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Found 26504 Articles for Server Side Programming

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The range function in R provides the minimum and maximum values instead of the difference between the two. Hence, we can find the minimum and maximum by using range function but for a data frame we cannot use it directly. Check out the below examples to understand how it works.Example1Live Demo> set.seed(974) > x1 x2 x3 df1 df1Output x1 x2 x3 1 0 6 10 2 0 7 10 3 3 3 11 4 2 7 9 5 3 2 5 6 3 4 7 7 2 7 7 8 2 8 5 9 0 4 9 10 2 2 ... Read More

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If we find the mean of scientific numbers then the result will be also in scientific notation. We can get rid of this problem by using options(scipen=999), once we will use this code in R console all the inputs that are in scientific notation will be converted to normal numeric form, including any calculation and if we want to go back to the scientific notation then options(scipen=0) can be used.ExampleLive Demo> x1 mean(x1)Output[1] 4.436267e-22Example> options(scipen=999) > mean(x1)Output[1] 0.0000000000000000000004436267ExampleLive Demo> x2 x2Output[1] 0.000000000000000000000000000000000000001010964 [2] 0.000000000000000000000000000068291679999999998 [3] 0.000000000000000000000000006026013000000000181 [4] 0.000000000000000000000000002702241000000000107 [5] 0.000000000000000000000042258669999999998179163 [6] 0.000000000000000000000000000000091949710000000 [7] 0.000000000000000000000000000000000000107406400 [8] 0.000000000000000000000000000000091949710000000 [9] 0.000000000000000000000003463124999999999951636 [10] 0.000000000000000000004305051000000000103323794 ... Read More

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The absolute distance can be found by calculating the difference between column values. And if we want the distance to be absolute then we would be need to use abs function. For example, suppose we have a data frame df that contain columns x and y then the absolute distance can be found by using df$Absolute_Distance set.seed(274) > x1 y1 df1 df1Output x1 y1 1 6 11 2 1 4 3 4 2 4 7 12 5 4 5 6 6 10 7 6 14 8 6 8 9 2 11 10 3 8 11 3 8 12 2 6 ... Read More

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The X Window System is a windowing system for bitmap displays. In R, we can create this graphical display by simply typing x11 in the R console and the graphic interface will pop-up on the right-hand side. We can change the width and height of this display by using the arguments width and height inside x11 call. There are many other arguments of x11 that helps us to change the aesthetic property of the bitmap display. The description of those arguments is as written below:Displaythe display on which the graphics window will appear. The default is to use the value ... Read More

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The boxplot function in base R helps us to create the boxplot without any hustle but this plot is covered with a square bracket and also takes the Y-axis labels on left-hand side. We can get rid of this square bracket without making an impact on the Y-axis labels. For this purpose, we need to use frame.plot = FALSE argument inside the boxplot function.Example1> x boxplot(x,frame.plot=FALSE)Output:Example2> y boxplot(y,frame.plot=FALSE)Output:Example3> z boxplot(z,frame.plot=FALSE)Output:

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Mostly, we start with creating models by including single independent variables effect on the dependent variable and then move on to interaction. But if we are sure that there exists some interaction among variables and we are looking for the interaction effect then only interaction regression model can be created. This can be done by using colon sign between variables to signify the interaction as shown in the below examples.Example1Consider the below data frame:Live Demo> x1 x2 x3 y df1 df1Outputx1 x2 x3 y 1 1 3 10 8 2 0 3 9 11 3 1 1 6 5 4 ... Read More

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The splitting of data frame is mainly done to compare different parts of that data frame but this splitting is based on some condition and this condition can be row values as well. For example, if we have a data frame df where a column represents categorical data then the splitting based on the categories can be done by using subset function as shown in the below examples.Example1Consider the below data frame:Live Demo> Country Ratings df1 df1Output Country Ratings 1 India 1 2 China 2 3 Russia 5 4 Sudan 3 5 India 5 6 China ... Read More

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Plotly in R is a package specifically designed to create highly-interactive and publication-quality charts. The chart can be created by using plot_ly function of the package and there are three main arguments of plot_ly defined as x, y, and type, where x refers to the X-axis, y refers to the Y-axis and type refers to the chart type but the axes values are stored in a data frame or itself a shared.ExampleLoading plotly package:> library(plotly)Consider the below data frame:Live Demo> x y df dfOutputx y 1 United States of America 501 2 United Kingdom 510 3 Republic of China 505Creating ... Read More

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To access columns of data frame in R, we just need to use $ sign but if the data frame is converted to a time series object then all the columns will behave as a time series, hence, we cannot simply use $ sign. For this purpose, we would need to use single square brackets and pass the appropriate column inside it. Look at the below examples to understand how it works.Example 1Consider the below data frame:Live Demo> set.seed(147) > x1 x2 x3 df1 df1Outputx1 x2 x3 1 5 11 4 2 5 5 3 3 4 6 2 4 ... Read More

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To create a function with two inputs, we just need to provide two different arguments inside function. For example, if we want to create a function to find the square of a+b then we can use x and y inside function. Check out the below examples to understand how we can do it.Example1Live Demo> F F(x=1, y=1) > F(x=2, y=3) > F(x=c(1, 2), y=c(2, 3))Output[1] 4 [1] 25 [1] 9 25Example> F(x=rpois(50, 2), y=rpois(50, 7))Output[1] 36 169 121 36 49 100 144 169 144 81 100 256 121 121 36 64 49 225 121 [20] 16 64 100 36 ... Read More