precip

```{r}
pacman::p_load(tidyverse)
```

```{r, eval=FALSE}
dataURL <- "http://coopnecochea.com/web/download/lluvias/Lluvias-2021.xls"
download.file(dataURL, destfile=data)
```


```{r}
prec21_raw <- tibble(
  mes = "data/Lluvias-2021.xls" %>% readxl::excel_sheets()) %>% filter(mes!="TOTAL AÑO 2021") %>% 
  mutate(
    data = map(mes, ~readxl::read_excel("data/Lluvias-2021.xls", 
                                        sheet = .x, 
                                        n_max=15) %>% 
                 mutate_all(as.character))) %>%
  unnest(cols = c(data)) 

prec21 <- prec21_raw  %>%  
  select(-TOTAL) %>% 
  replace(is.na(.), "0") %>% 
  mutate(across(everything(), ~str_replace(., "-----", "0"))) %>% 
  # mutate(across(matches("[1-9]"), as.numeric)) %>% 
  mutate_at(vars(`1`:`31`), as.numeric) %>% 
  left_join(
    prec21 %>% distinct(mes) %>% add_column(month=1:12)
    ) %>% 
  relocate(month) %>% 
  pivot_longer(cols = c(`1`:`31`), 
               names_to = "dia", 
               values_to = "mm") %>% 
  mutate(day = lubridate::parse_date_time(paste0("2021/", month, "/", dia), "y / m / d")) %>% 
  mutate(mm=replace_na(mm, 0))

# prec21 %>% filter(is.na(mes))
```


```{r}
prec21 %>% 
  group_by(Lugar,month) %>% 
  summarise(mm=sum(as.numeric(mm))) %>%
  ggplot()+
  aes(x = month, y=mm)+
  geom_col(fill = "steelblue")+
  facet_wrap("Lugar")+
  cowplot::theme_minimal_hgrid(font_size=9)+
  scale_x_continuous(breaks=seq(1,12,1), labels=1:12)+ 
  labs(title = "Precipitaciones 2021",
       x = "", 
       subtitle = "Datos obtenidos de coopnecochea.com") + 
  geom_text(data = . %>% group_by(Lugar) %>% summarise(mm = sum(mm)),
            aes(label = paste0(mm, "mm"), x = Inf, y = Inf, vjust= 1, hjust=1), 
            size =2)  
```