SD/20240328_4_实践部分/index.qmd

@@ -97,8 +97,3 @@ geom_bar(position = "fill")
 ## 综合实践：三维荧光数据处理
 
 
-## 欢迎讨论！{.center}
-
-
-`r rmdify::slideend(wechat = FALSE, type = "public", tel = FALSE, thislink = "https://drwater.rcees.ac.cn/course/public/RWEP/@PUB/SD/")`
-

SD/20240328_9_课后作业/第8次课后作业_模板.qmd

@@ -7,112 +7,18 @@ format: html
 # 下载airquality.xlsx，并读取数据
 
 ```{r}
-#| eval: false
-#| execute: false
 # 下载至临时文件
 tmpxlsxpath <- file.path(tempdir(), "airquality.xlsx")
 download.file("https://drwater.rcees.ac.cn/git/course/RWEP/raw/branch/PUB/data/airquality.xlsx",
   destfile = tmpxlsxpath)
-airqualitydf <- readxl::read_xlsx(tmpxlsxpath, sheet = 2)
+airqualitydf <- readxl::read_xlsx(tmpxlsxpath, sheet = 1)
-metadf <- readxl::read_xlsx(tmpxlsxpath, sheet = 1)
+metadf <- readxl::read_xlsx(tmpxlsxpath, sheet = 2)
 ```
 
 # 根据`airqualitydf.xlsx`，按采样点统计白天（8:00-20:00）与夜晚（20:00-8:00）中空气质量指数（AQI）中位数，按城市统计低于所有采样点AQI30%分位值的采样点占比，列出上述占比最高的10个城市（不考虑采样点数低于5个的城市）。
 
-```{r}
-#| eval: false
-#| execute: false
-require(tidyverse)
-airqualitydf |>
-  select(datetime, site, AQI) |>
-  filter(!is.na(AQI)) |>
-  group_by(site) |>
-  summarize(AQI.median = median(AQI, na.rm = TRUE)) |>
-  left_join(metadf |> select(site, city = Area)) |>
-  group_by(city) |>
-  filter(n() > 5) |>
-  summarize(p = sum(AQI.median < quantile(airqualitydf$AQI, probs = 0.5, na.rm = TRUE)) / n()) |>
-  top_n(10, p)
 
 
-airqualitydf |>
-  select(datetime, site, AQI) |>
-  filter(!is.na(AQI)) |>
-  group_by(site) |>
-  summarize(AQI.median = median(AQI, na.rm = TRUE))
-
-airqualitydf |>
-  select(datetime, site, AQI) |>
-  filter(!is.na(AQI)) |>
-  left_join(metadf |> select(site, city = Area)) |>
-  group_by(city) |>
-  filter(length(unique(site)) >= 5) |>
-  summarize(p = sum(AQI < quantile(airqualitydf$AQI, probs = 0.2,
-    na.rm = TRUE)) / n()) |>
-  slice_max(p, n = 10)
-```
 
 
 # 按照不同城市分组，统计白天与夜晚AQI中位数是否具有显著差异。
-
-```{r}
-#| eval: false
-
-if (FALSE) {
-
-require(infer)
-testdf <- airqualitydf |>
-  select(datetime, site, AQI) |>
-  filter(!is.na(AQI)) |>
-  left_join(metadf |> select(site, city = Area)) |>
-  group_by(city) |>
-  filter(length(unique(site)) >= 5) |>
-  mutate(dayornight = factor(ifelse(between(hour(datetime), 8, 20), "day", "night"),
-    levels = c("day", "night"))
-  ) |>
-  group_by(city) |>
-  nest(citydf = -city) |>
-  mutate(median_diff = purrr::map_dbl(citydf, ~
-    .x |>
-      specify(AQI ~ dayornight) |>
-      calculate(stat = "diff in medians", order = c("day", "night")) |>
-      pull(stat)
-)) |>
-  ungroup() |>
-#  slice_sample(n = 12) |>
-  mutate(null_dist = purrr::map(citydf, ~
-    .x |>
-      specify(AQI ~ dayornight) |>
-   hypothesize(null = "independence") |>
-   generate(reps = 1000, type = "permute") |>
-      calculate(stat = "diff in medians", order = c("day", "night"))
-)) |>
-  mutate(fig = purrr::pmap(list(null_dist, median_diff, city),
-    ~ visualize(..1) +
-  shade_p_value(obs_stat = ..2, direction = "both") +
-      ggtitle(..3)
-  )) |>
-  mutate(p_value = purrr::map2_dbl(null_dist, median_diff, 
-    ~  get_p_value(.x, obs_stat = .y, direction = "both") |>
-      pull(p_value)
-  )) |>
-  arrange(p_value) |>
-  mutate(sigdiff = ifelse(p_value < 0.01, "显著差异", "无显著差异"))
-
-testdf |>
-  select(city, sigdiff) |>
-knitr::kable()
-
-  lang <- "cn"
-(testdf |>
-  slice_sample(n = 9) |>
-  pull(fig)) |>
-patchwork::wrap_plots(ncol = 3) +
-dwfun::theme_sci(5, 5)
-
-dwfun::ggsavep("./testdf.pdf")
-
-}
-
-```
-

