Server Side Programming Articles - Page 1537 of 2650

Suppose we have a positive number n, we have to check whether n can be written as the sum of unique positive factorial numbers or not.So, if the input is like n = 144, then the output will be True, as 4! + 5! = 24 + 120 = 144To solve this, we will follow these steps −fact := 1res := a new listx := 2while fact = res[i], thenn := n - res[i]return true when n is same as 0Let us see the following implementation to get better understanding −Example Live Democlass Solution: def solve(self, n):    fact = 1 ... Read More

Suppose we have two values 0 and 1 then how many combinations of these values are possible, the answer is 8 and these combinations are (0,0), (1,0), (0,1), (1,1). In R, we can use expand.grid function to create these combinations but to save it in a data frame, we would need to use as.data.frame function.Example Live Demodf1

A standard normal distribution has mean equals to zero and the standard deviation equals to one. Therefore, when we plot it with three sigma limits, we have six points on the X-axis referring to the plus and minus around zero. If the limits are defined then the plotting can be shown with larger width and that will change the display of the curve. We can do this by creating a sequence for the length of the standard normal variable and its density.Consider the below vectors corresponding to the limits and density−x

The correlation coefficient value size in correlation matrix plot created by using corrplot function ranges from 0 to 1, 0 referring to the smallest and 1 referring to the largest, by default it is 1. To change this size, we need to use number.cex argument. For example, if we want to decrease the size to half then we can use number.cex = 0.5.ExampleConsider the below matrix − Live Demoset.seed(99) M corrplot(cor(M), addCoef.col="black")OutputChanging the size of correlation coefficient value to 0.75 −corrplot(cor(M), addCoef.col="black", number.cex=0.75)OutputChanging the size of correlation coefficient value to 0.30 −> corrplot(cor(M), addCoef.col="black", number.cex=0.30)OutputRead More

Suppose we have a list of sorted numbers called nums, we have to find the sum of the absolute differences between every pair of numbers in the given list. Here we will consider (i, j) and (j, i) are different pairs. If the answer is very large, mod the result by 10^9+7.So, if the input is like nums = [2, 4, 8], then the output will be 24, as |2 - 4| + |2 - 8| + |4 - 2| + |4 - 8| + |8 - 2| + |8 - 4|.To solve this, we will follow these steps −m ... Read More

We often need groupwise mean in data analysis, especially in situations where analysis of variance techniques is used because these techniques helps us to compare different groups based on their measures of central tendencies and measures of variations. It can be done by using aggregate function so that the output can be saved in a data frame object. In the below examples, we can see how it can be done and also check the final object type.ExampleConsider the below data frame − Live Demoset.seed(109) Salary

The concatenation of vector to a list simply means adding an external vector to the list we already have. For this purpose, we need to defined the vector with list function so that the R program understands that we are adding a list object to another list, otherwise the vector entries will be considered as separate vectors to be added in the list. To understand this in a better way, check out the below examples.Example Live DemoConsider the below list −List1

Suppose we have a robot, that is currently sitting in at position (0, 0) (Cartesian plane). If we have list of its moves that it can make, containing N(North), S(South), W(West), and E(East). We have to check whether it can reach at destination coordinate (x, y).So, if the input is like moves = ['N', 'N', 'E', 'E', 'S'], (x, y) = (2, 1), then the output will be True, To solve this, we will follow these steps −temp_coord := [0, 0]for each move in moves, doif move is same as "N", thentemp_coord[1] := temp_coord[1] + 1otherwise when move is same ... Read More

Suppose we have a string containing letters of three types, R, B, and dot(.). Here R stands for our current position, B stands for a blocked position, and dot(.) stands for an empty position. Now, in one step, we can move to any adjacent position to our current position, as long as it is valid (empty). We have to check whether we can reach either the leftmost position or the rightmost position.So, if the input is like s = "...........R.....BBBB.....", then the output will be True, as R can reach left most position, because there is no block.To solve this, ... Read More

Suppose we have some parameters P, O, E, T. If we have P dollars in principal that we want to invest the stock market. The stock market alternates between first returning E and then O percent interest per year, we have to check how many years it would take to reach at least T dollars.So, if the input is like P = 200, O = 10, E = 25, T = 300, then the output will be 3 as in the first year we will get interest 25%, so end up with 200+50 = 250, then next year we will ... Read More