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Suppose, we have an array of objects that contains data about some students like this −const arr = [{ name: 'A', idNo: 1, marks: { math: 98, sci: 97, eng: 89 } }, { name: 'B', idNo: 2, marks: { math: 88, sci: 87, eng: 79 } }, { name: 'C', idNo: 3, marks: { math: 87, sci: 98, eng: 91 ... Read More
A named vector cannot be directly converted to a list because we would need to un-name the vector names and convert those names to names of the list elements. This can be done by using lapply function function. For example, suppose we have a named vector x then it can be converted to a list by using the command x x1 names(x1) x1OutputA B C D E F G H I J K L M N O P Q R S T U V W X Y Z 1 2 3 4 5 6 7 8 9 10 11 12 ... Read More
If two data frames in R have equal number of columns then we can find the correlation coefficient among the columns of these data frames which will be the correlation matrix. For example, if we have a data frame df1 that contains column x and y and another data frame df2 that contains column a and b then the correlation coefficient between df1 and df2 can be found by cor(df1, df2).Example1Consider the below data frame:Live Demo> x1 x2 df1 df1Output x1 x2 1 39.56630 38.25632 2 39.43689 44.14647 3 40.80479 37.43309 ... Read More
The abline function can give us a straight line from intercept 0 with slope 1 in an existing plot. We would need to pass the coefficients inside the function as abline(coef = c(0,1)). Therefore, we can use this function to add a line starting from bottom left and ending at top right. This is also called diagonal line because it joins the end points on one side with the opposite of the other side.Example> plot(1:10,type="n") > abline(coef=c(0,1))Output:
The mean of row values can be found by using rowwise function of dplyr package along with the mutate function to add the new column of means in the data frame. The rowwise function actually helps R to read the values in the data frame rowwise and then we can use mean function to find the means as shown in the below examples.Example1Consider the below data frame:Live Demo> x1 x2 df1 df1Output x1 x2 1 0 8 2 2 3 3 2 5 4 0 5 5 3 2 6 0 10 7 3 5 8 1 7 9 0 ... Read More
Suppose, we have an array of objects like this −const arr = [ {area: 'NY', name: 'Bla', ads: true}, {area: 'DF', name: 'SFS', ads: false}, {area: 'TT', name: 'SDSD', ads: true}, {area: 'SD', name: 'Engine', ads: false}, {area: 'NSK', name: 'Toyota', ads: false}, ];We are required to write a JavaScript function that takes in one such array as the first argument and an array of string literals as the second argument.Our function should then filter the input array of objects to contain only those objects whose "area" property is included in the array of literals ... Read More
Suppose, we have some data regarding some images in an array like this −const arr = [{ 'image': "jv2bcutaxrms4i_img.png", 'gallery_image': true }, { 'image': "abs.png", 'gallery_image': true }, { 'image': "acd.png", 'gallery_image': false }, { 'image': "jv2bcutaxrms4i_img.png", 'gallery_image': true }, { 'image': "abs.png", 'gallery_image': true }, { 'image': "acd.png", 'gallery_image': false }];We are required to write a JavaScript function that takes in one such array.Our function should remove the objects from the array that have duplicate values for the 'image' property.ExampleThe code for this will be −const arr ... Read More
The central limit theorem says that as the sample size increases the distribution of the sample means approaches normal distribution. Therefore, irrespective of the actual population distribution if we take samples of larger size and find the mean of these samples then the distribution of these sample means will be approximately normal. We can display this in R, by creating the histogram of such type of means.Example1> x y
Suppose, we have an array of values like this −const arr = [ { value1:[1, 2], value2:[{type:'A'}, {type:'B'}] }, { value1:[3, 5], value2:[{type:'B'}, {type:'B'}] } ];We are required to write a JavaScript function that takes in one such array. Our function should then prepare an array where the data is grouped according to the "type" property of the objects.Therefore, for the above array, the output should look like −const output = [ {type:'A', value: [1, 2]}, {type:'B', value: [3, 5]} ];ExampleThe code ... Read More
In a linear model, a residual is the difference between the observed value and the fitted value and it is not different for a general linear model. The difference between linear model and the general linear model is that we use a probability distribution to create a general linear model. If we want to find the residual for a general linear model then resid function can be used just like it is used with the linear model.Example1Consider the below data frame:Live Demo> x1 y1 df1 df1Output x1 y1 1 4 2 2 3 3 3 5 3 4 4 2 ... Read More