Chad Fibke 2017-10-13
library(tidyverse)## Loading tidyverse: ggplot2
## Loading tidyverse: tibble
## Loading tidyverse: tidyr
## Loading tidyverse: readr
## Loading tidyverse: purrr
## Loading tidyverse: dplyr
## Conflicts with tidy packages ----------------------------------------------
## filter(): dplyr, stats
## lag(): dplyr, stats
library(gapminder)
library(RColorBrewer)summary(mpg)## manufacturer model displ year
## Length:234 Length:234 Min. :1.600 Min. :1999
## Class :character Class :character 1st Qu.:2.400 1st Qu.:1999
## Mode :character Mode :character Median :3.300 Median :2004
## Mean :3.472 Mean :2004
## 3rd Qu.:4.600 3rd Qu.:2008
## Max. :7.000 Max. :2008
## cyl trans drv cty
## Min. :4.000 Length:234 Length:234 Min. : 9.00
## 1st Qu.:4.000 Class :character Class :character 1st Qu.:14.00
## Median :6.000 Mode :character Mode :character Median :17.00
## Mean :5.889 Mean :16.86
## 3rd Qu.:8.000 3rd Qu.:19.00
## Max. :8.000 Max. :35.00
## hwy fl class
## Min. :12.00 Length:234 Length:234
## 1st Qu.:18.00 Class :character Class :character
## Median :24.00 Mode :character Mode :character
## Mean :23.44
## 3rd Qu.:27.00
## Max. :44.00
glimpse(mpg)## Observations: 234
## Variables: 11
## $ manufacturer <chr> "audi", "audi", "audi", "audi", "audi", "audi", "...
## $ model <chr> "a4", "a4", "a4", "a4", "a4", "a4", "a4", "a4 qua...
## $ displ <dbl> 1.8, 1.8, 2.0, 2.0, 2.8, 2.8, 3.1, 1.8, 1.8, 2.0,...
## $ year <int> 1999, 1999, 2008, 2008, 1999, 1999, 2008, 1999, 1...
## $ cyl <int> 4, 4, 4, 4, 6, 6, 6, 4, 4, 4, 4, 6, 6, 6, 6, 6, 6...
## $ trans <chr> "auto(l5)", "manual(m5)", "manual(m6)", "auto(av)...
## $ drv <chr> "f", "f", "f", "f", "f", "f", "f", "4", "4", "4",...
## $ cty <int> 18, 21, 20, 21, 16, 18, 18, 18, 16, 20, 19, 15, 1...
## $ hwy <int> 29, 29, 31, 30, 26, 26, 27, 26, 25, 28, 27, 25, 2...
## $ fl <chr> "p", "p", "p", "p", "p", "p", "p", "p", "p", "p",...
## $ class <chr> "compact", "compact", "compact", "compact", "comp...
??mpg
mpg %>%
ggplot(aes( x = displ, y = cty))+
geom_point()+
theme_classic()+
geom_rect(aes(xmin = 3, xmax = 4, ymin = 15, ymax = 20), alpha = 0.0001, color = "red")
# This can help to highlight any data!
#xmin - (required) left edge of rectangle
#xmax - (required) right edge of rectangle
#ymin - (required) bottom edge of rectangle
#ymax - (required) top edge of rectangle
#size - (default: 0.5) line width of the rectangle's outline
#linetype - (default: 1=solid) line type of the rectangle's outline
#color - (default: NA=no outline) color of the rectangle's outline
#fill - (default: "grey20") fill color of the rectangle
#alpha - (default: 1=opaque) transparency of the rectangle's filmpg %>%
ggplot(aes(x = displ, y = class, color = trans))+
geom_point()+
facet_wrap(~class)
