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Sometimes we have vectors with NA values, also there might be a situation that one of vector having an NA at a position and the other vector has the numerical values at the same position. For example, 1, 2, NA and 1, 2, 3. In this case, we might want to combine these two vectors to make a single vector. This can be done by using coalesce function of dplyr package.Example> library(dplyr) > x1 x1Output[1] NA 4 NA 1 2 NA 4 1 4 1 2 3 1 4 2 2 NA 2 2 1Example Live Demo> y1 y1Output[1] 1 2 ... Read More
Sometimes we want to determine the multiplication of all the elements of a vector just like the sum. This might be required to test the changes in the mathematical operations that can be applied to a numerical vector. In base R, we have prod function which works same as sum but give us the multiplication of all the elements of a vector.Example Live Demo> v1 v1Output[1] 1 2 3 4 5> prod(v1)Output[1] 120 Example Live Demo> v2 v2Output[1] -0.500466629 0.394771317 0.575743107 0.026982141 0.812697502 [6] 0.995708241 2.198243938 -0.008609976 -0.931337300 -0.073743225> prod(v2)Output[1] 3.228448e-06Example Live Demo> v3 v3Output[1] 1.7328245888 -0.5772304935 2.5161349689 3.0401656274 0.1669773313 [6] -0.0001252235 0.7649984733 ... Read More
In general, the concatenation of numerical vectors and string results in a vector of strings in R. For example, if we want to concatenate 1, 2, 3 with Tutorialspoint using paste function then it will result in a vector as: "Tutorialspoint 1" "Tutorialspoint 2" "Tutorialspoint 3". But if we want it to return as "Tutorialspoint 1 2 3" then we need to use collapse argument with paste function.Example1> x1Output[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J"> y1Output[1] 1 9 6 3 8 1 8 5 9 1 2 8 3 8 4 5 10 1 6 3 ... Read More
A matrix can be converted into a pixel’s image of matrix. It is defined as the area of the matrix which contains pixels with equal or different sizes of left, right, bottom and upper.We can create this by using image function and its argument useRaster with the matrix data.Example Live Demo> M par(mar=c(5,5,5,5)) > image(M,useRaster=TRUE,axes=FALSE)Output> par(mar=c(10,10,10,10)) > image(M,useRaster=TRUE,axes=FALSE)Output> par(mar=c(2,2,2,2)) > image(M,useRaster=TRUE,axes=FALSE)OutputPixel matrix with grey color −> image(M,axes=FALSE,col=grey(seq(0,1,length=180)))Output
When we create a bar graph using ggplot2, the color of the bars is dark grey but it can be changed to different colors or we can also give different shades of grey to them. This will be helpful if we are plotting a pattern of categorical data. For example, plotting educational level on X-axis with frequencies of years of experience on Y-axis. We can do this by using scale_fill_grey function of ggplot2 package.ExampleConsider the below data frame − Live Demo> x Freq df dfOutput x Freq 1 A 14 2 B 12 3 C 13 4 D 15> library(ggplot2) > ggplot(df, ... Read More
In base R, the barplot function easily creates a barplot but if the number of bars is large or we can say that if the categories we have for X-axis are large then some of the X-axis labels are not shown in the plot. Therefore, if we want them in the plot then we need to use las and cex.names.ExampleConsider the below data and bar graph − Live Demo> x names(x) barplot(x)OutputShowing all the X-axis labels −> barplot(x,las=2,cex.names=0.5)Output
Every month have common dates except few such as February do not have 30 or 31 and even 29 in some years and there are months that contain 30 days while some contains 31 days. Therefore, finding a date say the first date, a middle date, or a last date is not an easy task but it can be done with the help of seq function in base R.Examples Live Demo> seq(as.Date("2020-01-01"), length=12, by="1 month")Output[1] "2020-01-01" "2020-02-01" "2020-03-01" "2020-04-01" "2020-05-01" [6] "2020-06-01" "2020-07-01" "2020-08-01" "2020-09-01" "2020-10-01" [11] "2020-11-01" "2020-12-01"Example Live Demo> seq(as.Date("2020-01-01"), length=36, by="1 month") Output[1] "2020-01-01" "2020-02-01" "2020-03-01" "2020-04-01" "2020-05-01" [6] ... Read More
We know that, R is a case sensitive programming language, hence matching strings of different case is not simple. For example, if a vector contains tutorialspoint and the other contains TUTORIALSPOINT then to check whether the strings match or not, we cannot use match function directly. To do this, we have to convert the lowercase string to uppercase or uppercase to lowercase with the match function.Examples Live Demo> x1 x1Output[1] "z" "v" "r" "y" "z" "l" "v" "t" "f" "p" "p" "z" "e" "b" "a" "o" "m" "d" [19] "e" "l" "y" "y" "u" "u" "w" "b" "a" "j" "n" "v" ... Read More
When we perform a t test in R and the difference between two groups is very large then the p-value of the test is printed as 2.2e – 16 which is a printing behaviour of R for hypothesis testing procedures. The actual p-value can be extracted by using the t test function as t.test(“Var1”, ”Var2”, var.equal=FALSE)$p.value. This p-value is not likely to be the same as 2.2e – 16.Example1 Live Demo> x1 y1 t.test(x1, y1, var.equal=FALSE)Output Welch Two Sample t-test data: x1 and y1 t = -3617.2, df = 10098, p-value < 2.2e-16 alternative hypothesis: true difference in means is not ... Read More
Sometimes we want to combine column values of two columns to create a new column. This is mostly used when we have a unique column that maybe combined with a numerical or any other type of column. Also, we can do this by separating the column values that is going to be created with difference characters. And it can be done with the help of apply function.ExampleConsider the below data frame − Live Demo> ID Country df1 df1Output ID Country 1 1 UK 2 2 UK 3 3 India 4 4 USA 5 5 USA 6 6 UK 7 7 Nepal 8 ... Read More