15 18 15
To find the least number of arguments a function expects while using in R can be done with the help of the syntax: length(formals(“function_name”)). For example, to find the number of arguments expected by mutate function of dplyr package can be calculated by using the command length(formals(mutate)) but we need to make sure that the package is loaded.Exampleslibrary(ggplot2) length(formals(ggplot))Output[1] 4 length(formals(boxplot)) [1] 2 length(formals(qnorm)) [1] 5 length(formals(rnorm)) [1] 3 length(formals(rpois)) [1] 2 length(formals(runif)) [1] 3 length(formals(punif)) [1] 5 length(formals(plot)) [1] 3 length(formals(pbinom)) [1] 5 length(formals(qbinom)) [1] 5 length(formals(hist)) [1] 2 length(formals(data)) [1] 7 length(formals(matrix)) [1] 5 length(formals(list)) [1] 0 length(formals(data.frame)) ... Read More
ExamplesInput str = “himalaya” => Reverse String would be like => “ayalamih”Input str = “mountain” => Reverse String would be like => “niatnuom”Approach to solve this problemStep 1: Define a function that accepts a string, i.e., str.Step 2: Convert str to byte string.Step 3: Start iterating the byte string.Step 4: Swap the first element with the last element of converted byte string.Step 5: Convert the byte string to string and return it.Programpackage main import "fmt" func reverseString(str string) string{ byte_str := []rune(str) for i, j := 0, len(byte_str)-1; i < j; i, j = i+1, j-1 { ... Read More
The set.seed helps to create the replicate of the random generation. If the name of the object changes that does not mean the replication will be changed but if we change the position then it will. Here, in the below example x4 in the first random generation and the x_4 in the second random generation with the same set.seed are same but x4 and x4 in both are different.Exampleset.seed(101) x1
ExamplesInput arr = [3, 5, 7, 9, 10, 4] => [4, 10, 9, 7, 5, 3]Input arr = [1, 2, 3, 4, 5] => [5, 4, 3, 2, 1]Approach to solve this problemStep 1: Define a function that accepts an array.Step 2: Start iterating the input array.Step 3: Swap first element with last element of the given array.Step 4: Return array.Programpackage main import "fmt" func reverseArray(arr []int) []int{ for i, j := 0, len(arr)-1; i
If we have two plots generated by using ggplot2 and arranged in a list then we can create them using ggarrange function. For example, if we have two objects p1 and p2 that are stored in the list called named as LIST then those plots can be created in the plot window by using the command ggarrange(plotlist=LIST,widths=c(2,1),labels=c("Scatter","Hist"))ExampleConsider the below data frame −set.seed(21) x
A sparse matrix is a type of matrix that has most of the elements equal to zero but there is no restriction for the number of zero elements. As a general criterion the number of non−zero elements are expected to be equal to the number of rows or number of columns. To create a sparse matrix in R, we can use sparseMatrix function of Matrix package.Example1i
ExamplesInput num = 1432 => output = 2341Input num = 9878 => output = 8789Input num = 6785 => output = 5876Approach to solve this problemStep 1: Define a function that accepts a number (num); type is int.Step 2: Define res = 0 variable and start a loop until num becomes 0.Step 3: Find remainder = num % 10 and make a number.Step 4: Divide num by 10.Step 5: Return res.Programpackage main import "fmt" func reverseNumber(num int) int { res := 0 for num>0 { remainder := num % 10 res = (res * 10) + remainder num /= 10 } return res } func main(){ fmt.Println(reverseNumber(168)) fmt.Println(reverseNumber(576)) fmt.Println(reverseNumber(12345)) }Output861 675 54321