library(tidyverse)
library(dplyr)
library(DBI) #contains functions to interect with the databasa
library(RSQLite) #SQLite database driver
library(jsonlite)
library(haven)
library(janitor)
library(readxl)
library(writexl)
library(openxlsx)
library(xlsx)
library(microbenchmark)
library(data.table)
library(readr)
library(remotes)
library(tidyr)
library(dbplyr)
library(knitr)
library(kableExtra)
library(psych)
library(readxl)
library(DescTools)
library(ggplot2)
library(e1071)
library(moments)
library(skimr)
library(tableone)
library(table1)
library(gtsummary)
library(gmodels)
library(naniar)
library(ggthemes)
library(ggThemeAssist)
library(forcats)
library(ggpubr)
library(patchwork)
library(reshape2)
library(car)
library(lares)
library(ggstatsplot)
library(GGally)
library(PerformanceAnalytics)
library(heatmap3)
library(sjPlot)
library(sjmisc)
library(pairsD3)
library(gridExtra)
library(gridExtra)
library(lmtest)
library(titanic)
library(tidyverse)
library(caret)
library(pROC)
mpg
## # A tibble: 234 × 11
## manufacturer model displ year cyl trans drv cty hwy fl class
## <chr> <chr> <dbl> <int> <int> <chr> <chr> <int> <int> <chr> <chr>
## 1 audi a4 1.8 1999 4 auto… f 18 29 p comp…
## 2 audi a4 1.8 1999 4 manu… f 21 29 p comp…
## 3 audi a4 2 2008 4 manu… f 20 31 p comp…
## 4 audi a4 2 2008 4 auto… f 21 30 p comp…
## 5 audi a4 2.8 1999 6 auto… f 16 26 p comp…
## 6 audi a4 2.8 1999 6 manu… f 18 26 p comp…
## 7 audi a4 3.1 2008 6 auto… f 18 27 p comp…
## 8 audi a4 quattro 1.8 1999 4 manu… 4 18 26 p comp…
## 9 audi a4 quattro 1.8 1999 4 auto… 4 16 25 p comp…
## 10 audi a4 quattro 2 2008 4 manu… 4 20 28 p comp…
## # ℹ 224 more rows
ggplot(data = mpg) +
geom_point(mapping = aes(x = displ, y = hwy))
## # A tibble: 234 × 11
## manufacturer model displ year cyl trans drv cty hwy fl class
## <chr> <chr> <dbl> <int> <int> <chr> <chr> <int> <int> <chr> <chr>
## 1 audi a4 1.8 1999 4 auto… f 18 29 p comp…
## 2 audi a4 1.8 1999 4 manu… f 21 29 p comp…
## 3 audi a4 2 2008 4 manu… f 20 31 p comp…
## 4 audi a4 2 2008 4 auto… f 21 30 p comp…
## 5 audi a4 2.8 1999 6 auto… f 16 26 p comp…
## 6 audi a4 2.8 1999 6 manu… f 18 26 p comp…
## 7 audi a4 3.1 2008 6 auto… f 18 27 p comp…
## 8 audi a4 quattro 1.8 1999 4 manu… 4 18 26 p comp…
## 9 audi a4 quattro 1.8 1999 4 auto… 4 16 25 p comp…
## 10 audi a4 quattro 2 2008 4 manu… 4 20 28 p comp…
## # ℹ 224 more rows
ggplot(data = mpg) +
geom_point(mapping = aes(x = class, y = drv))
ggplot(data = mpg) +
geom_point(mapping = aes(x = displ, y = hwy, color = class))
ggplot(data = mpg) +
geom_point(mapping = aes(x = displ, y = hwy, size = class))
#> Warning: Using size for a discrete variable is not advised.
# Left
ggplot(data = mpg) +
geom_point(mapping = aes(x = displ, y = hwy, alpha = class))
# Right
ggplot(data = mpg) +
geom_point(mapping = aes(x = displ, y = hwy, shape = class))
ggplot(data = mpg) +
geom_point(mapping = aes(x = displ, y = hwy), color = "blue")
ggplot(data = mpg) +
geom_point(mapping = aes(x = displ, y = hwy, color = "blue"))
ggplot(data = mpg) +
geom_point(mapping = aes(x = displ, y = hwy))
ggplot(data = mpg) +
geom_point(mapping = aes(x = displ, y = hwy)) +
facet_wrap(~ class, nrow = 2)
ggplot(data = mpg) +
geom_point(mapping = aes(x = displ, y = hwy)) +
facet_grid(drv ~ cyl)
ggplot(data = mpg) +
geom_point(mapping = aes(x = drv, y = cyl))
ggplot(data = mpg) +
geom_point(mapping = aes(x = displ, y = hwy)) +
facet_grid(drv ~ .)
