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Script.R
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#if (!require("XML")) { install.packages("XML"); require("XML") }
if (!require("ggplot2")) { install.packages("ggplot2"); require("ggplot2") }
#if (!require("RCurl")) { install.packages("RCurl"); require("RCurl") }
if (!require("qdap")) { install.packages("qdap"); require("qdap") }
if (!require("rvest")) { install.packages("rvest"); require("rvest") }
if (!require("RJSONIO")) { install.packages("RJSONIO"); require("RJSONIO") }
if (!require("RCurl")) { install.packages("RCurl"); require("RCurl") }
#if (!require("xlsx")) { install.packages("xlsx"); require("xlsx") }
#if (!require("rJava")) { install.packages("rJava"); require("rJava") }
#if (!require("mclust")) { install.packages("mclust"); require("mclust") }
library(gridExtra)
PlotsOutput = T
dataDir = "C:/Users/stepa/OneDrive/DataScience/Airports/Schedule/AirportsSchedule/Data"
plotDir = "C:/Users/stepa/OneDrive/DataScience/Airports/Schedule/AirportsSchedule/Plots"
#ddd = c(983245, 1230601, 1501318)
#diff(ddd)[2] / diff(ddd)[1]
# Parsing Airports of Regions ----
#u = "http://rov.aero/raspisanie_reysov"
#u = file.path(paste(dataDir, "/Data/", "/Platov_12.06.html", sep = ""))
u_Platov = paste(dataDir, "/Platov_13.08.html", sep ="")
u_Samara = paste(dataDir, "/Kuf_13.08.html", sep = "")
u_Ekb = paste(dataDir, "/SVX_13.08.html", sep = "")
u_NiNo = paste(dataDir, "/Goj_13.08.html", sep = "")
u = u_Ekb
AllDayRepeats = function(from1, to1, i) {
df_dates = seq(from1, to1, by = "days")
df_dates_2 = as.integer(format(seq(from1, to1, by = "days"), "%w"))
df_dates_2[df_dates_2 == 0] = 7
return(df_dates[df_dates_2 == i])
}
AR_schedule_parser = function(u, Geo, from2, to2) {
tables = read_html(u, options = c("HUGE"))
tables2 = html_nodes(tables, "table")
city = as.character(html_nodes(tables, "caption"))
city = gsub("<caption>", "", city)
city = gsub("</caption>", "", city)
li = html_table(tables, fill = T)
df_tmp = data.frame(Ðåéñ = NA, Ñàìîë¸ò = NA, Íàïðàâëåíèå = NA, Ðàñïèñàíèå = "2000-01-01 00:00:00", stringsAsFactors = F)
df_tmp[[4]] = as.POSIXlt(df_tmp[, 4], tz = "GMT")
j = 54
for (j in c(2:(length(city)+1))) {
#length(html_table(tables, fill = T)))) {
df2 = html_table(tables, fill = T)[[j]]
flight = as.character(html_nodes(tables2[j], "font"))
flight = gsub("<font class=\"daflight\">","",flight)
flight = gsub("</font>", "", flight)
jet = NULL
for (k in c(1:dim(df2)[1])) {
jet = c(jet,gsub(pattern = flight[k], replacement = "", df2[k, 1]))
}
data.frame(
Ðåéñ = df2[, 1],
Ðàñïèñàíèå = substr(df2[, 3], 1, 5)
)
tmp = gsub("ïåðèîä", "", df2[, 5])
from = substr(tmp, 1, 5)
to = substr(tmp, 7, 11)
from1 = as.POSIXlt(paste(from, ".", year, sep = ""), format = "%d.%m.%Y")
to1 = as.POSIXlt(paste(to, ".", year, sep = ""), format = "%d.%m.%Y")
#AllDayRepeats( from1[1], to1[1], 4)
#as.POSIXlt(paste(AllDayRepeats(from1[1], to1[1], 4), " ", substr(df2[1, 3], 1, 5), ":00", sep = ""), tz = "GMT")
#Sys.timezone(location = TRUE)
#i = 9
for (i in c(1:dim(df2)[1])) {
if (length(grep("ïí", gsub("äíè ïðèáûòèÿ ðåéñîâ", "", df2[i, 6]))) > 0) {
if (length(AllDayRepeats(from1[i], to1[i], 1)) > 0) {
df_tmp = rbind(df_tmp, data.frame(
Ðåéñ = flight[i],
Ñàìîë¸ò = jet[i],
Íàïðàâëåíèå = city[j-1],
Ðàñïèñàíèå = as.POSIXlt(paste(AllDayRepeats(from1[i], to1[i], 1), " ", substr(df2[i, 3], 1, 5), ":00", sep = ""), tz = "GMT"), stringsAsFactors = F))
}
}
if (length(grep("âò", gsub("äíè ïðèáûòèÿ ðåéñîâ", "", df2[i, 6]))) > 0) {
if (length(AllDayRepeats(from1[i], to1[i], 2)) > 0) {
df_tmp = rbind(df_tmp, data.frame(
Ðåéñ = flight[i],
Ñàìîë¸ò = jet[i],
Íàïðàâëåíèå = city[j-1],
Ðàñïèñàíèå = as.POSIXlt(paste(AllDayRepeats(from1[i], to1[i], 2), " ", substr(df2[i, 3], 1, 5), ":00", sep = ""), tz = "GMT"), stringsAsFactors = F))
}
}
if (length(grep("ñð", gsub("äíè ïðèáûòèÿ ðåéñîâ", "", df2[i, 6]))) > 0) {
if (length(AllDayRepeats(from1[i], to1[i], 3)) > 0) {
df_tmp = rbind(df_tmp, data.frame(
Ðåéñ = flight[i],
Ñàìîë¸ò = jet[i],
Íàïðàâëåíèå = city[j-1],
