render compile

SD/1.1_R语言介绍/_demo.qmd

@@ -0,0 +1,138 @@
+---
+title: "Lesson 6"
+format: html
+---
+
+
+
+
+```{r}
+
+https://rs1.drwater.net
+
+username: 
+  - ruser01
+  - ruser02
+  - ruser03
+  - ruser04
+  - ruser05
+  - ruser06
+
+RWEP2025
+
+```
+
+
+# 安装包
+
+
+```{r}
+install.packages("tidyverse")
+
+x <- c(1:10, NA)
+
+hist(x)
+
+mean(x, na.rm = TRUE)
+
+median(x, na.rm = TRUE)
+
+sd(x, na.rm = TRUE)
+
+
+for(i in 1:10){
+  print(i)
+}
+
+
+x + y + x * y
+
+myfunc <- function(x, y = 3) {
+  x + y + x * y
+}
+
+
+myfunc(1, 2)
+
+
+myfunc(10)
+
+
+c(FALSE, 2, 1:3, 3) 
+
+c(FALSE, 2, 1:3, 3) > 1
+
+all(c(FALSE, 2, 1:3, 3) > 1)
+
+
+c(1L,2L,3L)
+
+any(c(FALSE, 2, 1:3, 3) > 1)
+
+
+x <- 10
+
+sin(x) = ?
+
+paste("sin(x) = ", sin(x), sep = " ")
+
+paste0("sin(x) = ", sin(x))
+
+
+substr("Monday", 1, 3)
+
+
+
+```
+
+
+# tidy
+
+
+```{r}
+require(readxl)
+
+aqdf <-readxl::read_xlsx("../../data/airquality.xlsx", sheet = "metadf")
+
+# install.packages("skimr")
+
+aqdf |>
+  skimr::skim()
+
+# base
+
+# tidyverse
+
+aqdf |>
+  dplyr::group_by(Area) |>
+  dplyr::summarize(
+    n = n(),
+    lon.mean = mean(lon, na.rm = TRUE),
+    lon.sd = sd(lat, na.rm = TRUE)
+  ) |>
+  dplyr::filter(Area %in% c("北京市", "天津市", "上海市", "重庆市")) |>
+  ggplot(aes(x = n, y = lon.mean)) +
+  geom_point() +
+  geom_line() +
+  geom_errorbar(
+    aes(ymin = lon.mean - lon.sd,
+      ymax = lon.mean + lon.sd)
+  )
+
+
+
+
+
+
+
+readxl::read_xlsx("./airquality.xlsx")
+
+flights|>
+  filter(dest=="IAH")|>
+  group_by(year,month,day)|>summarize(n=n(),
+delay=mean(arr_delay,na.rm=TRUE))|>filter(n>10)
+
+```
+
+
+