# BƯỚC 1: DOWNLOAD DATASET library(FAOSTAT) # download dataset QCL lưu ở thư mục project crop_production <- get_faostat_bulk(code = "QCL", data_folder = "./") saveRDS(crop_production, "crop_production_e_all_data.rds") # BƯỚC 2: LÀM SẠCH DỮ LIỆU library(dplyr) library(tidyr) library(DT) crop_production <- readRDS("crop_production_e_all_data.rds") dim(crop_production) ## tách riêng dataset của Việt Nam vietnam_data <- subset(crop_production, area == "Viet Nam") dim(vietnam_data) ## subset dữ liệu Flag A từ nguồn chính thức do Việt Nam công bố vietnam_data_a <- subset(vietnam_data, flag == "A") dim(vietnam_data_a) ## chọn những cột cần thiết vietnam_crop <- vietnam_data_a[, c("item", "element", "year", "unit", "value")] ## sắp xếp theo năm và thông tin nông sản vietnam <- vietnam_crop %>% dplyr::arrange(desc(year), desc(item), desc(element)) str(vietnam) as.data.frame(table(vietnam$item)) -> df_1 ## chúng ta có clean dataset để đưa vào phân tích giai đoạn sau datatable(vietnam, options = list(pageLength = 30)) # BƯỚC 3: LỌC DỮ LIỆU VỀ LÚA GẠO ĐƯA VÀO ĐỒ THỊ rice <- subset(vietnam, item == "Rice") rice_ok <- subset(rice, element != "yield") rice_ok <- subset(rice_ok, select = -unit) head(rice_ok) rice_final <- rice_ok %>% tidyr::spread(key = "element", value = "value") # head(rice_final) # na.omit(rice_final) -> rice_final write.csv(rice_final, "rice_final_vietnam.csv", row.names = FALSE) # BƯỚC 4: VẼ ĐỒ THỊ rm(list = ls()) rice_final <- read.csv("rice_final_vietnam.csv") # head(rice_final) library(ggplot2) library(extrafont) windows() windows(width = 8, height = 6) windows(height = 6, width = 8) windows(8, 6) windows(6, 8) font_chu <- "Times New Roman" # library(Cairo) # Cairo::CairoPNG( # width = 8, # height = 6, # file = "rice_vn_cario_dpi_900.png", # bg = "white", # dpi = 900, # units = "in" # ) # # png(filename = "rice_vn_baser_dpi_900.png", # width = 8, height = 6, units = "in", # res = 900) p <- ggplot( data = rice_final, aes(x = year, y = production / 1000000, size = area_harvested / 1000, fill = production/area_harvested) ) + geom_point(shape = 21, colour = "red", alpha = 0.5, show.legend = TRUE) + scale_x_continuous(expand = c(0, 0), limits = c(1955, 2025), name = "Năm", breaks = c(1961, 1980, 2000, 2021) ) + scale_y_continuous(expand = c(0, 0), limits = c(0, 1.15 * max(rice_final$production) / 1000000), name = "Sản lượng thu hoạch (triệu tấn)" ) + scale_size_continuous(name = "Diện tích canh tác (nghìn/ha)", breaks = seq(from = 8000, to = 4000, by = -1000), limits = c(4000, 8000), range = c(1, 7), guide = guide_legend(order = 1, # direction = "horizontal" )) + # scale_fill_continuous(name = "Năng suất (tấn/ha)", # guide = guide_colourbar(barwidth = 1, barheight = 8, # order = 2), # limits = c(1, 10), # breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10), # labels = c(1, "", 3, "", 5, "", 7, "", "", 10), # type = "viridis") # # scale_fill_gradient(name = "Năng suất (tấn/ha)", # guide = guide_colourbar(barwidth = 1, barheight = 8, # order = 2), # limits = c(1, 10), # breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10), # labels = c(1, "", 3, "", 5, "", 7, "", "", 10), # high = "red", # low = "yellow") # scale_fill_viridis_c(name = "Năng suất (tấn/ha)", # guide = guide_colourbar(barwidth = 1, barheight = 8, # order = 2), # limits = c(1, 10), # breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10), # labels = c(1, "", 3, "", 5, "", 7, "", "", 10), # option = "D" # ) # scale_fill_gradient2(name = "Năng suất (tấn/ha)", # guide = guide_colourbar(barwidth = 1, barheight = 8, # order = 2), # limits = c(1, 10), # breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10), # labels = c(1, "", 3, "", 5, "", 7, "", "", 10), # high = "red", # mid = "green", # midpoint = 5, # low = "yellow") scale_fill_gradientn(name = "Năng suất (tấn/ha)", guide = guide_colourbar(barwidth = 1, barheight = 8, order = 2), # guide = "none", limits = c(1, 10), breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10), labels = c(1, "", 3, "", 5, "", 7, "", "", 10), # colours = c("#00ffff", "#FFF0D9", "#FFD391", "#ff4e41", "#ff3122") colours = c("#440154","#482878","#3e4989","#31688e","#26828e","#1f9e89","#35b779","#6ece58","#b5de2b","#fde725") ) + ############### theming đồ thị ## set một theme chung cho toàn đồ thị theme_classic() + ## đưa thông tin tiêu đề đồ thị labs(title = "Tình hình sản xuất lúa gạo ở Việt Nam từ 1960–2021", subtitle = "Nguồn: FAOSTAT [crop dataset, Vietnam, flag A]", caption = "Đồ thị: Duc Nguyen | tuhocr.com") + ## format text trong đồ thị theme(plot.title = element_text(size = "12", family = "Times New Roman", face = "bold", colour = "black", angle = 0, hjust = 0, vjust = 0, margin = margin(t = 0, r = 0, b = 10, l = 0, unit = "pt"))) + theme(plot.subtitle = element_text(size = "11", family = "Times New Roman", face = "plain", colour = "black", angle = 0, hjust = 0, vjust = 0, margin = margin(t = 0, r = 0, b = 10, l = 0, unit = "pt"))) + theme(plot.caption = element_text(size = "10", family = "Times New Roman", face = "plain", colour = "black", angle = 0, hjust = 1, vjust = 0, margin = margin(t = 0, r = 0, b = 0, l = 0, unit = "pt"))) + ## customize panel và margin của plot theme(panel.background = element_rect(fill = "white", colour = "white", linewidth = 0), plot.background = element_rect(fill = "grey90"), plot.margin = margin(t = 0.5, r = 0.5, b = 0.5, l = 0.5, unit = "cm")) + ## customize 2 trục đồ thị theme(axis.text.x = element_text(face = "bold", colour = "#993333", size = 10, family = "Times New Roman"), axis.text.y = element_text(face = "bold", colour = "#993333", size = 10, family = "Times New Roman")) + theme(axis.title.x = element_text(face = "bold", colour = "black", size = 11, family = "Times New Roman"), axis.title.y = element_text(face = "bold", colour = "black", size = 11, family = "Times New Roman", margin = margin(t = 0, r = 10, b = 0, l = 0, unit = "pt"))) + ## customize legend theme(legend.background = element_rect(fill = "transparent", colour = "transparent", linewidth = 0)) + # theme(legend.background = element_blank()) theme(legend.position = "right") + # theme(legend.position = c(0.5, 0.5)) + theme(legend.justification = c("left", "bottom")) + theme(legend.title = element_text(face = "bold", colour = "black", size = 11, family = "Times New Roman", margin = margin(t = 0, r = 0, b = 10, l = 0, unit = "pt"))) + theme(legend.text = element_text(face = "plain", colour = "black", size = 10, family = "Times New Roman")) + theme(legend.direction = "vertical") #################################### ## chú thích đồ thị p + geom_hline(yintercept = 48, colour = "#148c34", linewidth = 1.2, linetype = 2) + annotate(geom = "text", x = 2000, y = 1.1 * max(rice_final$production) / 1000000, label = "Ngưỡng cực hạn 48 triệu tấn/năm", colour = "red") + geom_label(aes(x = 1975, y = 0.9 * max(production)/1000000, label = paste("Năm", max(year), "Việt Nam", "\nthu hoạch được", round(rice_final[rice_final$year == max(rice_final$year), ]$production/1000000, digits = 0), "triệu tấn gạo", "\ntrên diện tích canh tác", round(rice_final[rice_final$year == max(rice_final$year), ]$area_harvested/1000, digits = 0), "nghìn ha", "\nnăng suất là", round(rice_final[rice_final$year == max(rice_final$year), ]$production/rice_final[rice_final$year == max(rice_final$year), ]$area_harvested, digits = 2), "tấn/ha")), fill = "#f5ec42", label.size = 0.15, size = 3.5) ########################## library(grid) library(gridExtra) library(png) logor <- readPNG("logor.png") # grid.raster(logor, x = 0.9, y = 0.9, width = 0.1) ## adjust opacity/transparent of image logor -> m w <- matrix(rgb(m[, , 1], m[, , 2], m[, , 3], m[, , 4] * 0.5), nrow = dim(m)[1]) # 0.5 is alpha grid.raster(w, x = 0.9, y = 0.9, width = 0.1) # download.file(url = "https://tuhocr.netlify.app/rice.png", # destfile = "rice.png", # mode = "wb") rice <- readPNG("rice.png") grid.raster(rice, x = 0.56, y = 0.24, width = 0.23) dev.copy(device = png, filename = "rice_vn_dev_dpi_90.png", width = 8, height = 6, units = "in", res = 90) # ggsave(filename = "rice_vn_ggsave_dpi_900.png", # width = 8, # height = 6, # units = "in", # dpi = 900) dev.off() # The ggplot2 package is built on top of grid package graphics. # # A grid graphical object (grob). # # Viewports are the plotting windows that you can move into and out of # to customize plots using grid graphics. # TÀI LIỆU THAM KHẢO # https://stackoverflow.com/questions/70942728/understanding-color-scales-in-ggplot2 # https://stackoverflow.com/questions/13143894/how-do-i-position-two-legends-independently-in-ggplot # https://stackoverflow.com/questions/52060601/ggplot-multiple-legends-arrangement # https://kohske.wordpress.com/2010/12/25/various-position-adjustments-of-legend-in-ggplot2/ # https://stackoverflow.com/questions/11357926/r-add-alpha-value-to-png-image # https://iruler.net/ # https://www.cloudbees.com/blog/what-is-the-difference-between-implicit-vs-explicit-programming # https://www.cloudbees.com/blog/what-is-the-difference-between-implicit-vs-explicit-programming # http://adv-r.had.co.nz/Style.html # https://style.tidyverse.org/ # https://styler.r-lib.org/ # https://studyr.netlify.app/script/fao.html