Ðàñïèñàíèå = as.POSIXlt(paste(AllDayRepeats(from1[i], to1[i], 3), " ", substr(df2[i, 3], 1, 5), ":00", sep = ""), tz = "GMT"), stringsAsFactors = F))
}
}
if (length(grep("÷ò", gsub("äíè ïðèáûòèÿ ðåéñîâ", "", df2[i, 6]))) > 0) {
if (length(AllDayRepeats(from1[i], to1[i], 4)) > 0) {
df_tmp = rbind(df_tmp, data.frame(
Ðåéñ = flight[i],
Ñàìîë¸ò = jet[i],
Íàïðàâëåíèå = city[j-1],
Ðàñïèñàíèå = as.POSIXlt(paste(AllDayRepeats(from1[i], to1[i], 4), " ", substr(df2[i, 3], 1, 5), ":00", sep = ""), tz = "GMT"), stringsAsFactors = F))
}
}
if (length(grep("ïò", gsub("äíè ïðèáûòèÿ ðåéñîâ", "", df2[i, 6]))) > 0) {
if (length(AllDayRepeats(from1[i], to1[i], 5)) > 0) {
df_tmp = rbind(df_tmp, data.frame(
Ðåéñ = flight[i],
Ñàìîë¸ò = jet[i],
Íàïðàâëåíèå = city[j-1],
Ðàñïèñàíèå = as.POSIXlt(paste(AllDayRepeats(from1[i], to1[i], 5), " ", substr(df2[i, 3], 1, 5), ":00", sep = ""), tz = "GMT"), stringsAsFactors = F))
}
}
if (length(grep("ñá", gsub("äíè ïðèáûòèÿ ðåéñîâ", "", df2[i, 6]))) > 0) {
if (length(AllDayRepeats(from1[i], to1[i], 6)) > 0) {
df_tmp = rbind(df_tmp, data.frame(
Ðåéñ = flight[i],
Ñàìîë¸ò = jet[i],
Íàïðàâëåíèå = city[j-1],
Ðàñïèñàíèå = as.POSIXlt(paste(AllDayRepeats(from1[i], to1[i], 6), " ", substr(df2[i, 3], 1, 5), ":00", sep = ""), tz = "GMT"), stringsAsFactors = F))
}
}
if (length(grep("âñ", gsub("äíè ïðèáûòèÿ ðåéñîâ", "", df2[i, 6]))) > 0) {
if (length(AllDayRepeats(from1[i], to1[i], 7)) > 0) {
df_tmp = rbind(df_tmp, data.frame(
Ðåéñ = flight[i],
Ñàìîë¸ò = jet[i],
Íàïðàâëåíèå = city[j-1],
Ðàñïèñàíèå = as.POSIXlt(paste(AllDayRepeats(from1[i], to1[i], 7), " ", substr(df2[i, 3], 1, 5), ":00", sep = ""), tz = "GMT"), stringsAsFactors = F))
}
}
}
#sort( df_tmp[-c(1),], Ðàñïèñàíèå )
#gsub("äíè ïðèáûòèÿ ðåéñîâ", "", df2[, 6])
}
df_tmp = df_tmp[-c(1),]
df3 = cbind(df_tmp[, 1], df_tmp[, 4], data.frame(Îæèäàåòñÿ = rep(NA, dim(df_tmp)[1]), Ñòàòóñ = rep(NA, dim(df_tmp)[1]), Àâèàêîìïàíèÿ = substr( df_tmp$`Ðåéñ`, 1, 2) ), df_tmp[, 1], df_tmp[, 3], df_tmp[, 2])
colnames(df3) = c("ðåéñ", "ðàñïèñàíèå", "îæèäàåìîå âðåìÿ", "ñòàòóñ", "Àâèàêîìïàíèÿ", "Íîìåð ðåéñà", "Íàïðàâëåíèå", "Ñàìîë¸ò")
df = df3[(df3$`ðàñïèñàíèå` >= as.POSIXct(from2, tz = "GMT")) & (df3$`ðàñïèñàíèå` <= as.POSIXct(to2, tz = "GMT")),]
df = df[order(df$ðàñïèñàíèå),]
df = df[!duplicated(df[, c(2, 7, 8)]), ]
df$`Íàïðàâëåíèå` = as.character(df$`Íàïðàâëåíèå`)
df$`Àâèàêîìïàíèÿ` = as.character(df$`Àâèàêîìïàíèÿ`)
df$`Ñàìîë¸ò` = as.character(df$`Ñàìîë¸ò`)
df$`Ñàìîë¸ò` = gsub("A-", "Airbus A", df$`Ñàìîë¸ò`)
df$`Ñàìîë¸ò` = gsub("EMB-", "Embraer ", df$`Ñàìîë¸ò`)
df$`Ñàìîë¸ò` = gsub("B-", "Boeing ", df$`Ñàìîë¸ò`)
df$`Ñàìîë¸ò` = gsub("CRJ-", "Bombardier CRJ", df$`Ñàìîë¸ò`)
df$`Ñàìîë¸ò` = gsub("RRJ-95LR", "Ñóõîé Ñóïåðäæåò 100", df$`Ñàìîë¸ò`)
df$`Ñàìîë¸ò` = gsub("RRJ-95B", "Ñóõîé Ñóïåðäæåò 100", df$`Ñàìîë¸ò`)
# IATA codes http://www.iata.org/publications/Pages/code-search.aspx
df$`Àâèàêîìïàíèÿ` = gsub("SU", "Àýðîôëîò", df$`Àâèàêîìïàíèÿ`)
df$`Àâèàêîìïàíèÿ` = gsub("A4", "Àçèìóò", df$`Àâèàêîìïàíèÿ`)
df$`Àâèàêîìïàíèÿ` = gsub("FV", "Ðîññèÿ", df$`Àâèàêîìïàíèÿ`)
df$`Àâèàêîìïàíèÿ` = gsub("DP", "Ïîáåäà", df$`Àâèàêîìïàíèÿ`)
df$`Àâèàêîìïàíèÿ` = gsub("UT", "UTair", df$`Àâèàêîìïàíèÿ`)
df$`Àâèàêîìïàíèÿ` = gsub("U6", "Óð.Àâèà", df$`Àâèàêîìïàíèÿ`)
df$`Àâèàêîìïàíèÿ` = gsub("YC", "ßìàë", df$`Àâèàêîìïàíèÿ`)
df$`Àâèàêîìïàíèÿ` = gsub("4G", "Ãàçïðîì", df$`Àâèàêîìïàíèÿ`)
df$`Àâèàêîìïàíèÿ` = gsub("7J", "Òàäæèê", df$`Àâèàêîìïàíèÿ`)
df$`Àâèàêîìïàíèÿ` = gsub("7R", "RusLine", df$`Àâèàêîìïàíèÿ`)
df$`Àâèàêîìïàíèÿ` = gsub("8Q", "OnurAir", df$`Àâèàêîìïàíèÿ`)
df$`Àâèàêîìïàíèÿ` = gsub("9U", "Ìîëäàâèÿ", df$`Àâèàêîìïàíèÿ`)
df$`Àâèàêîìïàíèÿ` = gsub("AY", "FinnAir", df$`Àâèàêîìïàíèÿ`)
df$`Àâèàêîìïàíèÿ` = gsub("EL", "EllinAir", df$`Àâèàêîìïàíèÿ`)
df$`Àâèàêîìïàíèÿ` = gsub("FZ", "FlyDubai", df$`Àâèàêîìïàíèÿ`)
df$`Àâèàêîìïàíèÿ` = gsub("HY", "UzberAir", df$`Àâèàêîìïàíèÿ`)
df$`Àâèàêîìïàíèÿ` = gsub("KC", "Astana", df$`Àâèàêîìïàíèÿ`)
df$`Àâèàêîìïàíèÿ` = gsub("KK", "AtlasGlobal", df$`Àâèàêîìïàíèÿ`)
df$`Àâèàêîìïàíèÿ` = gsub("N4", "NordWind", df$`Àâèàêîìïàíèÿ`)
df$`Àâèàêîìïàíèÿ` = gsub("OK", "CzechAir", df$`Àâèàêîìïàíèÿ`)
df$`Àâèàêîìïàíèÿ` = gsub("R3", "ßêóòèÿ", df$`Àâèàêîìïàíèÿ`)
