利用R语言绘制世界航班路线图

作者简介Introductiontaoyan：伪码农，R语言爱好者，爱开源。个人博客: https://ytlogos.github.io/公众号：生信大讲堂
往期回顾R语言可视化学习笔记之相关矩阵可视化包ggcorrplot
R语言学习笔记之相关性矩阵分析及其可视化
ggplot2学习笔记系列之利用ggplot2绘制误差棒及显著性标记

ggplot2学习笔记系列之主题（theme）设置

用circlize包绘制circos-plot




一、 简介
本文基于NASA的夜间地图（https://www.nasa.gov/specials/blackmarble/2016/globalmaps/BlackMarble_2016_01deg.jpg）的基础上进行世界航班路线可视化，参考多篇博客以及可视化案例。1. 包加载本博客使用的包较多，利用pacman包里的p_load()函数进行加载
library(pacman)p_load(tidyverse, data.table, geosphere, grid, jpeg, plyr)    2. 数据准备使用的数据来自于OpenFlights.org（https://openflights.org/data.html）。3.数据下载download.file("https://raw.githubusercontent.com/jpatokal/openflights/master/data/airlines.dat",destfile = "airlines.dat", mode = "wb")download.file("https://raw.githubusercontent.com/jpatokal/openflights/master/data/airports.dat",destfile = "airports.dat", mode = "wb")download.file("https://raw.githubusercontent.com/jpatokal/openflights/master/data/routes.dat",destfile = "routes.dat", mode = "wb")4.数据导入
airlines <- fread("airlines.dat", sep = ",", skip = 1)airports <- fread("airports.dat", sep = ",")routes <- fread("routes.dat", sep = ",")5. 数据整理#添加列名colnames(airlines) <- c("airline_id", "name", "alias", "iata", "icao", "callisign", "country", "active")colnames(airports) <- c("airport_id", "name", "city", "country","iata", "icao", "latitude", "longitude","altitude", "timezone","dst","tz_database_time_zone","type", "source")colnames(routes) <- c("airline", "airline_id", "source_airport", "source_airport_id","destination_airport","destination_airport_id","codeshare", "stops","equipment")#类型转换routes$airline_id <- as.numeric(routes$airline_id)# airlines与routes数据融合flights <- left_join(routes, airlines, by="airline_id")# flights与airports数据融合airports_orig <- airports[,c(5,7,8)]colnames(airports_orig) <- c("source_airport","source_airport_lat", "source_airport_long")airports_dest <- airports[, c(5, 7, 8)]colnames(airports_dest) <- c("destination_airport", "destination_airport_lat", "destination_airport_long")flights <- left_join(flights, airports_orig, by = "source_airport")flights <- left_join(flights, airports_dest, by = "destination_airport")#剔除缺失值flights <- na.omit(flights, cols = c("source_airport_long", "source_airport_lat", "destination_airport_long", "destination_airport_lat"))#最后数据如下head(flights[,c(1:5)])    6. 下面就是准备地理信息数据本文主要是可视化地理信息上的点与点之间的连接，这可以通过geosphere包里的函数gcIntermediate()很轻松实现。具体使用方法可以参考这里（http://flowingdata.com/2011/05/11/how-to-map-connections-with-great-circles/）。
# 按航空公司拆分数据集flights_split <- split(flights, flights$name)# Calculate intermediate points between each two locationsflights_all <- lapply(flights_split, function(x) gcIntermediate(x[, c("source_airport_long", "source_airport_lat")], x[, c("destination_airport_long", "destination_airport_lat")], n=100, breakAtDateLine = FALSE, addStartEnd = TRUE, sp = TRUE))
# 转换为数据框flights_fortified <- lapply(flights_all, function(x) ldply(x@lines, fortify))
# Unsplit listsflights_fortified <- do.call("rbind", flights_fortified)
# Add and clean column with airline namesflights_fortified$name <- rownames(flights_fortified)flights_fortified$name <- gsub("\\..*", "", flights_fortified$name)
# Extract first and last observations for plotting source and destination points (i.e., airports)flights_points <- flights_fortified %>%    group_by(group) %>%    filter(row_number() == 1 | row_number() == n())    二、 可视化接下来就是进行可视化了，前面讲了我们只是在NASA提供的夜间地球图上面进行数据映射，所以第一我们需要获取该背景地图。1. 图片获取并渲染#下载图片
download.file("https://www.nasa.gov/specials/blackmarble/2016/globalmaps/BlackMarble_2016_01deg.jpg",destfile = "BlackMarble_2016_01deg.jpg", mode = "wb")
#加载并渲染图片
earth <- readJPEG("BlackMarble_2016_01deg.jpg", native = TRUE)earth <- rasterGrob(earth, interpolate = TRUE)
2. 数据映射由于航空公司十分多，就挑选几个有名的航空公司进行可视化。(1) Lufthansa(德国汉莎航空公司)ggplot() +annotation_custom(earth, xmin = -180, xmax = 180, ymin = -90, ymax = 90) +geom_path(aes(long, lat, group = id, color = name), alpha = 0.0, size = 0.0, data = flights_fortified) +geom_path(aes(long, lat, group = id, color = name), alpha = 0.2, size = 0.3, color = "#f9ba00", data = flights_fortified[flights_fortified$name == "Lufthansa", ]) +geom_point(data = flights_points[flights_points$name == "Lufthansa", ], aes(long, lat), alpha = 0.8, size = 0.1, colour = "white") +theme(panel.background = element_rect(fill = "#05050f", colour = "#05050f"),panel.grid.major = element_blank(),panel.grid.minor = element_blank(),axis.title = element_blank(),axis.text = element_blank(),axis.ticks.length = unit(0, "cm"),legend.position = "none") +annotate("text", x = -150, y = -18, hjust = 0, size = 14,label = paste("Lufthansa"), color = "#f9ba00", family = "Helvetica Black") +annotate("text", x = -150, y = -26, hjust = 0, size = 8,label = paste("Flight routes"), color = "white") +annotate("text", x = -150, y = -30, hjust = 0, size = 7,label = paste("ytlogos.github.io || NASA.gov || OpenFlights.org"), color = "white", alpha = 0.5) +coord_equal()

