If a golf ball and a club together cost 2,100 PLN, and the price difference between the club and the ball is 2,000 PLN, then how much costs the ball?
Consider the data-frame mtcars
(it should be loaded when
you load R, if not, it is provided by the library
datasets
). Calculate
Then create a function to convert miles per gallon to liter per 100
km, rounded up to 2 digits. Then add a column lp100km
where
you put all the consumption in liter per 100 km and store the results in
a variable d
Now execute the same with a for-loop.
Create a function to demonstrate the lexical scoping in R
Create an object type cardata
, that is your personal
soution for car databases. create a specific print function that plots
mpg
in function of hp
when called by
plot(x)
Consider the dataset mtcars
and sumarise the fuel
consumption in function of the number of cylinders.
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Now for both cyl and vs
## `summarise()` has grouped output by 'dispCats'. You can override using the
## `.groups` argument.
## `summarise()` has grouped output by 'dispCats'. You can override using the
## `.groups` argument.
Create a dataset d
as a copy of mtcars
with
one column extra for the fuel consumption in SI.
Plot the mpg in function of all other variables for
mtcars
.
Plot the fuel consumption in function of the horse power of the motor with blue crosses
use the data of the Standards and Poors index, it is in R as
SP500
, convert it to a time series with start date january
1990, and produce moving average forecast.