df$`Àâèàêîìïàíèÿ` = gsub("WZ", "RedWings", df$`Àâèàêîìïàíèÿ`)
df$`Àâèàêîìïàíèÿ` = gsub("XC", "Corendon", df$`Àâèàêîìïàíèÿ`)
df$`Àâèàêîìïàíèÿ` = gsub("YK", "AviaTraffic", df$`Àâèàêîìïàíèÿ`)
df$`Àâèàêîìïàíèÿ` = gsub("ZF", "Azur", df$`Àâèàêîìïàíèÿ`)
if (Geo) {
# Íàïðàâëåíèÿ ðàçë¸òà
nrow <- nrow(df)
counter <- 1
df$lon[counter] <- 0
df$lat[counter] <- 0
while (counter <= nrow) {
CityName <- gsub(' ', '%20', df$`Íàïðàâëåíèå`[counter]) #remove space for URLs
CountryCode <- ""
url <- paste(
"http://nominatim.openstreetmap.org/search?city="
, CityName
# , "&countrycodes="
# , CountryCode
, "&limit=9&format=json"
, sep = "")
x <- fromJSON(url)
if (is.vector(x)) {
df$lon[counter] <- x[[1]]$lon
df$lat[counter] <- x[[1]]$lat
}
counter <- counter + 1
}
df3 = as.data.frame(table(df$`Íàïðàâëåíèå`))
for (i in c(1:nrow(df3))) {
df[df$`Íàïðàâëåíèå` == df3[i, 1], 11] = df3[i, 2]
}
df$lat = as.numeric(as.character(df$lat))
df$lon = as.numeric(as.character(df$lon))
}
return(df)
}
year = "2018"
FromDay = "2018-09-17 00:00:00"
ToDay = "2018-09-23 23:59:59"
df_Platov = AR_schedule_parser(u_Platov, F, FromDay, ToDay)
df_Samara = AR_schedule_parser(u_Samara, F, FromDay, ToDay)
df_Ekb = AR_schedule_parser(u_Ekb, F, FromDay, ToDay)
df_NiNo = AR_schedule_parser(u_NiNo, F, FromDay, ToDay)
#write.csv2(df_Platov, file.path(dataDir, paste("TimeTable_Platov_", as.Date(Sys.Date()), " site", ".csv", sep = "")))
#write.csv2(df_Ekb, file.path(dataDir, paste("TimeTable_Ekb_", as.Date(Sys.Date()), " site", ".csv", sep = "")))
#write.csv2(df_Samara, file.path(dataDir, paste("TimeTable_Samara_", as.Date(Sys.Date()), " site", ".csv", sep = "")))
#write.csv2(df_NiNo, file.path(dataDir, paste("TimeTable_NiNo_", as.Date(Sys.Date()), " site", ".csv", sep = "")))
# Parsing Yandex -----
"9600213" # Sheremetievo
"9866615" # Platov
"9600365" # Borispol
"9600396" # Simpferopol
station = "9600396"
airport = "Ñèìôåðîïîëü"
airport_en = "Simpheropol"
station = "9866615"
airport = "Ïëàòîâ"
airport_en = "Platov"
#Sys.getlocale()
#LANG = "ru_RU.65001"
#LANG <- Sys.getenv("LANG")
#Sys.setlocale("LC_ALL", "Russian_Russia.65001")
#Sys.setlocale("LC_ALL", "Russian_Russia.20866")
#Sys.setlocale("LC_ALL", "Russian_Russia.1251")
# u = "http://en.wikipedia.org/wiki/World_population"
#u = "https://rasp.yandex.ru/station/9866615?start=2018-05-05T00%3A00%3A00&span=24"
#u = "https://raspisanie.msk.ru/plane/s9866615"
#u = "https://ru.wikipedia.org/wiki/Ñïèñîê_íàèáîëåå_çàãðóæåííûõ_àýðîïîðòîâ_Ðîññèè"
#u <- getURL(u)
# Yandex Rasp
sDate = Sys.Date() + 1
#u = paste( "https://rasp.yandex.ru/station/9866615?start=", Sys.Date()+1, "T00%3A00%3A00&span=24", sep = "")
# Tables
#i = 13
#u = paste("https://rasp.yandex.ru/station/", station, "?start=", Sys.Date() + 1 + i, "T00%3A00%3A00&span=24", sep = "")
#sDate = Sys.Date() + 1 + i
OneDay_TimeTable = function(u, sDate)
{
tables = read_html(u, encoding = "UTF-8")
dff = html_nodes(tables, "table")
df = html_table( dff[9], fill = T)[[1]]
df = df[-c(1:6), c(2:5)]
colnames( df ) = df[1,]
df = df[-c(1), ]
library(stringr)
df$`Àâèàêîìïàíèÿ` = str_split_fixed( df$`ðåéñ`, ",", 2)[,2]
df$`ðåéñ` = str_split_fixed(df$`ðåéñ`, ",", 2)[, 1]
df$`Íîìåð ðåéñà` = apply(str_split_fixed(df$`ðåéñ`, " ", 3)[, 1:2], MARGIN = 1, FUN = paste, collapse = " ")
#df$`ðåéñ` = str_split_fixed(df$`ðåéñ`, " ", 3)[, 3]
#df$`ðåéñ` = str_split_fixed(df$`ðåéñ`, " ", 2)[, 3]
#df$`ðåéñ` = str_split_fixed(df$`ðåéñ`, " ", 2)[,2]
df_div3 = html_nodes(tables, xpath = '//*[@class="b-timetable__tripname"]')
#str_split_fixed(html_text(html_nodes(df_div3, "a")), " ", 3)[1, 1]
df$`Íàïðàâëåíèå` = str_split_fixed( html_text(html_nodes(df_div3, "a")), " ", 3)[, 2]
df_div4 = html_nodes(tables, xpath = '//*[@class="b-timetable__description"]')
df$`Ñàìîë¸ò` = str_split_fixed( html_text( df_div4 ), ", ", 2)[, 1]
#df = df[ , c(7,5,2,6, 8)]
df$`ðàñïèñàíèå`[1] = strsplit(df$`ðàñïèñàíèå`[1], ", ")[[1]][1]
df$`ðàñïèñàíèå` = as.POSIXlt(paste( sDate, df$`ðàñïèñàíèå`))
return(df)
}
OneWeek_TimeTable = function(station)
{
df = NULL
for(i in c(1:7))
{
cat(".",i,".")
