---
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)
```