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Found 2038 Articles for R Programming
![Nizamuddin Siddiqui](https://www.tutorialspoint.com/assets/profiles/218290/profile/60_42434-1594357075.jpg)
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To check whether a string is a subset of another string we can use grepl function.Example> Company Job grepl(Job, Company, fixed = TRUE) [1] TRUEHere we are getting TRUE because Tutor is a subset of TutorialsPoint.> grepl(Company, Job, fixed = TRUE) [1] FALSEHere we are getting FALSE because TutorialsPoint is not a subset of Tutor.
![Nizamuddin Siddiqui](https://www.tutorialspoint.com/assets/profiles/218290/profile/60_42434-1594357075.jpg)
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We can use options(scipen=999) to do this.Example> x t.test(x, mu=2000)One Sample t-testdata: x t = -14.212, df = 9, p-value = 1.801e-07 alternative hypothesis: true mean is not equal to 200095 percent confidence interval −151.3501 659.0499sample estimates −mean of x 405.2Here p-value is in scientific notation. Now we can deactivate it as follows −> options(scipen=999) > t.test(x, mu=2000)One Sample t-testdata: x t = -14.212, df = 9, p-value = 0.0000001801 alternative hypothesis: true mean is not equal to 200095 percent confidence interval −151.3501 659.0499sample estimates −mean of x 405.2If we want to activate scientific notation again then it be ... Read More
![Nizamuddin Siddiqui](https://www.tutorialspoint.com/assets/profiles/218290/profile/60_42434-1594357075.jpg)
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Reordering of columns can be done by using square brackets.Example> df = data.frame(matrix(rnorm(20), nrow=5)) > df X1 X2 X3 X4 1 -0.3637644 2.0770246 0.48763128 -0.09019256 2 -3.1758515 2.3173075 0.86846761 0.38396459 3 1.1844641 0.3412267 1.90986295 -1.03493074 4 -0.5953466 1.7211738 -0.90686896 -0.71215313 5 -0.8732530 0.3256303 0.02312328 -0.36993899Let’s say we want to change the order of columns as X3, X2, X4, and X1 then it can be done as shown below −> df[,c(3,2,4,1)] X3 X2 X4 X1 1 0.48763128 2.0770246 -0.09019256 -0.3637644 2 0.86846761 2.3173075 0.38396459 -3.1758515 3 1.90986295 0.3412267 -1.03493074 1.1844641 4 -0.90686896 1.7211738 -0.71215313 -0.5953466 5 0.02312328 0.3256303 -0.36993899 -0.8732530
![Nizamuddin Siddiqui](https://www.tutorialspoint.com/assets/profiles/218290/profile/60_42434-1594357075.jpg)
681 Views
There are three ways to find the index of an element in a vector.Example> x x [1] 8 10 9 6 2 1 4 7 5 3Using which> which(x == 6)[[1]] [1] 4Here we found the index of 6 in vector x.Using match> match(c(4,8),x) [1] 7 1Here we found the index of 4 and 8 in vector x.Using which with %in% > which(x %in% c(2,4)) [1] 5 7Here we found the index of 2 and 4 in vector x.
![Nizamuddin Siddiqui](https://www.tutorialspoint.com/assets/profiles/218290/profile/60_42434-1594357075.jpg)
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This can be done simply by using sample function.Example> df = data.frame(matrix(rnorm(20), nrow=5)) > df X1 X2 X3 X4 1 -0.3277833 -0.1810403 0.2844406 -2.9676440 2 0.8262923 0.4334449 0.4031084 -1.9278049 3 -0.1769219 -0.1583660 -0.2829540 -0.1962654 4 1.0357773 0.9326049 0.3250011 -1.8835882 5 -1.0682642 -0.6589731 -0.4783144 -0.2945062Let’s say we want to select 3 rows randomly then it can be done as follows −> df[sample(nrow(df), 3), ] X1 X2 X3 X4 2 0.8262923 0.4334449 0.4031084 -1.9278049 1 -0.3277833 -0.1810403 0.2844406 -2.9676440 5 -1.0682642 -0.6589731 -0.4783144 -0.2945062
![Nizamuddin Siddiqui](https://www.tutorialspoint.com/assets/profiles/218290/profile/60_42434-1594357075.jpg)
148 Views
We can do this by defining the newname as shown below −> Samp Samp sample.1.100..10. 1 47 2 63 3 57 4 16 5 53 6 7 7 54 8 2 9 13 10 14 > colnames(Samp) Samp Sampled Values 1 47 2 63 3 57 4 16 5 53 6 7 7 54 8 2 9 13 10 14 Since we only have one column in the data frame, so it is sufficient to use the object name.
![Nizamuddin Siddiqui](https://www.tutorialspoint.com/assets/profiles/218290/profile/60_42434-1594357075.jpg)
334 Views
The easiest way to add zeros before numbers is by using paste0 functionExample> ID Gender Lens data data ID Gender Lens 1 25499 1 0.8 2 25500 2 1.2 3 25501 2 1.0 4 25502 1 2.0 5 25503 2 1.8 6 25504 1 1.4Let’s say we want to add 00 before every ID.It can be done by using paste0 function as follows −> IDs newdata newdata IDs Gender Lens 1 0025499 1 0.8 2 0025500 2 1.2 3 0025501 2 1.0 4 0025502 1 2.0 5 0025503 2 1.8 6 0025504 1 1.4
![Nizamuddin Siddiqui](https://www.tutorialspoint.com/assets/profiles/218290/profile/60_42434-1594357075.jpg)
2K+ Views
We can do this by using aggregate function or with the help tapplyExample> x x Category Frequency 1 Graduation 12 2 Graduation 19 3 Post-Graduation 15 4 Graduation 20 5 PhD 25 6 Post-Graduation 13 7 PhD 14Using aggregate> aggregate(x$Frequency, by=list(Group=x$Category), FUN=sum) Group x 1 Graduation 51 2 PhD 39 3 Post-Graduation 28 Using tapply > tapply(x$Frequency, x$Category, FUN=sum) Graduation PhD Post-Graduation 51 39 28