add L7.qmd

coding/L7.qmd

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+---
+title: "RWEP L7- Data Transform"
+---
+
+# Data Source
+
+
+```{r}
+dailylanddf <- readr::read_csv("../data/chinawq/daily_land.csv")
+metadatadf <- readxl::read_xls("../data/chinawq/metadata_and_statistics.xls")
+monthlylanddf <- readr::read_csv("../data/chinawq/monthly_ocean.csv")
+weeklylanddf <- readr::read_csv("../data/chinawq/weekly_land.csv")
+```
+
+
+```{r}
+require(tidyverse)
+dailylanddf
+
+
+dailylanddf |>
+  select(.data$MonitoringLocationIdentifier, .data$LongitudeMeasure_WGS84)
+
+dailylanddf |>
+  select("MonitoringLocationIdentifier", "LongitudeMeasure_WGS84")
+
+
+dailylanddf |>
+  select(1:3)
+
+
+dailylanddf |>
+  rename(x = 1) |>
+  rename(y = 2)
+```
+
+
+
+# 内置function
+
+
+```{r}
+
+dailylanddf |>
+  select(1:3) |>
+  rename_all(\(x) c("a", "b", "c")) |>
+  rename_all(\(x) paste0(x, "_new"))
+
+dailylanddf |>
+  select(1:3) |>
+  rename_all(~ c("a", "b", "c")) |>
+  rename_all(~ paste0(., "_new"))
+
+
+dailylanddf |>
+  select(1:3) |>
+  rename_all(~ c("x", "y", "z"))
+```
+
+```{r}
+fulldatadf <- readr::read_csv("../data/chinawq/full_dataset.csv")
+
+datadf <- fulldatadf |>
+  select(lon = 2, lat = 3, date = 4, varname = 5, value = 6) |>
+  mutate(value = as.numeric(value)) |>
+  tidyr::pivot_wider(names_from = varname, values_from = value)
+
+saveRDS(datadf, "../data/chinawq/datadf.rds")
+```
+
+
+# 统计
+
+## 统计每月的DO的平均值
+
+```{r}
+datadf <- readRDS("../data/chinawq/datadf.rds")
+
+datadf |>
+  select(1:7) |>
+  mutate(month = month(date)) |>
+  select(lon, lat, month, date, everything()) |>
+  group_by(month) |>
+  summarize(DO_mean = mean(DO, na.rm = TRUE), DO_sd = sd(DO, na.rm = TRUE)) |>
+  ggplot(aes(x = month, y = DO_mean)) +
+  geom_point() +
+  geom_smooth(method = "loess") +
+  geom_errorbar(aes(ymin = DO_mean - DO_sd, ymax = DO_mean + DO_sd))
+```
+
+
+```{r}
+datadf |>
+  select(1:7) |>
+  mutate(month = month(date)) |>
+  mutate(year = year(date)) |>
+  select(lon, lat, year, month, date, everything()) |>
+  summarize(
+    DO_mean = mean(DO, na.rm = TRUE),
+    DO_sd = sd(DO, na.rm = TRUE),
+    .by = c(year, month)
+  ) |>
+  ggplot(aes(x = month, y = DO_mean)) +
+  geom_point() +
+  geom_smooth(method = "loess") +
+  geom_errorbar(aes(ymin = DO_mean - DO_sd, ymax = DO_mean + DO_sd)) +
+  facet_wrap(~year)
+```
+
+
+```{r}
+datadf |>
+  select(1:7) |>
+  mutate(month = month(date)) |>
+  mutate(year = year(date)) |>
+  select(-lon, -lat, -date) |>
+  group_by(year, month) |>
+  summarize_all(\(x) mean(x, na.rm = TRUE))
+```
+
+## nest
+
+```{r}
+
+for (isite in 1:10) {
+  m <- datadf |>
+    select(1:7) |>
+    tidyr::nest(wqdf = -c(lon, lat)) |>
+    pull(wqdf) |>
+    nth(isite) |>
+    lm(formula = DO ~ pH, data = _)
+  slope <- coef(m)[2]
+  print(slope)
+}
+```
+
+## purrr::map
+
+```{r}
+
+ datadf |>
+   select(1:7) |>
+   tidyr::nest(wqdf = -c(lon, lat)) |>
+   slice(1:10) |>
+   mutate(
+     m = purrr::map(
+       wqdf,
+       \(x) {
+         lm(formula = DO ~ pH, data = x)
+       }
+     )
+   ) |>
+   mutate(slope = purrr::map_dbl(m, \(x) coef(x)[2])) |>
+   mutate(
+     p = purrr::map(wqdf, \(x) {
+       x |>
+         ggplot(aes(x = pH, y = DO)) +
+         geom_smooth(method = "lm") +
+         geom_point()
+     })
+   ) |>
+   pull(p) |>
+   patchwork::wrap_plots() +
+   patchwork::plot_layout(ncol = 2)
+```
+
+
+
+
+