df_tmp = OneDay_TimeTable(
paste("https://rasp.yandex.ru/station/",station,"?start=", Sys.Date() + 1 + i, "T00%3A00%3A00&span=24", sep = ""),
Sys.Date() + 1 + i)
df = rbind(df, df_tmp)
}
A320_1 = "Airbus A320"
A320_2 = "Airbus À320"
df$`Ñàìîë¸ò`[df$`Ñàìîë¸ò` == A320_2] = A320_1
A321_1 = "Airbus À321"
A321_2 = "Airbus A321"
df$`Ñàìîë¸ò`[df$`Ñàìîë¸ò` == A321_2] = A321_1
return(df)
}
df = OneWeek_TimeTable(station)
# Íàïðàâëåíèÿ ðàçë¸òà
nrow <- nrow(df)
counter <- 1
df$lon[counter] <- 0
df$lat[counter] <- 0
while (counter <= nrow) {
CityName <- gsub(' ', '%20', df$`Íàïðàâëåíèå`[counter]) #remove space for URLs
CountryCode <- ""
url <- paste(
"http://nominatim.openstreetmap.org/search?city="
, CityName
# , "&countrycodes="
# , CountryCode
, "&limit=9&format=json"
, sep = "")
x <- fromJSON(url)
if (is.vector(x)) {
df$lon[counter] <- x[[1]]$lon
df$lat[counter] <- x[[1]]$lat
}
counter <- counter + 1
}
df3 = as.data.frame(table(df$`Íàïðàâëåíèå`))
for (i in c(1:nrow(df3))) {
df[df$`Íàïðàâëåíèå` == df3[i, 1], 11] = df3[i, 2]
}
df$lat = as.numeric(as.character(df$lat))
df$lon = as.numeric(as.character(df$lon))
df$`ðàñïèñàíèå` = as.POSIXct(df$`ðàñïèñàíèå`)
df$`Íàïðàâëåíèå` = as.character(df$`Íàïðàâëåíèå`)
colnames(df)[11] = "×àñòîòà"
write.csv2(df, file.path(dataDir, paste("TimeTable_", airport_en, "_", as.Date(Sys.Date()), ".csv", sep = "")))
#df = read.csv2( file.path(dataDir, "TimeTable_2018-05-25.csv"))[,c(2:12)]
df_Platov = df
# Analysis -----
Freq_plot = function(dff, p_title) {
return(ggplot(data = dff) +
geom_bar(stat = "identity", aes(reorder(Var1, Freq), Freq), fill = "cyan4") +
geom_text(aes(reorder(Var1, Freq), label = Freq, y = Freq), size = 3, hjust = -0.1, colour = "dimgray", vjust = 0.25) +
theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
xlab("") + ylab("") + coord_flip() +
scale_y_continuous(breaks = round(seq(0, max(dff$Freq), max(dff$Freq) / 25))) +
theme(plot.margin = unit(c(0, 0.2, 0, 0), "cm")) +
ggtitle(p_title)
)
}
Frequncies_Routes_Capacities = function(df, airport, airport_en, PlotsOutput) {
########################
# Frequncies plots
df_cities = as.data.frame(sort(table(df$`Íàïðàâëåíèå`), decreasing = T))
df_airlines = as.data.frame(sort(table(df$`Àâèàêîìïàíèÿ`), decreasing = T))
df_jets = as.data.frame(sort(table(df$`Ñàìîë¸ò`), decreasing = T))
p1 = Freq_plot(df_cities, paste("Ðåéñîâ èç àýðîïîðòà", airport, "\nïî íàïðàâëåíèÿì (â íåäåëþ)"))
p1
p2 = Freq_plot(df_airlines, paste("Êîëè÷åñòâî ðåéñîâ èç àýðîïîðòà ", airport, "\nïî àâèàêîìïàíèÿì (â íåäåëþ)"))
p2
p3 = Freq_plot(df_jets, paste("Êîëè÷åñòâî ðåéñîâ èç àýðîïîðòà ", airport, "\nïî òèïàì ñàìîë¸òîâ (â íåäåëþ)"))
p3
if (PlotsOutput) {
#pdf(file = file.path(paste(plotDir, "/City_vs_Freq ", Sys.Date(), " ", airport, ".pdf", sep = "")), width = 12, height = 12, pointsize = 10)
png(filename = file.path(paste(plotDir, "/City_vs_Freq ", Sys.Date(), " ", airport_en, ".png", sep = "")), width = 800, height = 800, units = "px", pointsize = 12, bg = "white", res = NA, family = "Times", restoreConsole = TRUE, type = c("cairo-png"))
p1 + annotate(geom = "text", x = 15, y = 80.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 10, alpha = 0.5)
dev.off()
png(filename = file.path(plotDir, paste("Airline_vs_Freq ", Sys.Date(), " ", airport_en, ".png", sep = "")), width = 800, height = 800, units = "px", pointsize = 12, bg = "white", res = NA, family = "", restoreConsole = TRUE, type = c("cairo-png"))
p2 + annotate(geom = "text", x = 7, y = 25.0, xend = Inf, yend = Inf, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 10, alpha = 0.5, family = 'Arial')
dev.off()
png(filename = file.path(plotDir, paste("Jet_vs_Freq ", Sys.Date(), " ", airport_en, ".png", sep = "")), width = 800, height = 800, units = "px", pointsize = 12, bg = "white", res = NA, family = "", restoreConsole = TRUE, type = c("cairo-png"))
p3 + annotate(geom = "text", x = 7, y = 35, xend = Inf, yend = Inf, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 7, alpha = 0.5, family = 'Arial')
dev.off()
}
########################
# Frequency by Day plot
wdays = c( "Ïí", "Âò", "Ñð", "×ò", "Ïò", "Ñá", "Âñ")
#weekdays(df$`ðàñïèñàíèå` )
tab2 = apply(table( as.integer(format(df$`ðàñïèñàíèå`, format = "%w")), df$`Íàïðàâëåíèå`), FUN = sum, MARGIN = 1)
df_wd_fly = data.frame(Var1 = as.character(names(tab2)), Freq = tab2 )
df_wd_fly$Var1 = as.numeric( df_wd_fly$Var1 ) - 1
df_wd_fly[ df_wd_fly$Var1 == 0, 1] = 7
dff = df_wd_fly
p4 = ggplot(data = dff) +
geom_bar(stat = "identity", aes(Var1, Freq), fill = "cyan4") +
geom_text(aes(Var1, Freq, label = Freq, y = Freq), size = 3, colour = "dimgray", vjust = -0.3) +
# theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
xlab("") + ylab("") + # coord_flip() +
scale_x_continuous(breaks = 1:7, labels = wdays) +
theme(plot.margin = unit(c(0, 0.2, 0, 0), "cm")) +
ggtitle( paste("Êîëè÷åñòâî ðåéñîâ èç àýðîïîðòà", airport, "\nïî äíÿì íåäåëè")) +
annotate(geom = "text", x = 4, y = 17, xend = Inf, yend = Inf, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 9, alpha = 0.5, family = 'Arial')
p4
tab2 = apply(table(as.integer(format(df$`ðàñïèñàíèå`, format = "%H")), df$`Íàïðàâëåíèå`), FUN = sum, MARGIN = 1)
df_h_fly = data.frame(Var1 = as.character(names(tab2)), Freq = tab2)
df_h_fly$Var1 = as.numeric(df_h_fly$Var1)
#df_h_fly[df_h_fly$Var1 == 0, 1] = 7
dff = df_h_fly
p5 = ggplot(data = dff) +
geom_bar(stat = "identity", aes(Var1, Freq), fill = "cyan4") +
geom_text(aes(Var1, Freq, label = Freq, y = Freq), size = 3, colour = "dimgray", vjust = -0.3) +
# theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
xlab("") + ylab("") + # coord_flip() +
scale_x_continuous(breaks = df_h_fly$Var1, labels = df_h_fly$Var1) +
theme(plot.margin = unit(c(0, 0.2, 0, 0), "cm")) +
