---
disqus: ahb0222
GA : G-VF9ZT413CG
---
# 使用R擷取觀測資料查詢系統氣象資料並繪製四季風花圖
> [color=#40f1ef][name=LHB阿好伯, 2022/03/27][:earth_africa:](https://www.facebook.com/LHB0222/)
###### tags: `R` `可視化` `ggplot2`

[TOC]

:::danger
2024/01/20更新
非常可惜的是以前的網站更新了QQ
沒辦法在像之前一樣更改網址爬取資料
目前解決方式只好先分成兩步驟
先使用Python的Selenium下載CSV檔
再用ggplot2畫圖
相關程式碼我就分享出來
拋磚引玉看看有沒有大神能夠將整個程式碼在優化一下
或是有更好用的爬蟲套件能分享一下
不然光Selenium的安裝跟使用就耗費我好多時間XD
Chrome的版本太新就是一個大問題chromedriver支援還沒跟上QQ
要想像之前架設一個Shiny能自動爬取跟畫圖看來是有困難QQ
[使用Python selenium 爬取codis氣候資料服務系統資料並使用ggplot2繪製風花圖](/LW3Ys5qwQ4a4j6zrOdc8HA)
:::

開始構思如何增加[Shinydashboard(儀錶板)手動添加數據繪製風花圖](/Kd2uUuldTrmfafDFt_GfCA)中的功能
目前想到可以增加如每月分或每季的比較
初步是使用patchwork套件做組合


library("patchwork")
library("shiny")
library("jsonlite")
library("rvest")
library("magrittr")
library("lubridate")
library("ggplot2")
library("shinydashboard")
library("DataEditR")
library("jsonlite")
library("lubridate")
library("shinydashboard")

start_date <- "2021/1/1"
end_date <- "2021/12/31"  #終止時間
lab_max <- 30

url_start <- paste0("https://e-service.cwb.gov.tw/HistoryDataQuery/DayDataController.do?command=viewMain&station=",station_number,"&stname=%25E9%259E%258D%25E9%2583%25A8&datepicker=")
start_date <- ymd(start_date)  #起始時間
end_date <- ymd(end_date)  #終止時間
data1 <- data.frame()
data2 <- data.frame()
for(d in c(0:(end_date - start_date))){
  url <- paste0(url_start,as.character(start_date + d),"&altitude=15m")
  #時間資料
  time_H <- url %>% 
    read_html() %>%
    html_nodes(xpath='//*[(@id = "MyTable")]//td[(((count(preceding-sibling::*) + 1) = 1) and parent::*)]') %>% 
    html_text(trim	= T) %>% 
    as.numeric()
  #風速資料
  Windspeed <- url %>%
    read_html() %>%
    html_nodes(xpath='//td[(((count(preceding-sibling::*) + 1) = 7) and parent::*)]') %>%
    html_text(trim	= T) %>% 
    gsub("X","-9999", .) %>% 
    as.numeric()
  #風向
  windDirection<- url %>%
    read_html() %>%
    html_nodes(xpath='//td[(((count(preceding-sibling::*) + 1) = 8) and parent::*)]') %>%
    html_text(trim	= T) %>% 
    gsub("X","-9999", .) %>% 
    as.numeric()
  data1 <- cbind(as.character(start_date + d), time_H, Windspeed,windDirection)  #合併資料
  data2 <- rbind(data2, data1)
  print(start_date + d)
}
str(data2)
windD <- (c("N","NNE","NE","ENE","E","ESE","SE","SSE","S","SSW","SW","WSW","W","WNW","NW","NNW","N"))
FourSeasons2 <- factor(c("冬","春","夏","秋","冬"))
data3 <- na.omit(data2)  #刪除包含NA值的列
data3$windDirection_N <- cut(as.numeric(data3$windDirection),
                             breaks = c(0, 11.26, 33.76, 56.26, 78.76, 101.26, 127.76, 146.26, 168.76, 191.26, 213.76, 236.26, 258.76, 281.26, 303.76, 326.26, 348.75, 360),
                             windD,
                             include.lowest = TRUE)
data3$Windspeed_N <- cut(as.numeric(data3$Windspeed),
                         breaks =c(0, 2.1, 4.1,  6.1, Inf),
                         labels = c("0~2", "2.1~4", "4.1~6", ">6.1"),
                         right = F)
data3$FourSeasons <- force(cut(month(data3$V1),
                             breaks = c(0, 1, 4, 7, 10, 12),
                             FourSeasons2,
                             include.lowest = TRUE))
data3$month <- month(data3$V1)
data3$year <- year(data3$V1)
data3$Windspeed <- as.numeric(data3$Windspeed)
p1 <- data3 %>% dplyr::filter(FourSeasons == "春") %>% ggplot( aes(x = windDirection_N, fill = Windspeed_N))+
  geom_bar( aes(y = (..count..)/sum(..count..)*100 ), 
            position = position_stack(reverse = TRUE)) + 
  theme_bw() + scale_x_discrete(drop = FALSE,
                                labels = windD)+
  scale_fill_discrete(guide = guide_legend(reverse=TRUE), name = "Wind Speed (m/s)",breaks = c("0~2", "2.1~4", "4.1~6", ">6.1"),
                      labels=  c("0~2", "2.1~4", "4.1~6", ">6.1"),drop = F)+
  coord_polar(start = -0.2) + 
  xlab("") + #ggtitle(paste(station_number,"(",start_date,"~",end_date,")"))+
    theme(axis.title=element_blank(), 
        axis.text.y=element_blank(), 
        axis.ticks=element_blank())+
  annotate("text",x = "NE", 
           y = c(scales::extended_breaks(5)(range(0,as.numeric(lab_max)))), 
           label = paste(c(scales::extended_breaks(5)(range(0,as.numeric(lab_max)))),"%"))
#ggsave("P1.png")

