Server Side Programming Articles - Page 1535 of 2650

Frequency polygons are the graphs of the values to understand the shape of the distribution of the values. They are useful in comparing different data sets and visualising cumulative frequency distribution of the data sets. In base R, we can use polygon function to create the frequency polygon but first we should create a line plot for the two variables under consideration.ExampleConsider the below vectors x and y −set.seed(999) x

Often, we find that the values that represent factor levels are recorded as numerical values, therefore, we need to convert those numerical values to factor. In this way, we can use the factor column properly in our analysis otherwise R program will treat the factors as numerical values and the analysis output will be incorrect.Example Live Demodata(mtcars) str(mtcars)Output'data.frame': 32 obs. of 11 variables: $ mpg : num 21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ... $ cyl : num 6 6 4 6 8 6 8 4 4 6 ... $ disp: num 160 160 108 258 360 ... $ hp : num 110 110 93 110 175 105 245 62 95 123 ... $ drat: num 3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ... $ wt : num 2.62 2.88 2.32 3.21 3.44 ... $ qsec: num 16.5 17 18.6 19.4 17 ... $ vs : num 0 0 1 1 0 1 0 1 1 1 ... $ am : num 1 1 1 0 0 0 0 0 0 0 ... $ gear: num 4 4 4 3 3 3 3 4 4 4 ... $ carb: num 4 4 1 1 2 1 4 2 2 4 ... mtcars$cyl

Applying for loop to a vector or a list is no different, we can simply use in the usual manner. For example, if we have a list called List and we want to print all the elements of the list then we can use the code for(i in List){print(i)}, here i refers to the vectors in the List.Example Live DemoList

By default, the area covered by legends for a plot created by using plot function is of full size that is 1 (the area size has a range of 0 to 1, where 1 refers to the full size and 0 refers to none). To reduce the size, we can use cex argument with the legend function as shown in the below example.ExampleConsider the below vectors and the plot created between these two vectors −x

Suppose we have a binary tree; we have to check whether its height is balanced or not. We know that for a height balanced tree, for every node in the tree, the absolute difference of the height of its left subtree and the height of its right subtree is 0 or 1.So, if the input is likethen the output will be TrueTo solve this, we will follow these steps −Define a function dfs(), this will take node, if node is null, then −return 0l := 1 + dfs(left of node)r := 1 + dfs(right of node)if |l - r| > ... Read More

Suppose we have a list of points and a number k. The points are in the form (x, y) representing Cartesian coordinates. We can group any two point p1 and p2 if the Euclidean distance between them is

When we find statistical summary of an R data frame, we only get the minimum value, first quartile, median, mean, third quartile, and maximum value but in descriptive there are many other useful measures such as variance, standard deviation, skewness, kurtosis, etc. Therefore, we can use basicStats function of fBasics package for this purpose.Loading fBasics package −library(fBasics)Consider mtcars data in base R −Example Live Demodata(mtcars) head(mtcars, 20)Output          mpg    cyl     disp    hp    drat    wt qsec vs am gear carb Mazda RX4         21.0    6 160.0 110    3.90 ... Read More

Suppose we have a number n, we have to find the number of strings of length n can be generated using the following rules −Each character is a lower case vowel [a, e, i, o, u]"a" may only be followed by one "e""e" may only be followed by any of "a" and "i""i" may not be followed by another "i""o" may only be followed by any of "i" and "u""u" may only be followed by one "a"If the result is very large, mod the result by 10^9 + 7.So, if the input is like n = 2, then the output ... Read More

The R-squared value is the coefficient of determination, it gives us the percentage or proportion of variation in dependent variable explained by the independent variable. To display this value on the scatterplot with regression model line without taking help from any package, we can use plot function with abline and legend functions.Consider the below data frame −Example Live Demoset.seed(1234) x

If a vector contains five values then there will be ten pairwise differences. For example, suppose we have five numbers starting from 1, then the pairwise combinations for these values will be (1,2), (1,3), (1,4), (1,5), (2,3), (2,4), (2,5), (3,4), (3,5), (4,5). Now to find the absolute pairwise differences, we would be need to find the differences between each of these combinations and take the absolute value of the answer hence the result will be 1, 2, 3, 4, 1, 2, 3, 1, 2, 1.Example Live Demox1