ggtitle(paste("Êîëè÷åñòâî ðåéñîâ èç àýðîïîðòà", airport, "\nïî âðåìåíè äíÿ çà íåäåëþ")) +
annotate(geom = "text", x = 11, y = 13, xend = Inf, yend = Inf, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 7, alpha = 0.5, family = 'Arial')
p5
if (PlotsOutput) {
png(filename = file.path(plotDir, paste("Freq_per_day ", Sys.Date(), " ", airport_en, ".png", sep = "")), width = 800, height = 400, units = "px", pointsize = 12, bg = "white", res = NA, family = "", restoreConsole = TRUE, type = c("cairo-png"))
p4
dev.off()
png(filename = file.path(plotDir, paste("Freq_per_hour ", Sys.Date(), " ", airport_en, ".png", sep = "")), width = 800, height = 800, units = "px", pointsize = 12, bg = "white", res = NA, family = "", restoreConsole = TRUE, type = c("cairo-png"))
p5
dev.off()
}
###########
# Capacity
# http://www.wsdot.wa.gov/Aviation/planning/EconomicCalc/Documents/AirplaneCapacityTable
df_capacity = data.frame(
type = c(
"Airbus A319", "Airbus A320", "Airbus À321", "Airbus A321", "Airbus A321 SH", "Airbus A330-200", "Airbus A330-300", "Airbus À330-200", "Airbus À330-300",
"Boeing 737-100", "Boeing 737-200", "Boeing 737-300", "Boeing 737-400", "Boeing 737-500", "Boeing 737-600", "Boeing 737-700", "Boeing 737-800", "Boeing 737-800W", "Boeing 737-900", "Boeing 737-900ER",
"Boeing 757-200", "Boeing 757-300",
"Boeing 767-200", "Boeing 767-200ER", "Boeing 767-300", "Boeing 767-300ER", "Boeing 767-400ER",
"Boeing 777-200", "Boeing 777-200ER", "Boeing 777-200LR", "Boeing 777-300", "Boeing 777-300ER", "Boeing 777-8X", "Boeing 777-9X", "Boeing 747-400",
"Canadair regional jet", "Bombardier CRJ200",
"Embraer 170", "Embraer 175", "Embraer EMB 175", "Embraer 190", "Embraer 195",
"AT-72-5",
"Ñóõîé Ñóïåðäæåò 100", "ÒÓ-204", "ßÊ-42", "ÀÍ-24"),
capacity = c(
134, 164, 199, 199, 199, 293, 335, 293, 335,
103, 133, 149, 168, 132, 130, 148, 189, 189, 189, 215,
214, 260,
214, 214, 261, 261, 296,
300, 300, 300, 365, 365, 365, 415, 416,
76, 50,
76, 84, 106, 106, 116,
74,
95, 210, 120, 50))
df_capacity$type = as.character(df_capacity$type)
df_jets$Var1 = as.character(df_jets$Var1)
cap = NULL
for (i in c(1:dim(df_jets)[1])) {
if (df_jets[i, 1] %in% df_capacity[, 1]) {
cap = c(cap, df_capacity[df_capacity[, 1] == df_jets[i, 1], 2])
} else cap = c(cap, 0)
}
df_jets$`Âìåñòèìîñòü` = cap
df_jets$`¨ìêîñòü` = df_jets$Freq * df_jets$`Âìåñòèìîñòü`
df_tmp = df_jets[, c(1, 4)]
colnames(df_tmp) = c("Var1", "Freq")
p6 = Freq_plot(df_tmp, paste("¨ìêîñòü ðåéñîâ èç àýðîïîðòà", airport, "\nïî òèïàì ñàìîë¸òîâ (â íåäåëþ)")) + annotate(geom = "text", x = 5, y = 5000, xend = Inf, yend = Inf, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 10, alpha = 0.5, family = 'Arial') + ylab(paste("Îáùàÿ ¸ìêîñòü ïî òèïàì (â îäíîì íàïðàâëåíèè â ìåñÿö):", sum(df_jets$`¨ìêîñòü`) * 4))
p6
# Ïàññàæèðîïîòîê
sum(df_jets$`¨ìêîñòü`) * 8 * 0.7
# ¨ìêîñòü ïî íàïðàâëåíèìÿì
df$`Ñàìîë¸ò` = as.character(df$`Ñàìîë¸ò`)
df$`Êðåñëà` = rep(0, dim(df)[1])
for (i in c(1:dim(df_capacity)[1])) {
df$`Êðåñëà`[df$`Ñàìîë¸ò` == df_capacity$type[i]] = df_capacity$capacity[i]
}
tab3 = table(df$`Íàïðàâëåíèå`, df$`Êðåñëà`)
for (i in c(1:dim(tab3)[1])) {
tab3[i,] = tab3[i,] * as.integer(colnames(tab3))
}
df_city_capacity = as.data.frame(sort(apply(tab3, MARGIN = 1, sum), decreasing = T))
df_city_capacity = cbind(rownames(df_city_capacity), df_city_capacity)
df_city_capacity[, 1] = as.character(df_city_capacity[, 1])
colnames(df_city_capacity) = c("Var1", "Freq")
sum(df_city_capacity$Freq)
p7 = Freq_plot(df_city_capacity, paste("¨ìêîñòü èç àýðîïîðòà", airport, "\nïî íàïðàâëåíèÿì (â íåäåëþ)")) +
annotate(geom = "text", x = 15, y = 9000, xend = Inf, yend = Inf, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 10, alpha = 0.5, family = 'Arial') + ylab(paste("Îáùàÿ ¸ìêîñòü ïî òèïàì (â îäíîì íàïðàâëåíèè â ìåñÿö):", sum(df_jets$`¨ìêîñòü`) * 4))
p7
# Ïî ÀÊ
#for (i in c(1:dim(df_jets)[1])) {
# df[df$`Ñàìîë¸ò` == df_capacity$type[i], 12] = df_capacity$capacity[i]
#}
tab3 = table(df$`Àâèàêîìïàíèÿ`, df$`Êðåñëà`)
for (i in c(1:dim(tab3)[1])) {
tab3[i,] = tab3[i,] * as.integer(colnames(tab3))
}
df_airline_capacity = as.data.frame(sort(apply(tab3, MARGIN = 1, sum), decreasing = T))
df_airline_capacity = cbind(rownames(df_airline_capacity), df_airline_capacity)
df_airline_capacity[, 1] = as.character(df_airline_capacity[, 1])
colnames(df_airline_capacity) = c("Var1", "Freq")
sum(df_airline_capacity$Freq)
p8 = Freq_plot(df_airline_capacity, paste("¨ìêîñòü èç àýðîïîðòà", airport, "\nïî àâèàêîìïàíèÿì (â íåäåëþ)")) +
annotate(geom = "text", x = 9, y = 3000, xend = Inf, yend = Inf, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 10, alpha = 0.5, family = 'Arial') + ylab(paste("Îáùàÿ ¸ìêîñòü ïî òèïàì (â îäíîì íàïðàâëåíèè â ìåñÿö):", sum(df_jets$`¨ìêîñòü`) * 4))
p8
if (PlotsOutput) {
png(filename = file.path(plotDir, paste("Jet_vs_Capacity ", Sys.Date(), " ", airport_en, ".png", sep = "")), width = 800, height = 800, units = "px", pointsize = 12, bg = "white", res = NA, family = "", restoreConsole = TRUE, type = c("cairo-png"))
p6
dev.off()
png(filename = file.path(plotDir, paste("City_vs_Capacity ", Sys.Date(), " ", airport_en, ".png", sep = "")), width = 800, height = 800, units = "px", pointsize = 12, bg = "white", res = NA, family = "", restoreConsole = TRUE, type = c("cairo-png"))
p7
dev.off()
png(filename = file.path(plotDir, paste("Airline_vs_Capacity ", Sys.Date(), " ", airport_en, ".png", sep = "")), width = 800, height = 800, units = "px", pointsize = 12, bg = "white", res = NA, family = "", restoreConsole = TRUE, type = c("cairo-png"))
p8
dev.off()
}
return(list(
data.frame(City = df_cities[, 1], Freq = df_cities[, 2], Capacity = df_city_capacity[, 2]),
