RStudio__temp_mm.R

library(tidyverse)
#temp
dates <- seq.Date(lubridate::dmy("1-6-2020"), lubridate::dmy("15-12-2020"), by = "1 day")
temp <- metR::GetSMNData(dates, type = "daily", bar = TRUE)
# temp %>% distinct(station) %>% pull()

temp %>% 
  filter(station == "TANDIL AERO") %>% 
  mutate(date = as.Date(date)) %>% 
  ggplot()+
  aes(x=date, y = tmin)+ 
  geom_line(aes(col = "mín"))+
  geom_line(aes(y = tmax, col= "máx"))+
  theme_bw()+
  labs(title = "Temperatura", x = "", y = "°C")+
  # scale_x_date(date_labels = "%B")
  scale_color_manual(name = NULL,values = c(
    'mín' = 'steelblue',
    'máx' = 'red3'))+
  scale_x_date(breaks="month", labels=scales::date_format("%b"))+
  theme(legend.justification = c(0, 1), legend.position = c(0.01, 0.98)) -> temp_p
temp_p

#mm 
coop_dir = tempfile(fileext = ".xls")
dataURL <- "http://coopnecochea.com/web/download/lluvias/Lluvias-2020.xls"
download.file(dataURL, destfile=coop_dir)

total_2020 <- tibble(mes = coop_dir %>% readxl::excel_sheets()) %>% 
  mutate(data = map(mes, ~readxl::read_excel(coop_dir, sheet = .x) %>% 
                      mutate_all(as.character))) %>% 
  slice(n()) %>% 
  unnest(cols = c(data)) %>% 
  drop_na(Lugar)

total_2020 %>% 
  select(-TOTAL,-mes) %>% 
  pivot_longer(cols = c(`ENE`:`DIC`), 
               names_to = "mes", 
               values_to = "mm") %>%
  filter(Lugar == "Balcarce", 
         mes %in% c("JUN", "JUL", "AGO", "SEP", "OCT", "NOV", "DIC")) %>% 
  mutate(mes = tolower(mes),
         mes = as.factor(mes),
         mes = fct_relevel(mes, "jun", "jul", "ago", "sep", "oct", "nov", "dic"),
         mm = as.numeric(mm)) %>% 
  ggplot()+
  aes(x = mes, y=mm)+
  geom_col(fill = "steelblue")+
  geom_text(aes(label = mm, x = mes, y = mm, vjust= 1.2), size =3, col = "white")+
  theme_bw()+
  labs(title = "Precipitaciones acumuladas mensuales", x = "")->mm_p

library(patchwork)
(temp_p + mm_p) 
ggsave(last_plot(), file = "temp_mm.png", width = 8, height = 4)