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nlitkowski 2021-05-26 16:55:52 +02:00
parent c4b1aa0008
commit 6eb390fb21
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proj2/projekt2.R
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@ -1,10 +1,13 @@
library(dplyr) library(dplyr)
library(plotly) library(plotly)
library(mgcv)
cov <- read.csv("proj2/owid-covid-data.csv", header = TRUE) cov <- read.csv("proj2/owid-covid-data.csv", header = TRUE)
cov_pl <- cov[cov$location == "Poland",] cov_pl <- cov[cov$location == "Poland",]
# Poland - new deaths by date ---------------------------------------------
plot_ly( plot_ly(
cov_pl, cov_pl,
x = cov_pl$date, x = cov_pl$date,
@ -14,6 +17,8 @@ plot_ly(
mode = "lines+markers" mode = "lines+markers"
) )
# Poland - new deaths vs new cases per million ----------------------------
plot_ly( plot_ly(
cov_pl, cov_pl,
x = cov_pl$date, x = cov_pl$date,
@ -29,6 +34,8 @@ plot_ly(
mode = "lines+markers" mode = "lines+markers"
) )
# Poland - vaccines by date -----------------------------------------------
cov_pl_vac = cov_pl[as.POSIXct(cov_pl$date) > as.POSIXct('2020-12-12'),] cov_pl_vac = cov_pl[as.POSIXct(cov_pl$date) > as.POSIXct('2020-12-12'),]
plot_ly( plot_ly(
@ -48,5 +55,29 @@ plot_ly(
connectgaps = TRUE connectgaps = TRUE
) )
# World - new deaths vs new vaccines ---------------------------------------
cov_vac <- cov[as.POSIXct(cov$date) > as.POSIXct('2020-12-12'),]
cov_vac[["new_vaccinations"]][is.na(cov_vac[["new_vaccinations"]])] <- 0
cov_vac[["new_deaths"]][is.na(cov_vac[["new_deaths"]])] <- 0
df <- data.frame(
date=cov_vac$date,
new_deaths=cov_vac$new_deaths,
new_vaccinations=cov_vac$new_vaccinations
)
df <- df %>%
group_by(date)
plot_ly(
df,
x = df$date,
y = df$new_deaths,
name = "New deaths",
type = "scatter",
mode = "lines"
) %>%
add_lines(
y = df$new_vaccinations,
name = "New vaccines"
)