data.frame(City = df_airlines[order(as.character(df_airlines$Var1)), 1], Freq = df_airlines[order(as.character(df_airlines$Var1)), 2], Capacity = df_airline_capacity[order(df_airline_capacity$Var1), 2]),
df_jets,
df_wd_fly, df_h_fly,
p1, p2, p3, p4, p5, p6, p7, p8))
}
Analysis_Rostov = Frequncies_Routes_Capacities( df_Platov, "Ðîñòîâ", "Platov", T )
Analysis_Ekb = Frequncies_Routes_Capacities( df_Ekb, "Åêá", "Ekb", F )
Analysis_Samara = Frequncies_Routes_Capacities( df_Samara, "Ñàìàðà", "Samara", F )
Analysis_NiNo = Frequncies_Routes_Capacities( df_NiNo, "ÍèÍî", "NiNo", F )
#Analysis_Sim = Frequncies_Routes_Capacities(df_Sim, "Ñèìô", "Simf", F)
# AR group comparison plots ----
# Routes number
df_RoutesN = data.frame(
Var1 = c("Åêá", "Ðîñòîâ", "Ñàìàðà", "ÍèÍî"),
Freq = c( dim(Analysis_Ekb[[1]])[1],
dim(Analysis_Rostov[[1]])[1],
dim(Analysis_Samara[[1]])[1],
dim(Analysis_NiNo[[1]])[1]))
p1 = Freq_plot( df_RoutesN, "×èñëî íàïðàâëåíèé ïî ãîðîäàì")
# Airlines number
df_AirlinesN = data.frame(
Var1 = c("Åêá", "Ðîñòîâ", "Ñàìàðà", "ÍèÍî"),
Freq = c(dim(Analysis_Ekb[[2]])[1],
dim(Analysis_Rostov[[2]])[1],
dim(Analysis_Samara[[2]])[1],
dim(Analysis_NiNo[[2]])[1]))
p2 = Freq_plot(df_AirlinesN, "×èñëî ÀÊ ïî ãîðîäàì")
# Jets number
df_JetsN = data.frame(
Var1 = c("Åêá", "Ðîñòîâ", "Ñàìàðà", "ÍèÍî"),
Freq = c(dim(Analysis_Ekb[[3]])[1],
dim(Analysis_Rostov[[3]])[1],
dim(Analysis_Samara[[3]])[1],
dim(Analysis_NiNo[[3]])[1]))
p3 = Freq_plot(df_JetsN, "×èñëî òèïîâ ïî ãîðîäàì")
grid.arrange(p1, p2, p3, ncol = 3)
# Main jet type
df_JetMain = data.frame(
Var1 = c("Åêá", "Ðîñòîâ", "Ñàìàðà", "ÍèÍî"),
Freq = c( Analysis_Ekb[[3]][1,1],
Analysis_Rostov[[3]][1, 1],
Analysis_Samara[[3]][1, 1],
Analysis_NiNo[[3]][1, 1]))
library(stringr)
df_AB_competition = rbind(
data.frame(
City = "Åêá",
Airbus = sum(str_count(df_Ekb$`Ñàìîë¸ò`, pattern = "Airbus")) / dim(df_Ekb)[1] * 100,
Boeing = sum(str_count(df_Ekb$`Ñàìîë¸ò`, pattern = "Boeing")) / dim(df_Ekb)[1] * 100,
Bombardier = sum(str_count(df_Ekb$`Ñàìîë¸ò`, pattern = "Bombardier")) / dim(df_Ekb)[1] * 100,
Embraer = sum(str_count(df_Ekb$`Ñàìîë¸ò`, pattern = "Embraer")) / dim(df_Ekb)[1] * 100,
Ñóõîé = sum(str_count(df_Ekb$`Ñàìîë¸ò`, pattern = "Ñóõîé")) / dim(df_Ekb)[1] * 100,
ATR = sum(str_count(df_Ekb$`Ñàìîë¸ò`, pattern = "AT")) / dim(df_Ekb)[1] * 100),
data.frame(
City = "Ðîñòîâ",
Airbus = sum(str_count(df_Platov$`Ñàìîë¸ò`, pattern = "Airbus")) / dim(df_Platov)[1] * 100,
Boeing = sum(str_count(df_Platov$`Ñàìîë¸ò`, pattern = "Boeing")) / dim(df_Platov)[1] * 100,
Bombardier = sum(str_count(df_Platov$`Ñàìîë¸ò`, pattern = "Bombardier")) / dim(df_Platov)[1] * 100,
Embraer = sum(str_count(df_Platov$`Ñàìîë¸ò`, pattern = "Embraer")) / dim(df_Platov)[1] * 100,
Ñóõîé = sum(str_count(df_Platov$`Ñàìîë¸ò`, pattern = "Ñóõîé")) / dim(df_Platov)[1] * 100,
ATR = sum(str_count(df_Platov$`Ñàìîë¸ò`, pattern = "AT")) / dim(df_Platov)[1] * 100),
data.frame(
City = "Ñàìàðà",
Airbus = sum(str_count(df_Samara$`Ñàìîë¸ò`, pattern = "Airbus")) / dim(df_Samara)[1] * 100,
Boeing = sum(str_count(df_Samara$`Ñàìîë¸ò`, pattern = "Boeing")) / dim(df_Samara)[1] * 100,
Bombardier = sum(str_count(df_Samara$`Ñàìîë¸ò`, pattern = "Bombardier")) / dim(df_Samara)[1] * 100,
Embraer = sum(str_count(df_Samara$`Ñàìîë¸ò`, pattern = "Embraer")) / dim(df_Samara)[1] * 100,
Ñóõîé = sum(str_count(df_Samara$`Ñàìîë¸ò`, pattern = "Ñóõîé")) / dim(df_Samara)[1] * 100,
ATR = sum(str_count(df_Samara$`Ñàìîë¸ò`, pattern = "AT")) / dim(df_Samara)[1] * 100),
data.frame(
City = "ÍèÍî",
Airbus = sum(str_count(df_NiNo$`Ñàìîë¸ò`, pattern = "Airbus")) / dim(df_NiNo)[1] * 100,
Boeing = sum(str_count(df_NiNo$`Ñàìîë¸ò`, pattern = "Boeing")) / dim(df_NiNo)[1] * 100,
Bombardier = sum(str_count(df_NiNo$`Ñàìîë¸ò`, pattern = "Bombardier")) / dim(df_NiNo)[1] * 100,
Embraer = sum(str_count(df_NiNo$`Ñàìîë¸ò`, pattern = "Embraer")) / dim(df_NiNo)[1] * 100,
Ñóõîé = sum(str_count(df_NiNo$`Ñàìîë¸ò`, pattern = "Ñóõîé")) / dim(df_NiNo)[1] * 100,
ATR = sum(str_count(df_NiNo$`Ñàìîë¸ò`, pattern = "AT")) / dim(df_NiNo)[1] * 100))
# melt the data frame for plotting
library(reshape2)
data.m <- melt(df_AB_competition, id.varÑóõîé = 'City')
colnames( data.m ) = c("Ãîðîä","Òèï","Äîëÿ")
# plot everything
p4 = ggplot(data.m, aes(Ãîðîä, Äîëÿ)) +
geom_bar(aes(fill = Òèï), stat = "identity", position = "dodge") + xlab("") + ylab("Äîëÿ") +
geom_text(aes(fill = Òèï, label = round(Äîëÿ), y = round(Äîëÿ)), size = 3, hjust = 0.3, colour = "dimgray", vjust = -0.3,
position = position_dodge(width = 0.9)) +
theme(plot.margin = unit(c(0, 0.2, 0, 0), "cm"))# + ggtitle("Äîëè ïî òèïàì")
p4
grid.arrange(Analysis_Ekb[[9]], Analysis_Rostov[[9]], Analysis_Samara[[9]], Analysis_NiNo[[9]], ncol = 2)
grid.arrange(Analysis_Ekb[[10]], Analysis_Rostov[[10]], Analysis_Samara[[10]], Analysis_NiNo[[10]], ncol = 2)
grid.arrange(Analysis_Ekb[[6]], Analysis_Rostov[[6]], Analysis_Samara[[6]], Analysis_NiNo[[6]], ncol = 2)
grid.arrange(Analysis_Ekb[[7]], Analysis_Rostov[[7]], Analysis_Samara[[7]], Analysis_NiNo[[7]], ncol = 2)
grid.arrange(Analysis_Ekb[[8]], Analysis_Rostov[[8]], Analysis_Samara[[8]], Analysis_NiNo[[8]], ncol = 2)
grid.arrange(Analysis_Ekb[[11]], Analysis_Rostov[[11]], Analysis_Samara[[11]], Analysis_NiNo[[13]], ncol = 2)
grid.arrange(Analysis_Ekb[[12]], Analysis_Rostov[[12]], Analysis_Samara[[12]], Analysis_NiNo[[13]], ncol = 2)
grid.arrange(Analysis_Ekb[[13]], Analysis_Rostov[[13]], Analysis_Samara[[13]], Analysis_NiNo[[13]], ncol = 2)
if (PlotsOutput) {
library(gridExtra)
# General frequencies
png(filename = file.path(plotDir, paste("AR frequencies ", Sys.Date(), ".png", sep = "")), width = 1280, height = 300, units = "px", pointsize = 12, bg = "white", res = NA, family = "", restoreConsole = TRUE, type = c("cairo-png"))
grid.arrange(