(2) Emirates(阿联酋航空公司)
ggplot() +annotation_custom(earth, xmin = -180, xmax = 180, ymin = -90, ymax = 90) +geom_path(aes(long, lat, group = id, color = name), alpha = 0.0, size = 0.0, data = flights_fortified) +geom_path(aes(long, lat, group = id, color = name), alpha = 0.2, size = 0.3, color = "#ff0000", data = flights_fortified[flights_fortified$name == "Emirates", ]) +geom_point(data = flights_points[flights_points$name == "Emirates", ], aes(long, lat), alpha = 0.8, size = 0.1, colour = "white") +theme(panel.background = element_rect(fill = "#05050f", colour = "#05050f"),panel.grid.major = element_blank(),panel.grid.minor = element_blank(),axis.title = element_blank(),axis.text = element_blank(),axis.ticks.length = unit(0, "cm"),legend.position = "none") +annotate("text", x = -150, y = -18, hjust = 0, size = 14,label = paste("Emirates"), color = "#ff0000", family = "Fontin") +annotate("text", x = -150, y = -26, hjust = 0, size = 8,label = paste("Flight routes"), color = "white") +annotate("text", x = -150, y = -30, hjust = 0, size = 7,label = paste("ytlogos.github.io || NASA.gov || OpenFlights.org"), color = "white", alpha = 0.5) +coord_equal()