#dimonds and cuts
glimpse(diamonds) ## Observations: 53,940
## Variables: 10
## $ carat <dbl> 0.23, 0.21, 0.23, 0.29, 0.31, 0.24, 0.24, 0.26, 0.22, ...
## $ cut <ord> Ideal, Premium, Good, Premium, Good, Very Good, Very G...
## $ color <ord> E, E, E, I, J, J, I, H, E, H, J, J, F, J, E, E, I, J, ...
## $ clarity <ord> SI2, SI1, VS1, VS2, SI2, VVS2, VVS1, SI1, VS2, VS1, SI...
## $ depth <dbl> 61.5, 59.8, 56.9, 62.4, 63.3, 62.8, 62.3, 61.9, 65.1, ...
## $ table <dbl> 55, 61, 65, 58, 58, 57, 57, 55, 61, 61, 55, 56, 61, 54...
## $ price <int> 326, 326, 327, 334, 335, 336, 336, 337, 337, 338, 339,...
## $ x <dbl> 3.95, 3.89, 4.05, 4.20, 4.34, 3.94, 3.95, 4.07, 3.87, ...
## $ y <dbl> 3.98, 3.84, 4.07, 4.23, 4.35, 3.96, 3.98, 4.11, 3.78, ...
## $ z <dbl> 2.43, 2.31, 2.31, 2.63, 2.75, 2.48, 2.47, 2.53, 2.49, ...
# so we will use a bar chart if we are looking at cut
diamonds %>%
ggplot(aes(x = cut, y = price))+
geom_boxplot(aes(fill = cut))+
theme_classic()+
facet_wrap(~cut, scales = "free")
diamonds %>%
ggplot(aes(x = cut))+
geom_bar(aes(fill = cut))+
theme_classic()+
theme(legend.box.background = element_rect()) 
# remeber we have to tell r the element line, rect or text\some scatter plot
mpg %>%
ggplot(aes(x = displ, y = hwy))+
geom_point()+
geom_smooth(color = "red", span = 0.2) # the smaller the span then the sliding widow will be very small!## `geom_smooth()` using method = 'loess'
mpg %>%
ggplot(aes( x = displ))+
geom_smooth( aes(y = hwy , color = "hwy"), size = 1.3, span = 100)+
geom_smooth( aes(y = cty , color = "cty"), size = 1.3, span = 0.2)+
geom_point(aes( y = cty), color = "red")+
geom_point(aes(y=hwy), color = "blue")+
theme_classic()+
geom_hline(yintercept = mean(mpg$hwy))+
geom_hline(yintercept = mean(mpg$cty))## `geom_smooth()` using method = 'loess'
## `geom_smooth()` using method = 'loess'
#If you speficy your asthetics at the begining, it is carried out for the rest of the layers. Now once we add a layer we can overright these aes **per** layer#ggsave()gapminder %>%
ggplot(aes( x = year, y = lifeExp, group = country))+
geom_line(aes(color = continent), alpha = 0.5)+
geom_point(alpha = 0.1)+
theme_classic()+
facet_wrap(~continent, ncol = 5)+
theme(legend.box.background = element_rect(),
strip.background = element_rect(fill = "orange"),
axis.text.x = element_text(angle = 90))
#remeber the theme only going to tweak the alredy established axis and all of that1
# for facet grid (rows~columns)
#(if you see row ~ . ) the . is nothing or we can even add multiple matrix combos (.~x1 + x2) mpg %>%
ggplot(aes( x = cyl, group = class, fill = class))+
geom_histogram(binwidth = 1, color = "black")+
facet_wrap(~class)+
theme_bw()
talks about scaling:
#c("fixed", "free_x", "free_y", "free")) : 'arg' should be one of “fixed”, “free_x”, “free_y”, “free”
mpg %>%
ggplot(aes( x = cyl, group = class, fill = class))+
geom_histogram(binwidth = 1, color = "black")+
facet_wrap(~class, scales = "free_x")+
theme_bw()
msleep %>%
ggplot(aes(x = sleep_cycle, y = sleep_total, color = vore)) +
geom_point()+
ggtitle("how things sleep")+
xlab("Sleep Cycle")+
ylab("Total amount of sleep")+
scale_colour_manual( name = "Diet", #this will allow us to pick what we want in the legend
values = c("red", "blue", "green", "black"),
breaks = c("carni", "herbi", "insecti","omni"))## Warning: Removed 52 rows containing missing values (geom_point).
# lets add some color:
display.brewer.all()
msleep %>%
ggplot(aes(x= brainwt, fill = vore))+
geom_histogram(binwidth = 1 )+
scale_x_log10()+
scale_fill_brewer("RDGry")## Warning: Removed 27 rows containing non-finite values (stat_bin).
diamonds %>%
ggplot(aes(color, fill = cut))+
geom_bar(position = "dodge")
mpg %>%
ggplot(aes(x= cty, y = hwy))+
geom_point()+
geom_text(aes(label = class ))+
annotate("label", 15, 40, label = "this is not a drill") #the "lable" will give us a outlined box!
exercise:
msleep %>%
ggplot(aes(x = sleep_total, y =bodywt))+
geom_text(aes(label = genus, color = genus))+
scale_y_log10()+
theme(legend.position = "")
diamonds %>%
ggplot(aes(x = carat, y = price))+
geom_point(alpha = 0.2)
ggsave("plot.pdf", device = "pdf")## Saving 7 x 5 in image