R study notes[1]

文章目录

• introducing to R
• references

introducing to R

1. R is an integrated suite involved data handling,storage facility,calculations on arrays,tools for data analysis and so on.
2. running the command R in the terminal of OS can start R software.in R terminal ,to input q() can quit R software.
3. the R source codes can bet puted together into a file,assuming the name is “source.R”, follow with running by source(\"source.R\") in R terminal.
4. objects() is a R command to show all objects created by the R session survived . call rm() for delete a part of these objects.

> rm(x)> objects()[1] \"y\"

5. make a vector is simple,for example, to run the code x<-c(1,2,3,4,5,6,7,4,3,5,8).seq used to generate a sequence like arrange in python.

> x<-c(1,2,3,4,5,6,7,4,3,5,8)> y<-seq(1,8,0.2)> x [1] 1 2 3 4 5 6 7 4 3 5 8> y [1] 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 3.2 3.4 3.6 3.8 4.0 4.2 4.4 4.6 4.8 5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0> 

6. arrange function in R is used for sorting a data frame by one or more variables,must install the package called as dplyr installed with install.packages(\"dplyr\").

> mtcars  mpg cyl disp hp drat wt qsec vs am gear carbMazda RX4  21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4Merc 240D  24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4Merc 280C  17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2Fiat X1-9  27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2> arranged_data <- arrange(mtcars, mpg)> head(arranged_data)  mpg cyl disp hp drat wt qsec vs am gear carbCadillac Fleetwood 10.4 8 472 205 2.93 5.250 17.98 0 0 3 4Lincoln Continental 10.4 8 460 215 3.00 5.424 17.82 0 0 3 4Camaro Z28 13.3 8 350 245 3.73 3.840 15.41 0 0 3 4Duster 360 14.3 8 360 245 3.21 3.570 15.84 0 0 3 4Chrysler Imperial 14.7 8 440 230 3.23 5.345 17.42 0 0 3 4Maserati Bora 15.0 8 301 335 3.54 3.570 14.60 0 1 5 8

7. many of compuations can be applied to vector as follows.

> x [1] 1 2 4 2 5 4 3 4 1 4 55 22> x*8-2 [1] 6 14 30 14 38 30 22 30 6 30 438 174 > arranged_data$wt*2 [1] 10.500 10.848 7.680 7.140 10.690 7.140 7.560 6.870 7.040 6.340 8.140 7.460 6.880 6.920 6.880 6.880 7.690 5.540 5.240 5.750 6.430 5.560 4.930[24] 4.640 6.300 6.380 4.280 3.870 3.230 3.026 4.400 3.670

references

1. https://www.r-project.org/