ggplot(data = mpg) +
geom_point(mapping = aes(x = displ, y = hwy)) +
facet_grid(. ~ cyl)
ggplot(data = mpg) +
geom_point(mapping = aes(x = displ, y = hwy)) +
facet_wrap(~ class, nrow = 2)
# left
ggplot(data = mpg) +
geom_point(mapping = aes(x = displ, y = hwy))
# right
ggplot(data = mpg) +
geom_smooth(mapping = aes(x = displ, y = hwy))
ggplot(data = mpg) +
geom_smooth(mapping = aes(x = displ, y = hwy, linetype = drv , color = class))
ggplot(data = mpg) +
geom_smooth(mapping = aes(x = displ, y = hwy))
ggplot(data = mpg) +
geom_smooth(mapping = aes(x = displ, y = hwy, group = drv))
ggplot(data = mpg) +
geom_smooth(
mapping = aes(x = displ, y = hwy, color = drv),
show.legend = FALSE
)
ggplot(data = mpg) +
geom_point(mapping = aes(x = displ, y = hwy)) +
geom_smooth(mapping = aes(x = displ, y = hwy))
ggplot(data = mpg, mapping = aes(x = displ, y = hwy)) +
geom_point() +
geom_smooth()
ggplot(data = mpg, mapping = aes(x = displ, y = hwy)) +
geom_point(mapping = aes(color = class)) +
geom_smooth()
ggplot(data = mpg, mapping = aes(x = displ, y = hwy)) +
geom_point(mapping = aes(color = class)) +
geom_smooth(data = filter(mpg, class == "subcompact"), se = FALSE)
ggplot(data = mpg, mapping = aes(x = displ, y = hwy, color = drv)) +
geom_point() +
geom_smooth(se = FALSE)
ggplot(data = mpg, mapping = aes(x = displ, y = hwy)) +
geom_point() +
geom_smooth()
ggplot() +
geom_point(data = mpg, mapping = aes(x = displ, y = hwy)) +
geom_smooth(data = mpg, mapping = aes(x = displ, y = hwy))
ggplot(data = diamonds) +
geom_bar(mapping = aes(x = cut))
ggplot(data = diamonds) +
stat_count(mapping = aes(x = cut))
demo <- tribble(
~cut, ~freq,
"Fair", 1610,
"Good", 4906,
"Very Good", 12082,
"Premium", 13791,
"Ideal", 21551
)
ggplot(data = demo) +
geom_bar(mapping = aes(x = cut, y = freq), stat = "identity")
ggplot(data = diamonds) +
geom_bar(mapping = aes(x = cut, y = stat(prop), group = 1))
#> Warning: `stat(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, y = after_stat(prop)))
ggplot(data = diamonds) +
geom_bar(mapping = aes(x = cut, fill = color, y = after_stat(prop)))
ggplot(data = diamonds) +
geom_bar(mapping = aes(x = cut, colour = 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, mapping = aes(x = cut, fill = clarity)) +
geom_bar(alpha = 1/5, position = "identity")
ggplot(data = diamonds, mapping = aes(x = cut, colour = clarity)) +
geom_bar(fill = NA, position = "identity")
ggplot(data = diamonds) +
geom_bar(mapping = aes(x = cut, fill = clarity), position = "fill")
ggplot(data = diamonds) +
geom_bar(mapping = aes(x = cut, fill = clarity), position = "dodge")
ggplot(data = mpg) +
geom_point(mapping = aes(x = displ, y = hwy), position = "jitter")
ggplot(data = mpg, mapping = aes(x = cty, y = hwy)) +
geom_point()
ggplot(data = mpg, mapping = aes(x = class, y = hwy)) +
geom_boxplot()
ggplot(data = mpg, mapping = aes(x = class, y = hwy)) +
geom_boxplot() +
coord_flip()
nz <- map_data("nz")
ggplot(nz, aes(long, lat, group = group)) +
geom_polygon(fill = "white", colour = "black")
ggplot(nz, aes(long, lat, group = group)) +
geom_polygon(fill = "white", colour = "black") +
coord_quickmap()
bar <- ggplot(data = diamonds) +
geom_bar(
mapping = aes(x = cut, fill = cut),
show.legend = FALSE,
width = 1
) +
theme(aspect.ratio = 1) +
labs(x = NULL, y = NULL)
bar + coord_flip()
ggplot(data = mpg, mapping = aes(x = cty, y = hwy)) +
geom_point() +
geom_abline() +
coord_fixed()
# The preferred method of creating horizontal instead of vertical boxplots
ggplot(diamonds, aes(price, cut)) +
geom_boxplot()
# Using `coord_flip()` to make the same plot
ggplot(diamonds, aes(cut, price)) +
geom_boxplot() +
coord_flip()
# With swapped aesthetics, the y-scale controls the left axis
ggplot(diamonds, aes(y = carat)) +
geom_histogram() +
scale_y_reverse()
# In `coord_flip()`, the x-scale controls the left axis
ggplot(diamonds, aes(carat)) +
geom_histogram() +
coord_flip() +
scale_x_reverse()
# In line and area plots, swapped aesthetics require an explicit orientation
df <- data.frame(a = 1:5, b = (1:5) ^ 2)
ggplot(df, aes(b, a)) +
geom_area(orientation = "y")
# The same plot with `coord_flip()`
ggplot(df, aes(a, b)) +
geom_area() +
coord_flip()