R Markdown

This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see http://rmarkdown.rstudio.com.

When you click the Knit button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this:

summary(cars)
##      speed           dist       
##  Min.   : 4.0   Min.   :  2.00  
##  1st Qu.:12.0   1st Qu.: 26.00  
##  Median :15.0   Median : 36.00  
##  Mean   :15.4   Mean   : 42.98  
##  3rd Qu.:19.0   3rd Qu.: 56.00  
##  Max.   :25.0   Max.   :120.00

Including Plots

You can also embed plots, for example:

Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.

library(tidyverse)
## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──
## ✔ ggplot2 3.3.6     ✔ purrr   0.3.4
## ✔ tibble  3.1.7     ✔ dplyr   1.0.9
## ✔ tidyr   1.2.0     ✔ stringr 1.4.0
## ✔ readr   2.1.2     ✔ forcats 0.5.1
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
library(modelr)
options(na.action = na.warn)
library(nycflights13)
library(lubridate)
## 
## 载入程辑包：'lubridate'
## The following objects are masked from 'package:base':
## 
##     date, intersect, setdiff, union
ggplot(diamonds, aes(cut, price)) + geom_boxplot()

ggplot(diamonds, aes(color, price)) + geom_boxplot()

ggplot(diamonds, aes(clarity, price)) + geom_boxplot()

ggplot(diamonds,aes(carat,price))+geom_hex(bins=50)

diamonds2 <- diamonds %>%
   filter(carat <= 2.5) %>%
   mutate(lprice = log2(price), lcarat = log2(carat))
ggplot(diamonds2, aes(lcarat, lprice)) +geom_hex(bins = 50)

mod_diamond <- lm(lprice ~ lcarat, data = diamonds2)
grid <- diamonds2 %>%
   data_grid(carat = seq_range(carat, 20)) %>%
   mutate(lcarat = log2(carat)) %>%
   add_predictions(mod_diamond, "lprice") %>%
   mutate(price = 2 ^ lprice)
ggplot(diamonds2, aes(carat, price)) +geom_hex(bins = 50) +geom_line(data = grid, color = "red", size = 1)

diamonds2 <- diamonds2 %>%
   add_residuals(mod_diamond, "lresid")
ggplot(diamonds2, aes(lcarat, lresid)) +geom_hex(bins = 50)

ggplot(diamonds2, aes(cut, lresid)) + geom_boxplot()

ggplot(diamonds2, aes(color, lresid)) + geom_boxplot()

ggplot(diamonds2, aes(clarity, lresid)) + geom_boxplot()

mod_diamond2 <- lm(lprice ~ lcarat + color + cut + clarity,data = diamonds2)
grid <- diamonds2 %>%
   data_grid(cut, .model = mod_diamond2) %>%
   add_predictions(mod_diamond2)
ggplot(grid, aes(cut, pred)) +geom_point()

diamonds2 <- diamonds2 %>%
  add_residuals(mod_diamond2, "lresid2")
ggplot(diamonds2, aes(lcarat, lresid2)) +geom_hex(bins = 50)