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Server Side Programming Articles
Page 2017 of 2109
How to convert a data frame to data.table in R?
Since operations with data.table are sometimes faster than the data frames, we might want to convert a data frame to a data.table object. The main difference between data frame and data.table is that data frame is available in the base R but to use data.table we have to install the package data.table. We can do this with the help setDT function in the data.table package.ExampleConsider the below data frame −> set.seed(1) > x1 x2 x3 x4 x5 df df x1 x2 x3 x4 x5 1 -0.1264538 1.7189774 2 6 9.959193 2 0.6836433 1.5821363 3 4 7.477968 3 -0.3356286 ...
Read MoreHow to change the axes labels using plot function in R?
In a plot, the axes labels help us to understand the range of the variables for which the plot is created. While creating a plot in R using plot function, the axes labels are automatically chosen but we can change them. To do this, firstly we have to remove the axes then add each of the axes with the labels we want and then create the box for the plot.ExampleConsider the below data −> x y plot(x, y)OutputChanging the axes labels for X and Y axes −> plot(x, y, axes=FALSE)+ + axis(side = 1, at = c(2, 5, 10))+ + ...
Read MoreHow to get row index or column index based on their names in R?
We might prefer to use row index or column index during the analysis instead of using their numbers, therefore, we can get them with the help of grep function. While dealing with a large data set it becomes helpful because large data sets have large number of rows and columns so it is easier to recall them with their indexes instead of numbers. Specifically, column indexes are needed, on the other hand, rows are required in special cases only such as analysing a particular case.ExampleConsider the below data frame −> set.seed(1) > x1 x2 x3 x4 x5 df head(df, 20) ...
Read MoreHow to extract initial, last, or middle characters from a string in R?
In Text analysis, we might want to extract characters from a single string or from a vector of strings. This extraction might be required to create a new string with some specific words required for further analysis. We can do this with the help of str_sub function of stringr package.ExampleConsider the below string −> x1 library(stringr) > str_sub(x1, 1, 8) [1] "Removing" > str_sub(x1, 1, 23) [1] "Removing harmful things" > str_sub(x1, 29, 37) [1] " the road" > str_sub(x1, 30, 37) [1] "the road" > str_sub(x1, -58, -51) [1] "Removing" > str_sub(x1, -58, -1) [1] "Removing harmful things from ...
Read MoreHow to count the number of rows for a combination of categorical variables in R?
When we have two categorical variables then each of them is likely to have different number of rows for the other variable. This helps us to understand the combinatorial values of those two categorical variables. We can find such type of rows using count function of dplyr package.ExampleConsider the CO2 data in base R −> head(CO2, 20) > head(CO2, 20) Plant Type Treatment conc uptake 1 Qn1 Quebec nonchilled 95 16.0 2 Qn1 Quebec nonchilled 175 ...
Read MoreHow to randomize an already created vector in R?
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 MoreHow to replace NA's to a value of selected columns in an R data frame?
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 MoreCircular queues-Insertion and deletion operations in C++
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 MoreHow to count the number of words in a string in R?
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 MoreHow to change plot area margins using ggplot2 in R?
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"))
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