Loading data
# Packages
#library(easypackages)
#packages("readxl", "httr", "tidyverse", "ggplot2", "ggthemes", "Rcpp")
#library(rgeos) #Musi byt spusteny pred maptools (nahrazuje gpclib)
#library(ggmap)
#library(maptools)
#library(rgdal)
#library(RColorBrewer)
#library(plotly)
#browseURL("https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide", browser = getOption("browser"), encodeIfNeeded = FALSE)
url4 = paste("https://www.ecdc.europa.eu/sites/default/files/documents/COVID-19-geographic-disbtribution-worldwide-","2020-10-09", ".xlsx", sep = "")
# url4 = paste("https://www.ecdc.europa.eu/sites/default/files/documents/COVID-19-geographic-disbtribution-worldwide-",format(Sys.time(), "%Y-%m-%d"), ".xlsx", sep = "") # Better, but only works after data dayly actualisation
GET(url4, write_disk(tf <- tempfile(fileext = ".xlsx")))
## Response [https://www.ecdc.europa.eu/sites/default/files/documents/COVID-19-geographic-disbtribution-worldwide-2020-10-09.xlsx]
## Date: 2020-10-10 19:17
## Status: 200
## Content-Type: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
## Size: 2.76 MB
## <ON DISK> C:\Users\FRANCE~1\AppData\Local\Temp\RtmpwdvjKk\file239c49aa4747.xlsx
Summarizing data
data$GeoId = data$geoId
data$Cases = data$cases
data$Deaths = data$deaths
data$DateRep = data$dateRep
data$Month = data$month
df = data %>%
group_by(GeoId) %>%
summarise(cases = sum(Cases), deaths = sum(Deaths))
## `summarise()` ungrouping output (override with `.groups` argument)
df[df$GeoId=="UK",]$GeoId = "GB"
df[df$GeoId=="EL",]$GeoId = "GR"
head(df)
## # A tibble: 6 x 3
## GeoId cases deaths
## <chr> <dbl> <dbl>
## 1 AD 2568 54
## 2 AE 102929 438
## 3 AF 39693 1472
## 4 AG 111 3
## 5 AI 3 0
## 6 AL 14899 411
First graphs
ggplot(df[df$cases > 500000, ], aes(reorder(x = GeoId, X = cases), y = cases, fill = GeoId)) +
geom_bar(stat = "identity") +
theme_light() +
labs(title = "Země s výskytem případů Covid-19 nad 500.000",
x = "kód země",
y = "počty případů") +
guides(fill = "none")
![](data:image/png;base64,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)
ggplot(df[df$deaths > 30000, ], aes(reorder(x = GeoId, X = deaths), y = deaths, fill = GeoId)) +
geom_bar(stat = "identity") +
theme_light() +
#scale_y_log10() +
# scale_fill_stata("s2color") +
labs(title = "Země s počtem úmrtí na Covid-19 nad 30.000",
x = "kód země",
y = "počty úmrtí") +
guides(fill = "none")
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)
Map - code provided by Patrik Galeta (except just small changes)
# Code by Patrik Galeta follows:
# Nahrat shapefile
world_shp = readOGR(paste(getwd(), "/shp_world", sep = ""),
layer = "TM_WORLD_BORDERS_SIMPL-0.3",
use_iconv = TRUE, encoding = "utf-8")
## OGR data source with driver: ESRI Shapefile
## Source: "D:\ownCloud2\!!!Vyuka\!KSS-KA1\shp_world", layer: "TM_WORLD_BORDERS_SIMPL-0.3"
## with 246 features
## It has 11 fields
## Integer64 fields read as strings: POP2005
# Spojeni shape data s df, mapove podklady se spoji s informaci o poctu pripadu
db <- merge(x = world_shp@data, y = df, by.x = "ISO2", by.y = "GeoId")
# Uprava shape file pro ggplot
world_fortified <- fortify(world_shp, region = "ISO2")
## Warning in RGEOSUnaryPredFunc(spgeom, byid, "rgeos_isvalid"): Ring Self-
## intersection at or near point -53.756366730000003 48.50326347
## Warning in RGEOSUnaryPredFunc(spgeom, byid, "rgeos_isvalid"): Ring Self-
## intersection at or near point -70.917236329999994 -54.70861816
## Warning in RGEOSUnaryPredFunc(spgeom, byid, "rgeos_isvalid"): Ring Self-
## intersection at or near point 5.3369464899999999 61.592775340000003
## Warning in RGEOSUnaryPredFunc(spgeom, byid, "rgeos_isvalid"): Ring Self-
## intersection at or near point 143.66192817999999 49.312211990000002
## SpP is invalid
## Warning in rgeos::gUnaryUnion(spgeom = SpP, id = IDs): Invalid objects found;
## consider using set_RGEOS_CheckValidity(2L)
world_fortified_df <- left_join(world_fortified, db, by=c("id"="ISO2"))
db = within(db, {
LAB = paste0(ISO2, ": ",cases)
})
# Mapa
g = ggplot() +
geom_polygon(data = world_fortified_df[world_fortified_df$REGION==c(150)&
world_fortified_df$id!="RU",],
aes(x = long, y = lat, group = group, fill = cases),
col = "grey44") +
geom_text(data = db[db$REGION==c(150)&db$ISO2!="RU",],
aes(x = LON, y = LAT, label = LAB), size = 2.2, col = "black") +
guides(size = F, fill = F) +
scale_fill_gradientn(colours = brewer.pal(n = 8, name = "Dark2")[-(1)])+
labs(title = paste0("Confirmed coronavirus cases by ", format(Sys.time(), "%d. %m. %Y"))) +
theme_void() +
theme(plot.title = element_text(face = "bold", size = 10))
ggplotly(g)
## Warning: `group_by_()` is deprecated as of dplyr 0.7.0.
## Please use `group_by()` instead.
## See vignette('programming') for more help
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_warnings()` to see where this warning was generated.