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library(ggpubr)
x <- 1:100
y <- (x + x^2 + x^3) + rnorm(length(x), mean = 0, sd = mean(x^3) / 4)
my.data <- data.frame(x, y, group = c("A", "B"),
                      y2 = y * c(0.5,2), block = c("a", "a", "b", "b"))

# Fit polynomial regression line and add labels
formula <- y ~ poly(x, 3, raw = TRUE)
p <- ggplot(my.data, aes(x, y2, color = group)) +
  geom_point() +

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# library("googledrive")
library("googlesheets4")
library("tidyverse")
library("ggpubr")

# drive_auth(use_oob = TRUE, cache = TRUE)
# 
mysheets <- googledrive::drive_find(type = "spreadsheet")
mysheets
# reuse token to Sheet Auth. 

juanchiem

# https://itsalocke.com/blog/understanding-rolling-calculations-in-r/
# https://inta.gob.ar/sites/default/files/inta_impacto_de_los_factores_ambientales_en_la_definicion_de_los_rendimientos_de_los_cultivos_resultados_de_la_campana_2013_de_trigo.pdf
# http://rafaela.inta.gov.ar/info/miscelaneas/101/trigo2004_n1.pdf 

library(tidyverse)
library(lubridate)

stations <- tibble::tribble(
              ~station,   ~lat,   ~lon,
       "Balcarce INTA", -37.75,  -58.3,

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# https://itsalocke.com/blog/understanding-rolling-calculations-in-r/
# https://inta.gob.ar/sites/default/files/inta_impacto_de_los_factores_ambientales_en_la_definicion_de_los_rendimientos_de_los_cultivos_resultados_de_la_campana_2013_de_trigo.pdf
# http://rafaela.inta.gov.ar/info/miscelaneas/101/trigo2004_n1.pdf 

pacman::p_load(tidyverse, lubridate, zoo)

stations <- tibble::tribble(
              ~station,   ~lat,   ~lon,
       "Balcarce INTA", -37.75,  -58.3,
  "Mar del Plata AERO", -37.93, -57.58,

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library(tidyverse)
library(patchwork)

dat_wide <- tibble(
  x = 1:3,
  top = c(4.5, 4, 5.5),
  middle = c(4, 4.75, 5),
  bottom = c(3.5, 3.75, 4.5)
)

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library(tidyverse)
library(ggforce)

tibble::tribble(
  ~patogeno, ~hum_min, ~hum_max, ~temp_min, ~temp_max,
  "RE",3L,6L,8L,14L,
  "RH",6L,10L,18L,25L,
  "RT",8L,12L,20L,30L,
  "MA",28L,32L,18L,28L,
  "SEP",72L,96L,10L,15L) %>% 

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library(ggplot2)

pic <- magick::image_read("https://i.imgur.com/GOjBfBu.png")

(tibble::tribble(
  ~patogeno, ~hum_min, ~hum_max, ~temp_min, ~temp_max,
  "Esc",48L,58L,8L,15L,
  "Red",36L,46L,10L,18L,
  "MB",48L,58L,20L,24L,
  "Ram",16L,26L,15L,20L) %>% 

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library(ggplot2)
ggplot() +
  geom_col(aes(x =  lubridate::month(1:12, label = TRUE, abbr = T),
               y = c(5,2,0,60,80,20,22,6,2,8,22,7)))+
  labs(x = "", y = "pl/m²")
             

                          
           

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library(extrafont)
download.file("http://simonsoftware.se/other/xkcd.ttf",
              dest="xkcd.ttf", mode="wb")
system("mkdir ~/.fonts")
system("cp xkcd.ttf  ~/.fonts")
font_import(paths = "~/.fonts", pattern="[X/x]kcd")
fonts()
loadfonts()

ggplot(data.frame(x = c(0, 1)), aes(x = x)) +

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devtools::install_github("graysonwhite/gglm")
library(gglm) # Load the package
data(mtcars) # Load example data
model <- lm(mpg ~ ., data = mtcars) # Create your model
gglm(model) #