# R-programming-statistics

R is a programming language possesses an extensive catalog of statistical and graphical methods. It includes machine learning algorithm, linear regression, time series, statistical inference to name a few. Most of the R libraries are written in R,but many large companies also use R programming language, including Uber, Google, Airbnb, Facebook and so on

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Showing posts with label Traditionally these are used to explore relationships between time and another variable. Show all posts
Showing posts with label Traditionally these are used to explore relationships between time and another variable. Show all posts

## Traditionally these are used to explore relationships between time and another variable

set.seed(1410)
> dsmall <- diamonds[sample(nrow(diamonds), 100), ]
>
> qplot(carat, price, data = diamonds)

>
> qplot(carat, price,col=101, data = diamonds)
>
> qplot(carat, price,col="red", data = diamonds)
>
> qplot(carat, price,col="green", data = diamonds)
> qplot(carat, price,col="yellow", data = diamonds)
> qplot(carat, price,col=125, data = diamonds)
> qplot(log(carat), log(price), data = diamonds)
>
> qplot(exp(carat), log(price), data = diamonds)
>
> qplot(log(carat), log(price),col=232, data = diamonds)
> qplot(carat, price, data = dsmall, colour = color)
> qplot(carat, price, data = dsmall, shape = cut)

Warning message:
Using shapes for an ordinal variable is not advised
>
> qplot(carat, price, data = diamonds, alpha = I(1/10))
> qplot(carat, price, data = dsmall, geom = c("point", "smooth"))
`geom_smooth()` using method = 'loess' and formula 'y ~ x'
> qplot(carat, price, data = dsmall, geom = c("boxplot", "smooth"))
`geom_smooth()` using method = 'loess' and formula 'y ~ x'
Warning message:
Continuous x aesthetic -- did you forget aes(group=...)?
> qplot(carat, price, data = dsmall, geom = c("path", "line"))