rm(list=ls(all=TRUE)) # Limpa memória gc() # Define working directory setwd("/cloud/project/LCF5900") # Load packages if(!require(tidyverse)) install.packages("tidyverse") library(tidyverse) if(!require(gganimate)) install.packages("gganimate") library(gganimate) # Define github URL where climate data from Piracicaba is stored url_1 <- "https://github.com/FlorestaR/dados/blob/main/X_PIRACLIM" xls_2 <- "DadosClima_Piracicaba.csv" prm_3 <- "?raw=true" gitFile <- file.path(url_1, xls_2) %>% paste0(prm_3) # Downloads Excel table as a tibble (dataframe) from github df <- read.csv(gitFile, sep=";") %>% tibble() # import # Show column names and first rows from the table colnames(df) head(df) tail(df) df <- df %>% select(ANO, MES, TMED, TMIN, TMAX, Chuva, Estiagem) %>% drop_na() %>% mutate_if(is.character,as.numeric) %>% filter(TMED <50) str(df) df %>% summarise(m_TMED = mean(TMED), m_TMIN = mean(TMIN), m_TMAX = mean(TMAX), m_Chuva = mean(Chuva), m_Estiagem = mean(Estiagem)) medMes <- group_by(df, ANO, MES) %>% summarise(tmedMes = mean(TMED)) p <- ggplot(medMes, aes(medMes$MES, medMes$tmedMes)) + geom_point() + # geom_smooth(method = "gam", formula = y ~ s(x, bs = "cs")) + ggtitle("{frame_time}") + transition_time(as.integer(medMes$ANO)) + ease_aes("linear") + enter_fade() + exit_fade() animate(p, width = 750, height = 450) anim_save(p, "grafGIF.gif") animate(p, renderer = ffmpeg_renderer(), width = 800, height = 450) anim_save("animGraf.mp4")