p2 <- data3 %>% dplyr::filter(FourSeasons == "夏") %>% ggplot( aes(x = windDirection_N, fill = Windspeed_N))+
  geom_bar( aes(y = (..count..)/sum(..count..)*100 ), 
            position = position_stack(reverse = TRUE)) + 
  theme_bw() + scale_x_discrete(drop = FALSE,
                                labels = windD)+
  scale_fill_discrete(guide = guide_legend(reverse=TRUE), name = "Wind Speed (m/s)",breaks = c("0~2", "2.1~4", "4.1~6", ">6.1"),
                      labels=  c("0~2", "2.1~4", "4.1~6", ">6.1"),drop = F)+
  coord_polar(start = -0.2) + 
  xlab("") + #ggtitle(paste(station_number,"(",start_date,"~",end_date,")"))+
  theme(axis.title=element_blank(), 
        axis.text.y=element_blank(), 
        axis.ticks=element_blank())+
  annotate("text",x = "NE", 
           y = c(scales::extended_breaks(5)(range(0,as.numeric(lab_max)))), 
           label = paste(c(scales::extended_breaks(5)(range(0,as.numeric(lab_max)))),"%"))
p3 <- data3 %>% dplyr::filter(FourSeasons == "秋") %>% ggplot( aes(x = windDirection_N, fill = Windspeed_N))+
  geom_bar( aes(y = (..count..)/sum(..count..)*100 ), 
            position = position_stack(reverse = TRUE)) + 
  theme_bw() + scale_x_discrete(drop = FALSE,
                                labels = windD)+
  scale_fill_discrete(guide = guide_legend(reverse=TRUE), name = "Wind Speed (m/s)",breaks = c("0~2", "2.1~4", "4.1~6", ">6.1"),
                      labels=  c("0~2", "2.1~4", "4.1~6", ">6.1"),drop = F)+
  coord_polar(start = -0.2) + 
  xlab("") + #ggtitle(paste(station_number,"(",start_date,"~",end_date,")"))+
  theme(axis.title=element_blank(), 
        axis.text.y=element_blank(), 
        axis.ticks=element_blank())+
  annotate("text",x = "NE", 
           y = c(scales::extended_breaks(5)(range(0,as.numeric(lab_max)))), 
           label = paste(c(scales::extended_breaks(5)(range(0,as.numeric(lab_max)))),"%"))
p4 <- data3 %>% dplyr::filter(FourSeasons == "冬") %>% ggplot( aes(x = windDirection_N, fill = Windspeed_N))+
  geom_bar( aes(y = (..count..)/sum(..count..)*100 ), 
            position = position_stack(reverse = TRUE)) + 
  theme_bw() + scale_x_discrete(drop = FALSE,
                                labels = windD)+
  scale_fill_discrete(guide = guide_legend(reverse=TRUE), name = "Wind Speed (m/s)",breaks = c("0~2", "2.1~4", "4.1~6", ">6.1"),
                      labels=  c("0~2", "2.1~4", "4.1~6", ">6.1"),drop = F)+
  coord_polar(start = -0.2) + 
  xlab("") + #ggtitle(paste(station_number,"(",start_date,"~",end_date,")"))+
  theme(axis.title=element_blank(), 
        axis.text.y=element_blank(), 
        axis.ticks=element_blank())+
  annotate("text",x = "NE", 
           y = c(scales::extended_breaks(5)(range(0,as.numeric(lab_max)))), 
           label = paste(c(scales::extended_breaks(5)(range(0,as.numeric(lab_max)))),"%"))

(p1+p2)/(p3+p4)+
  plot_annotation(tag_levels = list(c("春","夏","秋","冬")))+
  plot_layout(guides='collect')

每一季還好但若是每月使用patchwork就不適合了
但若是使用 facet_wrap的方式結果會是不一樣的QQ
目前還沒找到問題
若是有人知道問題在哪麻煩跟我說

p5 <- ggplot(data3, aes(x = windDirection_N, fill = Windspeed_N))+
  geom_bar( aes(y = (..count..)/sum(..count..)*100 ), 
            position = position_stack(reverse = TRUE)) + 
  theme_bw() + scale_x_discrete(drop = FALSE,
                                labels = windD)+
  scale_fill_discrete(guide = guide_legend(reverse=TRUE), name = "Wind Speed (m/s)",breaks = c("0~2", "2.1~4", "4.1~6", ">6.1"),
                      labels=  c("0~2", "2.1~4", "4.1~6", ">6.1"),drop = F)+
  coord_polar(start = -0.2) + 
  xlab("") + #ggtitle(paste(station_number,"(",start_date,"~",end_date,")"))+
  theme(axis.title=element_blank(), 
        axis.text.y=element_blank(), 
        axis.ticks=element_blank())
p5 + facet_wrap(~FourSeasons, ncol = 2)


🌟

🌟全文可以至下方連結觀看或是補充

全文分享至

https://www.facebook.com/LHB0222/

https://www.instagram.com/ahb0222/

有疑問想討論的都歡迎於下方留言

喜歡的幫我分享給所有的朋友 \o/

有所錯誤歡迎指教

# [:page_with_curl: 全部文章列表](https://hackmd.io/@LHB-0222/AllWritings)