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%md
# R jupyter kernel in sage worksheet
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%auto
ir = jupyter("ir")
%default_mode ir
︡1bb793b0-2c4a-455d-887d-7df00222144a︡{"html":"\n\n\n\n\n\n\n\n\n\n
\n\n\n\n"}︡{"done":true}︡
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R.version.string
︡dd3e5f3c-190b-4787-b639-f6328b74a09c︡{"stdout":"Out [2]: "}︡{"html":"'R version 3.2.2 (2015-08-14)'"}︡{"done":true}︡
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ax <- c(0,5,8,8)
ay <- c(2,3,5,3)
df <- data.frame(ax,ay)
df
︡c5937007-7af0-4a7a-be26-29cfd9e91159︡{"stdout":"Out [3]: "}︡{"file":{"filename":"/tmp/tmpVifJvz.png","show":true,"text":null,"uuid":"54adffc0-4cc4-4d7b-bf17-1c8f497d89da"},"once":false}︡{"done":true}︡
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R.version.string
︡201d09b6-6fff-4066-8a28-13fce7347ab6︡{"stdout":"Out [4]: "}︡{"html":"'R version 3.2.2 (2015-08-14)'"}︡{"done":true}︡
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# Motor Trend sample data
# https://stat.ethz.ch/R-manual/R-devel/library/datasets/html/mtcars.html
str(mtcars)
︡706b26c7-b37a-47b3-8c3f-ed113533f87b︡{"html":"'data.frame':\t32 obs. of 11 variables:\n $ mpg : num 21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...\n $ cyl : num 6 6 4 6 8 6 8 4 4 6 ...\n $ disp: num 160 160 108 258 360 ...\n $ hp : num 110 110 93 110 175 105 245 62 95 123 ...\n $ drat: num 3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...\n $ wt : num 2.62 2.88 2.32 3.21 3.44 ...\n $ qsec: num 16.5 17 18.6 19.4 17 ...\n $ vs : num 0 0 1 1 0 1 0 1 1 1 ...\n $ am : num 1 1 1 0 0 0 0 0 0 0 ...\n $ gear: num 4 4 4 3 3 3 3 4 4 4 ...\n $ carb: num 4 4 1 1 2 1 4 2 2 4 ...\n
"}︡{"done":true}︡
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# model car mpg as linear function of wt (1000 lbs) and number of cylinders
model <- lm(mpg ~ wt + cyl, data = mtcars)
summary(model)
︡949fe533-ed23-4a91-8c09-ae1415883b36︡{"stdout":"Out [6]: "}︡{"stdout":"\nCall:\nlm(formula = mpg ~ wt + cyl, data = mtcars)\n\nResiduals:\n Min 1Q Median 3Q Max \n-4.2893 -1.5512 -0.4684 1.5743 6.1004 \n\nCoefficients:\n Estimate Std. Error t value Pr(>|t|) \n(Intercept) 39.6863 1.7150 23.141 < 2e-16 ***\nwt -3.1910 0.7569 -4.216 0.000222 ***\ncyl -1.5078 0.4147 -3.636 0.001064 ** \n---\nSignif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n\nResidual standard error: 2.568 on 29 degrees of freedom\nMultiple R-squared: 0.8302,\tAdjusted R-squared: 0.8185 \nF-statistic: 70.91 on 2 and 29 DF, p-value: 6.809e-12\n"}︡{"done":true}︡
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# scatterplots
plot(mtcars[c('mpg','wt','cyl')])
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# r error message
model2 <- lm(mpg ~ badcol, data = mtcars)
︡1b1a7fa2-c357-48f1-a4ac-807912feee96︡{"html":"Error in eval(expr, envir, enclos): object 'badcol' not found\nTraceback:\n
"}︡{"html":"1. lm(mpg ~ badcol, data = mtcars)
"}︡{"html":"2. eval(mf, parent.frame())
"}︡{"html":"3. eval(expr, envir, enclos)
"}︡{"html":"4. stats::model.frame(formula = mpg ~ badcol, data = mtcars, drop.unused.levels = TRUE)
"}︡{"html":"5. model.frame.default(formula = mpg ~ badcol, data = mtcars, drop.unused.levels = TRUE)
"}︡{"html":"6. eval(predvars, data, env)
"}︡{"html":"7. eval(expr, envir, enclos)
"}︡{"done":true}︡
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# autocomplete with r jupyter kernel
# put cursor at the $ and press TAB
# you should see something like the
# image in the next cell
model$
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%sage
salvus.file('r-completion.png')
︡5d1fdabe-e725-4639-b53f-d1483a724575︡{"file":{"filename":"r-completion.png","show":true,"text":null,"uuid":"c58ec5c0-da0f-4205-9673-116dec22d014"},"once":false}︡{"done":true}︡
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