SD/20240402_9_课后作业/_extensions

@@ -1 +0,0 @@
-../../_extensions

SD/20240402_9_课后作业/index.qmd

@@ -1,49 +0,0 @@
----
-title: "课后作业9"
-subtitle: 《区域水环境污染数据分析实践》<br>Data analysis practice of regional water environment pollution
-author: 苏命、王为东<br>中国科学院大学资源与环境学院<br>中国科学院生态环境研究中心
-date: today
-lang: zh
-format:
-  revealjs:
-    theme: dark
-    slide-number: true
-    chalkboard:
-      buttons: true
-    preview-links: auto
-    lang: zh
-    toc: true
-    toc-depth: 1
-    toc-title: 大纲
-    logo: ./_extensions/inst/img/ucaslogo.png
-    css: ./_extensions/inst/css/revealjs.css
-    pointer:
-      key: "p"
-      color: "#32cd32"
-      pointerSize: 18
-revealjs-plugins:
-  - pointer
-filters:
-  - d2
----
-
-```{r}
-#| include: false
-#| cache: false
-lang <- "cn"
-require(tidyverse)
-require(learnr)
-```
-
-## 第9次课后作业
-
-自选数据集，使用R语言开展不同因子（如年份、季节、处理方式等）间某指标的差异分析，采用图表方式形成简要报告。
-
-作业模板：[第9次课后作业_模板.qmd](https://drwater.rcees.ac.cn/git/course/RWEP/raw/branch/main/SD/20240402_9_课后作业/第9次课后作业_模板.qmd)
-
-
-## 欢迎讨论！{.center}
-
-
-`r rmdify::slideend(wechat = FALSE, type = "public", tel = FALSE, thislink = "https://drwater.rcees.ac.cn/course/public/RWEP/@PUB/SD/")`
-

SD/20240402_9_课后作业/第9次课后作业_模板.qmd

@@ -1,8 +0,0 @@
----
-title: 课后作业9
-author: 姓名
-format: html
----
-
-要求：自选数据集，使用R语言开展不同因子间（如年份、季节、处理方式等）某指标的差异分析，采用图表+文字说明等方式形成简要报告。
-

index.qmd

@@ -19,4 +19,4 @@ subtitle: "课程简介"
 
 - 网页公开：[https://drwater.rcees.ac.cn/course/public/RWEP/\@PUB/index.html](https://drwater.rcees.ac.cn/course/public/RWEP/@PUB/index.html)
 - 课件代码：[https://drwater.rcees.ac.cn/git/course/RWEP.git](https://drwater.rcees.ac.cn/git/course/RWEP.git)
-- 代码web界面：[https://on.tty-share.com/s/2YElKFjzniilfg3vH-d1PUqqmz_MQzNki5dyxWWL7QONCX_77GzsdP9EEAgBQu3ONwM/](https://on.tty-share.com/s/2YElKFjzniilfg3vH-d1PUqqmz_MQzNki5dyxWWL7QONCX_77GzsdP9EEAgBQu3ONwM/)
+- 代码web界面：[https://on.tty-share.com/s/KHxahtDKk7EIIMFFA60dQfh4-YgnWkkXRjzkaFV_7pSj96kDw_VxTC6Qa76UpG4Yee8/](https://on.tty-share.com/s/KHxahtDKk7EIIMFFA60dQfh4-YgnWkkXRjzkaFV_7pSj96kDw_VxTC6Qa76UpG4Yee8/)