利用R语言绘制世界航班路线图

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作者简介Introduction

taoyan：伪码农，R语言爱好者，爱开源。 个人博客: https://ytlogos.github.io/ 、


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 locations flights_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 lists flights_fortified <- do.call(“rbind”, flights_fortified)

Add and clean column with airline names flights_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$name == “Air China”, ]) + geom_point(data = flights_points[flights_points$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

本文作者： 艾瑞可erik
本文链接： https://erik.xyz/2018/04/17/r-yu-yan-hui-zhi-shi-jie-hang-ban-xian-lu-tu/
版权声明： 本作品采用 知识共享署名-非商业性使用-相同方式共享 4.0 国际许可协议 进行许可。转载请注明出处！
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    缺失模块。
    1、请确保node版本大于6.2
    2、在博客根目录（注意不是yilia根目录）执行以下命令：
    npm i hexo-generator-json-content --save

    3、在根目录_config.yml里添加配置： 

      jsonContent:
    meta: false
    pages: false
    posts:
      title: true
      date: true
      path: true
      text: false
      raw: false
      content: false
      slug: false
      updated: false
      comments: false
      link: false
      permalink: false
      excerpt: false
      categories: false
      tags: true

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