CoCalc Public Filestmp / Welcome.ipynbOpen with one click!
Author: William A. Stein
In [1]:
2 + 3 summary(c(1,2,7))
5
Min. 1st Qu. Median Mean 3rd Qu. Max. 1.000 1.500 2.000 3.333 4.500 7.000

Welcome to rnotebook.io!

If you've never used a Notebook environment before, read on!

Otherwise, here's some stuff you might want to know:

  • This environment is preloaded with R and over three thousand R packages.
  • You can return and edit it any time, forever.
  • This is a BETA service. We're rapidly improving it.

Right now, you're using rnotebook.io without logging in. As a result, there are some restrictions on what you can do:

  • RAM consumption and disk space are limited.
  • There's no network access.

We will start lifting these restrictions in the free and paid accounts shortly.

Please send feedback (bugs, problems, suggestions) to [email protected].

Enjoy!

Getting started

Notebooks let you mix code, documentation and graphics. The following cell contains the traditional 'Hello, world!' greeting. Click it, then execute it by pressing Shift-Enter.

In [2]:
print("Hello, world!")
[1] "Hello, world!"

We're working in R, so you might want to play with one of the built-in datasets. Let's check out mtcars.

In [3]:
mtcars
mpgcyldisphpdratwtqsecvsamgearcarb
Mazda RX421.0 6 160.0110 3.90 2.62016.460 1 4 4
Mazda RX4 Wag21.0 6 160.0110 3.90 2.87517.020 1 4 4
Datsun 71022.8 4 108.0 93 3.85 2.32018.611 1 4 1
Hornet 4 Drive21.4 6 258.0110 3.08 3.21519.441 0 3 1
Hornet Sportabout18.7 8 360.0175 3.15 3.44017.020 0 3 2
Valiant18.1 6 225.0105 2.76 3.46020.221 0 3 1
Duster 36014.3 8 360.0245 3.21 3.57015.840 0 3 4
Merc 240D24.4 4 146.7 62 3.69 3.19020.001 0 4 2
Merc 23022.8 4 140.8 95 3.92 3.15022.901 0 4 2
Merc 28019.2 6 167.6123 3.92 3.44018.301 0 4 4
Merc 280C17.8 6 167.6123 3.92 3.44018.901 0 4 4
Merc 450SE16.4 8 275.8180 3.07 4.07017.400 0 3 3
Merc 450SL17.3 8 275.8180 3.07 3.73017.600 0 3 3
Merc 450SLC15.2 8 275.8180 3.07 3.78018.000 0 3 3
Cadillac Fleetwood10.4 8 472.0205 2.93 5.25017.980 0 3 4
Lincoln Continental10.4 8 460.0215 3.00 5.42417.820 0 3 4
Chrysler Imperial14.7 8 440.0230 3.23 5.34517.420 0 3 4
Fiat 12832.4 4 78.7 66 4.08 2.20019.471 1 4 1
Honda Civic30.4 4 75.7 52 4.93 1.61518.521 1 4 2
Toyota Corolla33.9 4 71.1 65 4.22 1.83519.901 1 4 1
Toyota Corona21.5 4 120.1 97 3.70 2.46520.011 0 3 1
Dodge Challenger15.5 8 318.0150 2.76 3.52016.870 0 3 2
AMC Javelin15.2 8 304.0150 3.15 3.43517.300 0 3 2
Camaro Z2813.3 8 350.0245 3.73 3.84015.410 0 3 4
Pontiac Firebird19.2 8 400.0175 3.08 3.84517.050 0 3 2
Fiat X1-927.3 4 79.0 66 4.08 1.93518.901 1 4 1
Porsche 914-226.0 4 120.3 91 4.43 2.14016.700 1 5 2
Lotus Europa30.4 4 95.1113 3.77 1.51316.901 1 5 2
Ford Pantera L15.8 8 351.0264 4.22 3.17014.500 1 5 4
Ferrari Dino19.7 6 145.0175 3.62 2.77015.500 1 5 6
Maserati Bora15.0 8 301.0335 3.54 3.57014.600 1 5 8
Volvo 142E21.4 4 121.0109 4.11 2.78018.601 1 4 2

You can plot things:

In [4]:
hist(mtcars$hp)

In R, ggplot2 is the defacto standard plotting packages. Let's make the same plot using ggplot2.

In [5]:
library(ggplot2) qplot(mtcars$hp)
`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

plotly is another popular graphing library. Let's try it!

In [8]:
library(plotly) set.seed(100) d <- diamonds[sample(nrow(diamonds), 1000), ] plot_ly(d, x = ~carat, y = ~price, color = ~carat, size = ~carat, text = ~paste("Clarity: ", clarity))
No trace type specified: Based on info supplied, a 'scatter' trace seems appropriate. Read more about this trace type -> https://plot.ly/r/reference/#scatter No scatter mode specifed: Setting the mode to markers Read more about this attribute -> https://plot.ly/r/reference/#scatter-mode WARNING: 1 intermediate output message was discarded.

That's it for now! Please play around, tell your friends, and let us know how we're doing! Tweet us at @RNotebookHQ !

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