Illya Mowerman
2/13/2018
Note that you will need to change the path for reading in the data
library(tidyverse)
hr <- read_csv("~/Dropbox/Bridgeport/2018 Spring/Data/HR_comma_sep.csv")
affairs <- read_csv("~/Dropbox/Bridgeport/2018 Spring/Data/affairs.csv")
ggplot(affairs) +
geom_histogram(aes(rating))
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
ggplot(affairs) +
geom_histogram(aes(rating) , binwidth = 1)
ggplot(hr) +
geom_boxplot(aes(y = satisfaction_level , x = ''))
ggplot(hr) +
geom_boxplot(aes(y = satisfaction_level , x = sales))
ggplot(hr) +
geom_point(aes(satisfaction_level , last_evaluation))
ggplot(hr) +
geom_smooth(aes(satisfaction_level , last_evaluation))
## `geom_smooth()` using method = 'gam'
ggplot(affairs) +
geom_bar(aes(occupation))
ggplot(affairs) +
geom_bar(aes(x = '', fill = factor(occupation)) , width = 1)
ggplot(affairs) +
geom_bar(aes(x = '', fill = factor(occupation)) , width = 1) +
coord_polar(theta = "y")
ggplot(affairs) +
geom_point(aes(x = rating , y = religiousness , size = affairs))
ggplot(affairs) +
geom_jitter(aes(x = rating , y = religiousness , size = affairs))
Space, Right Arrow or swipe left to move to next slide, click help below for more details