p1 + annotate(geom = "text", x = 3, y = 35.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 13, alpha = 0.5),
p2 + annotate(geom = "text", x = 3, y = 15.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 13, alpha = 0.5),
p3 + annotate(geom = "text", x = 3, y = 9.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 13, alpha = 0.5),
ncol = 3)
dev.off()
# Types of jets shares
png(filename = file.path(plotDir, paste("AR jets ", Sys.Date(), ".png", sep = "")), width = 640, height = 300, units = "px", pointsize = 12, bg = "white", res = NA, family = "", restoreConsole = TRUE, type = c("cairo-png"))
p4 + annotate(geom = "text", x = 2.5, y = 25.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 13, alpha = 0.5)
dev.off()
# Frequencies by day and hour
png(filename = file.path(plotDir, paste("AR days freqs ", Sys.Date(), ".png", sep = "")), width = 800, height = 800, units = "px", pointsize = 12, bg = "white", res = 60, family = "", restoreConsole = TRUE, type = c("windows"))
grid.arrange(
Analysis_Ekb[[9]] + annotate(geom = "text", x = 3.5, y = 25.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
Analysis_NiNo[[9]] + annotate(geom = "text", x = 3.5, y = 25.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
Analysis_Rostov[[9]] + annotate(geom = "text", x = 3.5, y = 25.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
Analysis_Samara[[9]] + annotate(geom = "text", x = 3.5, y = 25.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
ncol = 2)
dev.off()
png(filename = file.path(plotDir, paste("AR hours freqs ", Sys.Date(), ".png", sep = "")), width = 800, height = 800, units = "px", pointsize = 12, bg = "white", res = 60, family = "", restoreConsole = TRUE, type = c("windows"))
grid.arrange(
Analysis_Ekb[[10]] + annotate(geom = "text", x = 3.5, y = 25.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
Analysis_NiNo[[10]] + annotate(geom = "text", x = 3.5, y = 25.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
Analysis_Rostov[[10]] + annotate(geom = "text", x = 3.5, y = 25.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
Analysis_Samara[[10]] + annotate(geom = "text", x = 3.5, y = 25.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
ncol = 2)
dev.off()
# Cities, airlines, jets frequencies
png(filename = file.path(plotDir, paste("AR cities freqs ", Sys.Date(), ".png", sep = "")), width = 800, height = 800, units = "px", pointsize = 12, bg = "white", res = 60, family = "", restoreConsole = TRUE, type = c("windows"))#, compression = "lzw")
grid.arrange(
Analysis_Ekb[[6]] + annotate(geom = "text", x = 35, y = 25.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
Analysis_NiNo[[6]] + annotate(geom = "text", x = 10, y = 25.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
Analysis_Rostov[[6]] + annotate(geom = "text", x = 25, y = 25.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
Analysis_Samara[[6]] + annotate(geom = "text", x = 25, y = 25.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
ncol = 2)
dev.off()
png(filename = file.path(plotDir, paste("AR airlines freqs ", Sys.Date(), ".png", sep = "")), width = 1280, height = 1280, units = "px", pointsize = 12, bg = "white", res = 72, family = "", restoreConsole = TRUE, type = c("windows")) #, compression = "lzw")
grid.arrange(
Analysis_Ekb[[7]] + annotate(geom = "text", x = 15, y = 75.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
Analysis_NiNo[[7]] + annotate(geom = "text", x = 10, y = 25.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
Analysis_Rostov[[7]] + annotate(geom = "text", x = 15, y = 25.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
Analysis_Samara[[7]] + annotate(geom = "text", x = 15, y = 25.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
ncol = 2)
dev.off()
png(filename = file.path(plotDir, paste("AR jets freqs ", Sys.Date(), ".png", sep = "")), width = 800, height = 800, units = "px", pointsize = 12, bg = "white", res = 72, family = "", restoreConsole = TRUE, type = c("windows")) #, compression = "lzw")
grid.arrange(
Analysis_Ekb[[8]] + annotate(geom = "text", x = 10, y = 75.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
Analysis_NiNo[[8]] + annotate(geom = "text", x = 10, y = 15.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
Analysis_Rostov[[8]] + annotate(geom = "text", x = 5, y = 40.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
Analysis_Samara[[8]] + annotate(geom = "text", x = 10, y = 30.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
ncol = 2)
dev.off()
# Cities, airlines, jets frequencies
png(filename = file.path(plotDir, paste("AR jets capacities ", Sys.Date(), ".png", sep = "")), width = 800, height = 800, units = "px", pointsize = 12, bg = "white", res = 72, family = "", restoreConsole = TRUE, type = c("windows")) #, compression = "lzw")
grid.arrange(
Analysis_Ekb[[11]] + annotate(geom = "text", x = 15, y = 25.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
Analysis_NiNo[[11]] + annotate(geom = "text", x = 10, y = 25.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
Analysis_Rostov[[11]] + annotate(geom = "text", x = 5, y = 25.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
Analysis_Samara[[11]] + annotate(geom = "text", x = 15, y = 25.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
ncol = 2)
dev.off()
png(filename = file.path(plotDir, paste("AR cities capacities ", Sys.Date(), ".png", sep = "")), width = 800, height = 800, units = "px", pointsize = 12, bg = "white", res = 72, family = "", restoreConsole = TRUE, type = c("windows")) #, compression = "lzw")
grid.arrange(
Analysis_Ekb[[12]] + annotate(geom = "text", x = 15, y = 75.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
Analysis_NiNo[[12]] + annotate(geom = "text", x = 10, y = 15.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