(3) British Airways(英国航空公司)
ggplot() +annotation_custom(earth, xmin = -180, xmax = 180, ymin = -90, ymax = 90) +geom_path(aes(long, lat, group = id, color = name), alpha = 0.0, size = 0.0, data = flights_fortified) +geom_path(aes(long, lat, group = id, color = name), alpha = 0.2, size = 0.3, color = "#075aaa", data = flights_fortified[flights_fortified$name == "British Airways", ]) +geom_point(data = flights_points[flights_points$name == "British Airways", ], aes(long, lat), alpha = 0.8, size = 0.1, colour = "white") +theme(panel.background = element_rect(fill = "#05050f", colour = "#05050f"),panel.grid.major = element_blank(),panel.grid.minor = element_blank(),axis.title = element_blank(),axis.text = element_blank(),axis.ticks.length = unit(0, "cm"),legend.position = "none") +annotate("text", x = -150, y = -18, hjust = 0, size = 14,label = paste("BRITISH AIRWAYS"), color = "#075aaa", family = "Baker Signet Std") +annotate("text", x = -150, y = -26, hjust = 0, size = 8,label = paste("Flight routes"), color = "white") +annotate("text", x = -150, y = -30, hjust = 0, size = 7,label = paste("ytlogos.github.io || NASA.gov || OpenFlights.org"), color = "white", alpha = 0.5) +coord_equal()   

(4) Air China(中国国航)
ggplot() +annotation_custom(earth, xmin = -180, xmax = 180, ymin = -90, ymax = 90) +geom_path(aes(long, lat, group = id, color = name), alpha = 0.0, size = 0.0, data = flights_fortified) +geom_path(aes(long, lat, group = id, color = name), alpha = 0.2, size = 0.3, color = "#F70C15", data = flights_fortified[flights_fortified$name == "Air China"
eb76
, ]) +geom_point(data = flights_points[flights_points$name == "Air China", ], aes(long, lat), alpha = 0.8, size = 0.1, colour = "white") +theme(panel.background = element_rect(fill = "#05050f", colour = "#05050f"),panel.grid.major = element_blank(),panel.grid.minor = element_blank(),axis.title = element_blank(),axis.text = element_blank(),axis.ticks.length = unit(0, "cm"),legend.position = "none") +annotate("text", x = -150, y = -18, hjust = 0, size = 14,label = paste("Air China"), color = "#F70C15", family = "Times New Roman") +annotate("text", x = -150, y = -26, hjust = 0, size = 8,label = paste("Flight routes"), color = "white") +annotate("text", x = -150, y = -30, hjust = 0, size = 7,label = paste("ytlogos.github.io || NASA.gov || OpenFlights.org"), color = "white", alpha = 0.5) +coord_equal()   


(5) China Southern Airlines(中国南航)ggplot() +annotation_custom(earth, xmin = -180, xmax = 180, ymin = -90, ymax = 90) +geom_path(aes(long, lat, group = id, color = name), alpha = 0.0, size = 0.0, data = flights_fortified) +geom_path(aes(long, lat, group = id, color = name), alpha = 0.2, size = 0.3, color = "#004D9D", data = flights_fortified[flights_fortified$name == "China Southern Airlines", ]) +geom_point(data = flights_points[flights_points$name == "China Southern Airlines", ], aes(long, lat), alpha = 0.8, size = 0.1, colour = "white") +theme(panel.background = element_rect(fill = "#05050f", colour = "#05050f"),panel.grid.major = element_blank(),panel.grid.minor = element_blank(),axis.title = element_blank(),axis.text = element_blank(),axis.ticks.length = unit(0, "cm"),legend.position = "none") +annotate("text", x = -150, y = -18, hjust = 0, size = 14,label = paste("China Southern Airlines"), color = "#004D9D", family = "Times New Roman") +annotate("text", x = -150, y = -26, hjust = 0, size = 8,label = paste("Flight routes"), color = "white") +annotate("text", x = -150, y = -30, hjust = 0, size = 7,label = paste("ytlogos.github.io || NASA.gov || OpenFlights.org"), color = "white", alpha = 0.5) +coord_equal()

