Server Side Programming Articles - Page 1659 of 2646

Some vectors are randomly created and some are not randomly created in R but we can do randomization for both of these types of vectors. Randomization ensures unbiasedness therefore it is necessary especially when the vector is created with an objective that tends to change the result of the analysis. The randomization in R can be simply done with the help of sample function.Randomization of vectors that are not randomly created −> x1 x1 [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 ... Read More

There are two methods to create a vector with repeated values in R but both of them have different approaches, first one is by repeating each element of the vector and the second repeats the elements by a specified number of times. Both of these methods use rep function to create the vectors.ExampleConsider the below examples −> x1 x1 [1] 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 [39] 4 ... Read More

A queue is an abstract data structure that contains a collection of elements. Queue implements the FIFO mechanism i.e the element that is inserted first is also deleted first.Queue cane be one linear data structure. But it may create some problem if we implement queue using array. Sometimes by using some consecutive insert and delete operation, the front and rear position will change. In that moment, it will look like the queue has no space to insert elements into it. Even if there are some free spaces, that will not be used due to some logical problems. To overcome this ... Read More

In data analysis, finding some NA values in a data frame is very common but all the NA values do not create problems if the column that contain NA values is not useful for the analysis. We can replace all NA values to 0 or to any other for the columns that are useful.ExampleConsider the below data frame −> set.seed(99) > x1 x2 x3 x4 x5 df df   x1   x2   x3   x4    x5 1  NA   NA   25    NA 2  5     2   24    f    2 3  NA   ... Read More

The number of words in a sentence could be used for text analysis, therefore, we are required to count them. This can be for a single sentence or for multiple sentences. We can find the number of words in a sentence or in multiple sentences using strsplit with sapply.ExampleConsider the below sentences read as vectors −> x1 x1 [1] "Data Science is actually the Statistical analysis" > sapply(strsplit(x1, " "), length) [1] 7 > x2 x2 [1] "China faced trouble even after controlling COVID-19" > sapply(strsplit(x2, " "), length) [1] 7 > x3 x3 [1] "Corona virus has changed everything ... Read More

While creating plots using ggplot2, the plot area is of square shape but we can change our plot area by setting plot.margin in theme function. This is helpful when we want to decrease the plot area and also when the data points are less.ExampleConsider the below data frame −> set.seed(1) > x y df library(ggplot2)Creating the scatterplot without changing the plot area margins −> ggplot(df,aes(x,y))+ + geom_point()> ggplot(df,aes(x,y))+ + geom_point()+ + theme(plot.margin = unit(c(1,1,1,1), "cm"))> ggplot(df,aes(x,y))+ + geom_point()+ + theme(plot.margin = unit(c(2,2,2,2), "cm"))

Generally, a list in R contains a large number of elements and each element can be of different type which is a great thing about lists. Since we can store type of data as a list element therefore storage and selection to different type of data becomes easier. And we can also select single or multiple elements of the list at a time. This can be done with the help of single square brackets.ExampleConsider the below list −> list_data list_data [[1]] [1] "India" [[2]] [1] "China" [[3]] [1] 21 32 11 [[4]] [1] "a" "b" "c" "d" "e" [[5]] ... Read More

A matrix can have multiple rows and columns like a data frame. As in data frames, we sometimes require to take subsets, the same might be required with matrices. But subsetting matrices data is quite simple as compared to subsetting a data frame.ExampleConsider the below matrix −> M M [, 1] [, 2] [, 3] [, 4] [, 5] [1, ] 1 6 11 16 21 [2, ] 2 7 12 17 22 [3, ] 3 8 13 18 23 [4, ] 4 9 14 19 24 [5, ] 5 10 15 20 25Subsetting columns of matrix M −> M[, ... Read More

When there is a common factor with different levels, the joining of data frames is possible but the result will present all the levels with dplyr. We can make use of left_join function to join the two data frames but the size of the first data frame must be greater than the second data frame if they are not same.ExampleConsider the below data frames −> Class df1 df1 Class 1 Statistics 2 Maths 3 Chemistry 4 Physics 5 Economics 6 Political Science 7 Geography > Subject Age df2 df2 Subject Age 1 Maths 18 2 Chemistry 21 3 Physics 22 ... Read More

Selection of top or bottom elements can be done with the help of head and tail function in R. It is required when we want to understand the data in a vector or perform some calculation for partial data.ExampleConsider the below vectors, we will use head and tail to select top and bottom elements in these vectors by using positive and negative signs. These will have a different way to select the elements.> x x [1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" [20] "t" "u" "v" "w" ... Read More