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library(ggplot2)
## Warning: package 'ggplot2' was built under R version 4.3.2
library(tidyverse)
## Warning: package 'tidyverse' was built under R version 4.3.2
## Warning: package 'tibble' was built under R version 4.3.2
## Warning: package 'tidyr' was built under R version 4.3.2
## Warning: package 'readr' was built under R version 4.3.2
## Warning: package 'purrr' was built under R version 4.3.2
## Warning: package 'dplyr' was built under R version 4.3.2
## Warning: package 'stringr' was built under R version 4.3.2
## Warning: package 'forcats' was built under R version 4.3.2
## Warning: package 'lubridate' was built under R version 4.3.2
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.4 ✔ readr 2.1.5
## ✔ forcats 1.0.0 ✔ stringr 1.5.1
## ✔ lubridate 1.9.3 ✔ tibble 3.2.1
## ✔ purrr 1.0.2 ✔ tidyr 1.3.1
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(dplyr)
ggplot(data=mpg) + geom_smooth(mapping = aes(x=displ, y=hwy, linetype = drv))
## `geom_smooth()` using method = 'loess' and formula = 'y ~ x'
ggplot(data=mpg) + geom_smooth(mapping = aes(x=displ, y=hwy, group = drv))
## `geom_smooth()` using method = 'loess' and formula = 'y ~ x'
ggplot(data=mpg) + geom_smooth(mapping = aes(x=displ, y=hwy, color = drv), show.legend = FALSE)
## `geom_smooth()` using method = 'loess' and formula = 'y ~ x'
ggplot(data = mpg) + geom_point(mapping = aes(x=displ, y = hwy)) + geom_smooth(mapping = aes(x=displ, y=hwy))
## `geom_smooth()` using method = 'loess' and formula = 'y ~ x'
ggplot(data=mpg, mapping = aes(x=displ, y=hwy)) + geom_point() + geom_smooth()
## `geom_smooth()` using method = 'loess' and formula = 'y ~ x'
ggplot(data=mpg, mapping = aes(x=displ, y=hwy)) + geom_point(mapping=aes(color=class)) + geom_smooth()
## `geom_smooth()` using method = 'loess' and formula = 'y ~ x'
ggplot(data=mpg, mapping = aes(x=displ, y=hwy)) + geom_point(mapping=aes(color=class)) + geom_smooth(data =filter(mpg, class =="subcompact"), se=FALSE)
## `geom_smooth()` using method = 'loess' and formula = 'y ~ x'
ggplot(data=mpg, mapping = aes(x=displ, y=hwy)) + geom_point(mapping=aes(color=class)) + geom_smooth(data =filter(mpg, class =="minivan"), se=FALSE)
## `geom_smooth()` using method = 'loess' and formula = 'y ~ x'
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric = parametric,
## : pseudoinverse used at 4.008
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric = parametric,
## : neighborhood radius 0.708
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric = parametric,
## : reciprocal condition number 0
## Warning in simpleLoess(y, x, w, span, degree = degree, parametric = parametric,
## : There are other near singularities as well. 0.25
?diamonds
## starting httpd help server ... done
str(diamonds)
## tibble [53,940 × 10] (S3: tbl_df/tbl/data.frame)
## $ carat : num [1:53940] 0.23 0.21 0.23 0.29 0.31 0.24 0.24 0.26 0.22 0.23 ...
## $ cut : Ord.factor w/ 5 levels "Fair"<"Good"<..: 5 4 2 4 2 3 3 3 1 3 ...
## $ color : Ord.factor w/ 7 levels "D"<"E"<"F"<"G"<..: 2 2 2 6 7 7 6 5 2 5 ...
## $ clarity: Ord.factor w/ 8 levels "I1"<"SI2"<"SI1"<..: 2 3 5 4 2 6 7 3 4 5 ...
## $ depth : num [1:53940] 61.5 59.8 56.9 62.4 63.3 62.8 62.3 61.9 65.1 59.4 ...
## $ table : num [1:53940] 55 61 65 58 58 57 57 55 61 61 ...
## $ price : int [1:53940] 326 326 327 334 335 336 336 337 337 338 ...
## $ x : num [1:53940] 3.95 3.89 4.05 4.2 4.34 3.94 3.95 4.07 3.87 4 ...
## $ y : num [1:53940] 3.98 3.84 4.07 4.23 4.35 3.96 3.98 4.11 3.78 4.05 ...
## $ z : num [1:53940] 2.43 2.31 2.31 2.63 2.75 2.48 2.47 2.53 2.49 2.39 ...
summary(diamonds$carat)
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.2000 0.4000 0.7000 0.7979 1.0400 5.0100
summary(diamonds$depth)
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 43.00 61.00 61.80 61.75 62.50 79.00
summary(diamonds$cut)
## Fair Good Very Good Premium Ideal
## 1610 4906 12082 13791 21551
summary(diamonds$price)
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 326 950 2401 3933 5324 18823
view(diamonds)
Val<-c(46,34,87,22,91)
mean(Val)
## [1] 56
mean(diamonds$price)
## [1] 3932.8
ggplot(data=diamonds) + geom_point(mapping = aes(x=carat, y=price,color = cut))
hist(diamonds$carat, main="Histogram of diamonds carat weight", xlab="Carat")
hist(diamonds$price, main="Histogram of diamonds cost", xlab="price")
var(diamonds$carat)
## [1] 0.2246867
var(diamonds$price)
## [1] 15915629
sd(diamonds$carat)
## [1] 0.4740112
sd(diamonds$price)
## [1] 3989.44
table(diamonds$cut)
##
## Fair Good Very Good Premium Ideal
## 1610 4906 12082 13791 21551
ggplot(data=diamonds) + geom_bar(mapping = aes(x=cut))
ggplot(data=diamonds) + stat_count(mapping=aes(x=cut, y=..prop.., group=1))
## Warning: The dot-dot notation (`..prop..`) was deprecated in ggplot2 3.4.0.
## ℹ Please use `after_stat(prop)` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
ggplot(data=diamonds) + stat_summary(mapping=aes(x=cut, y=depth), fun.min = min, fun.max = max, fun = median)
ggplot(data=diamonds) + geom_bar(mapping = aes(x=cut, color=cut))
ggplot(data=diamonds) + geom_bar(mapping = aes(x=cut, fill=cut))
ggplot(data=diamonds) + geom_bar(mapping = aes(x=cut, fill=clarity))
ggplot(data=diamonds) + geom_bar(mapping = aes(x=cut, fill=clarity), position = "dodge")
ggplot(data=diamonds) + geom_bar(mapping = aes(x=color, fill=clarity), position = "dodge")
nz<- map_data("nz")
usa<- map_data("usa")
ggplot(nz, aes(long, lat, group=group)) + geom_polygon(fill = "white", color = "black")
ggplot(nz, aes(long, lat, group=group)) + geom_polygon(fill = "white", color = "black") + coord_quickmap()
ggplot(nz, aes(long, lat, group=group)) + geom_polygon(fill = "white", color = "black") + coord_quickmap()
ggplot(usa, aes(long, lat, group=group)) + geom_polygon(fill = "red", color = "blue")
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