rvest.Rmd

# 网络爬虫 {#rvest}


```{r message = FALSE, warning = FALSE}
library(tidyverse)
library(rvest)
library(sf)
```

## 链家网

```{r}
urls <-	paste0("https://sh.lianjia.com/ershoufang/pg", seq_along(1:2))


scrape_house_info  <- function(url) {

	web <- read_html(url)
	
	title <- web %>% 
	  html_nodes('.clear .title a') %>% 
	  html_text()

	houseinfo <- web %>% 
	  html_nodes('.houseInfo') %>%
	  html_text()

	
	price <- web %>% 
	  html_nodes('.totalPrice span') %>% 
	  html_text()

	price_per <- web %>% 
	  html_nodes('.unitPrice span') %>% 
	  html_text()

	df <- data.frame(title, houseinfo, price, price_per) 
	
	return(df)
}
```


```{r}
tb <- urls %>% map_df(scrape_house_info)

tb
```




## 猪肉价格

```{r}
df_price <-
  read_html("https://hangqing.zhuwang.cc/shengzhu/20190905/407978.html") %>%
  html_node(".tabzj") %>%
  html_table(header = T) %>% 
  set_names(
    c("region", "name", "price_today", "price_yestoday", "diff_last_day", "diff_last_week")
    ) %>% 
  mutate_at(vars(name), ~str_remove_all(., " ") ) %>% 
  mutate_at(vars(name), ~if_else( name == "黑龙江", "黑龙江省", .))

df_price
```




```{r}
china <- st_read("./demo_data/chinamap_data/bou2_4p.shp") %>% 
  st_set_crs(4326) %>% 
  group_by(NAME) %>%
  summarize()
```


```{r}
china_uni <- china %>% 
  mutate( NAME = iconv(NAME, "GBK", "UTF-8") ) %>% 
  mutate_at(vars(NAME), ~str_remove_all(., "自治区|回族|维吾尔|壮族") ) %>%
  mutate_at(vars(NAME), ~str_trim(.))
```


```{r}
df <- left_join(china_uni, df_price, by = c("NAME" = "name"))
```




```{r,fig.width= 8, fig.height= 8}
ggplot(data = df) + 
  geom_sf( aes(fill = price_today < 28), show.legend = FALSE) + 
  geom_sf_text(aes(label = NAME),
               size = 3
               ) +
  geom_sf_text(aes(label = price_today), 
               size = 3,
               #nudge_x = c(-0.4, 0.5, 0.7),
               nudge_y = c(-1, -1, -1)
               ) +
  coord_sf(crs = 4326) +
  ggtitle("全国猪肉价格地图")

```