(6) 一次性映射多家航空公司航行路线
#抽取数据集flights_subset <- c("Lufthansa", "Emirates", "British Airways")flights_subset <- flights_fortified[flights_fortified$name %in% flights_subset, ]flights_subset_points <- flights_subset%>%group_by(group)%>%filter(row_number()==1|row_number()==n())#可视化ggplot() +annotation_custom(earth, xmin = -180, xmax = 180, ymin = -90, ymax = 90) +geom_path(aes(long, lat, group = id, color = name), alpha = 0.2, size = 0.3, data = flights_subset) +geom_point(data = flights_subset_points, aes(long, lat), alpha = 0.8, size = 0.1, colour = "white") +scale_color_manual(values = c("#f9ba00", "#ff0000", "#075aaa")) +theme(panel.background = element_rect(fill = "#05050f", colour = "#05050f"),panel.grid.major = element_blank(),panel.grid.minor = element_blank(),axis.title = element_blank(),axis.text = element_blank(),axis.ticks.length = unit(0, "cm"),legend.position = "none") +annotate("text", x = -150, y = -4, hjust = 0, size = 14,label = paste("Lufthansa"), color = "#f9ba00", family = "Helvetica Black") +annotate("text", x = -150, y = -11, hjust = 0, size = 14,label = paste("Emirates"), color = "#ff0000", family = "Fontin") +annotate("text", x = -150, y = -18, hjust = 0, size = 14,label = paste("BRITISH AIRWAYS"), color = "#075aaa", family = "Baker Signet Std") +annotate("text", x = -150, y = -30, hjust = 0, size = 8,label = paste("Flight routes"), color = "white") +annotate("text", x = -150, y = -34, hjust = 0, size = 7,label = paste("ytlogos.github.io || NASA.gov || OpenFlights.org"), color = "white", alpha = 0.5) +coord_equal()

三、 SessionInfo    
sessionInfo()R version 3.4.3 (2017-11-30)Platform: x86_64-w64-mingw32/x64 (64-bit)Running under: Windows >= 8 x64 (build 9200)Matrix products: default
locale:[1] LC_COLLATE=Chinese (Simplified)_China.936  LC_CTYPE=Chinese (Simplified)_China.936[3] LC_MONETARY=Chinese (Simplified)_China.936 LC_NUMERIC=C[5] LC_TIME=Chinese (Simplified)_China.936
attached base packages:[1] grid      stats     graphics  grDevices utils     datasets  methods   base
other attached packages:[1] plyr_1.8.4          jpeg_0.1-8          geosphere_1.5-7     data.table_1.10.4-3[5] forcats_0.2.0       stringr_1.2.0       dplyr_0.7.4         purrr_0.2.4[9] readr_1.1.1         tidyr_0.8.0         tibble_1.4.2        ggplot2_2.2.1.9000[13] tidyverse_1.2.1     pacman_0.4.6
loaded via a namespace (and not attached): [1] Rcpp_0.12.15      cellranger_1.1.0  pillar_1.1.0      compiler_3.4.3    bindr_0.1 [6] tools_3.4.3       lubridate_1.7.1   jsonlite_1.5      nlme_3.1-131      gtable_0.2.0[11] lattice_0.20-35   pkgconfig_2.0.1   rlang_0.1.6       psych_1.7.8       cli_1.0.0[16] rstudioapi_0.7    yaml_2.1.16       parallel_3.4.3    haven_1.1.1       bindrcpp_0.2[21] xml2_1.2.0        httr_1.3.1        knitr_1.19        hms_0.4.1         glue_1.2.0[26] R6_2.2.2          readxl_1.0.0      foreign_0.8-69    sp_1.2-7          modelr_0.1.1[31] reshape2_1.4.3    magrittr_1.5      scales_0.5.0.9000 rvest_0.3.2     assertthat_0.2.0[36] mnormt_1.5-5      colorspace_1.3-2  stringi_1.1.6     lazyeval_0.2.1    munsell_0.4.3[41] broom_0.4.3       crayon_1.3.4   
   

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