Analysis_Rostov[[12]] + annotate(geom = "text", x = 15, y = 25.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
Analysis_Samara[[12]] + annotate(geom = "text", x = 15, y = 25.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
ncol = 2)
dev.off()
png(filename = file.path(plotDir, paste("AR airlines capacities ", Sys.Date(), ".png", sep = "")), width = 800, height = 800, units = "px", pointsize = 12, bg = "white", res = 72, family = "", restoreConsole = TRUE, type = c("windows")) #, compression = "lzw")
grid.arrange(
Analysis_Ekb[[13]] + annotate(geom = "text", x = 10, y = 75.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
Analysis_NiNo[[13]] + annotate(geom = "text", x = 10, y = 15.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
Analysis_Rostov[[13]] + annotate(geom = "text", x = 5, y = 40.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
Analysis_Samara[[13]] + annotate(geom = "text", x = 10, y = 30.0, label = 'Ñòåïàí Ñóøêî', color = 'white', angle = 45, fontface = 'bold', size = 22, alpha = 0.5),
ncol = 2)
dev.off()
}
# Mosaic plot ----
if (!require("vcd")) { install.packages("vcd"); require("vcd") }
tab = table(df$`Àâèàêîìïàíèÿ`, df$`Íàïðàâëåíèå`)
#mosaic(df$`Àâèàêîìïàíèÿ` ~ df$`Íàïðàâëåíèå`)
tab = tab[as.character(df_airlines$Var1), as.character(df_cities$Var1)]
#df_cross = as.data.frame.matrix(tab[1:5, 1:5])
#mosaic(tab, legend = T, zero_size = 0, zero_split = T)
#strucplot(tab[1:5, 1:5], legend = T, zero_size = 0, labeling = T)
#mosaic(~`Íàïðàâëåíèå` + `Àâèàêîìïàíèÿ`, data = df, zero_size = 0, zero_split = F, keep_aspect_ratio = F, ctx = 0.2)
#mosaic(~`Àâèàêîìïàíèÿ` + `Íàïðàâëåíèå`, data = df, zero_size = 0, legend = T)
#
mosaicplot(tab, las = 2, col = "cyan4", main = "")
mosaicplot(t(tab), las = 2, col = "cyan4", main = "")
if (PlotsOutput) {
png(filename = file.path(plotDir, paste("Mosaic_Airline_vs_City ", Sys.Date(), " ", airport_en, ".png", sep = "")), width = 800, height = 800, units = "px", pointsize = 12, bg = "white", res = NA, family = "", restoreConsole = TRUE, type = c("cairo-png"))
par(mar = rep(.5, 4))
mosaicplot(tab, las = 2, col = "cyan4", main = "", cex = 1.1)
text(x = grconvertX(0.5, from = "npc"), y = grconvertY(0.5, from = "npc"),
labels = "Ñòåïàí Ñóøêî", cex = 3, font = 2, col = adjustcolor("steelblue", alpha.f = 0.35), srt = 45)
dev.off()
png(filename = file.path(plotDir, paste("Mosaic_City_vs_Airline ", Sys.Date(), " ", airport_en, ".png", sep = "")), width = 800, height = 800, units = "px", pointsize = 12, bg = "white", res = NA, family = "", restoreConsole = TRUE, type = c("cairo-png"))
par(mar = rep(.5, 4))
mosaicplot(t(tab), las = 2, col = "cyan4", main = "", cex = 1.1)
text(x = grconvertX(0.5, from = "npc"), y = grconvertY(0.5, from = "npc"),
labels = "Ñòåïàí Ñóøêî", cex = 3, font = 2, col = adjustcolor("steelblue", alpha.f = 0.35), srt = 45)
dev.off()
}
# ÀÊ vs Ñàìîë¸ò
tab2 = table(df$`Àâèàêîìïàíèÿ`, df$`Ñàìîë¸ò`)
tab2 = tab2[as.character(df_airlines$Var1), as.character(df_jets$Var1)]
mosaicplot(tab2, las = 2, col = "cyan4", main = "")
mosaicplot(t(tab2), las = 2, col = "cyan4", main = "")
if (PlotsOutput) {
png(filename = file.path(plotDir, paste("Mosaic_Airline_vs_Jet ", Sys.Date(), " ", airport_en, ".png", sep = "")), width = 800, height = 800, units = "px", pointsize = 12, bg = "white", res = NA, family = "", restoreConsole = TRUE, type = c("cairo-png"))
par(mar = rep(.5, 4))
mosaicplot(tab2, las = 2, col = "cyan4", main = "", cex = 1.1)
text( x = grconvertX(0.5, from = "npc"), y = grconvertY(0.5, from = "npc"),
labels = "Ñòåïàí Ñóøêî", cex = 3, font = 2, col = adjustcolor("steelblue", alpha.f = 0.35), srt = 45)
dev.off()
png(filename = file.path(plotDir, paste("Mosaic_Jet_vs_Airline ", Sys.Date(), " ", airport_en, ".png", sep = "")), width = 800, height = 800, units = "px", pointsize = 12, bg = "white", res = NA, family = "", restoreConsole = TRUE, type = c("cairo-png"))
par(mar = rep(.5, 4))
mosaicplot( t(tab2), las = 2, col = "cyan4", main = "", cex = 1.1)
text(x = grconvertX(0.5, from = "npc"), # align to center of plot X axis
y = grconvertY(0.5, from = "npc"), # align to center of plot Y axis
labels = "Ñòåïàí Ñóøêî", # our watermark
cex = 3, font = 2, # large, bold font - hard to miss
col = adjustcolor("steelblue", alpha.f = 0.35), # translucent (0.2 = 20%) red color
srt = 45) # srt = angle of text: 45 degree angle to X axis
dev.off()
}
# ÀÊ vs Ñàìîë¸ò
tab3 = table(df$`Íàïðàâëåíèå`, df$`Ñàìîë¸ò`)
tab3 = tab3[as.character(df_cities$Var1), as.character(df_jets$Var1)]
mosaicplot(tab3, las = 2, col = "cyan4", main = "")
mosaicplot(t(tab3), las = 2, col = "cyan4", main = "")
if (PlotsOutput) {
png(filename = file.path(plotDir, paste("Mosaic_Airline_vs_Jet ", Sys.Date(), " ", airport_en, ".png", sep = "")), width = 800, height = 800, units = "px", pointsize = 12, bg = "white", res = NA, family = "", restoreConsole = TRUE, type = c("cairo-png"))
par(mar = rep(.5, 4))
mosaicplot(tab3, las = 2, col = "cyan4", main = "")
text(x = grconvertX(0.5, from = "npc"), y = grconvertY(0.5, from = "npc"),
labels = "Ñòåïàí Ñóøêî", cex = 3, font = 2, col = adjustcolor("steelblue", alpha.f = 0.35), srt = 45)
dev.off()
png(filename = file.path(plotDir, paste("Mosaic_Jet_vs_Airline ", Sys.Date(), " ", airport_en, ".png", sep = "")), width = 800, height = 800, units = "px", pointsize = 12, bg = "white", res = NA, family = "", restoreConsole = TRUE, type = c("cairo-png"))
par(mar = rep(.5, 4))
mosaicplot(t(tab3), las = 2, col = "cyan4", main = "", cex = 1.1)
text(x = grconvertX(0.5, from = "npc"), # align to center of plot X axis
y = grconvertY(0.5, from = "npc"), # align to center of plot Y axis
labels = "Ñòåïàí Ñóøêî", # our watermark