96 lines
2.0 KiB
R
96 lines
2.0 KiB
R
library(dplyr)
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library(plotly)
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library(mgcv)
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cov <- read.csv("proj2/owid-covid-data.csv", header = TRUE)
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cov_pl <- cov[cov$location == "Poland",]
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# Poland - new deaths by date ---------------------------------------------
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plot_ly(
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cov_pl,
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x = cov_pl$date,
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y = cov_pl$new_deaths,
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name = "New deaths",
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type = "scatter",
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mode = "lines+markers"
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)
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# Poland - new deaths vs new cases per million ----------------------------
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plot_ly(
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cov_pl,
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x = cov_pl$date,
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y = cov_pl$new_deaths_per_million,
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name = "New deaths per million",
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type = "scatter",
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mode = "lines+markers"
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) %>%
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add_trace(
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y = cov_pl$new_cases_per_million,
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name = "New cases per million",
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type = "scatter",
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mode = "lines+markers"
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)
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# Poland - vaccines by date -----------------------------------------------
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cov_pl_vac = cov_pl[as.POSIXct(cov_pl$date) > as.POSIXct('2020-12-12'),]
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plot_ly(
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cov_pl_vac,
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x = cov_pl_vac$date,
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y = cov_pl_vac$people_vaccinated,
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name = "People vaccinated",
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type = "scatter",
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mode = "lines",
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connectgaps = TRUE
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) %>%
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add_trace(
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y = cov_pl_vac$people_fully_vaccinated,
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name = "People fully vaccinated",
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type = "scatter",
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mode = "lines",
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connectgaps = TRUE
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)
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# World - new deaths vs new vaccines ---------------------------------------
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cov_vac <- cov[as.POSIXct(cov$date) > as.POSIXct('2020-12-12'),]
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cov_vac[["new_vaccinations"]][is.na(cov_vac[["new_vaccinations"]])] <- 0
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cov_vac[["new_deaths"]][is.na(cov_vac[["new_deaths"]])] <- 0
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df <- data.frame(
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date=cov_vac$date,
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new_deaths=cov_vac$new_deaths,
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new_vaccinations=cov_vac$new_vaccinations
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)
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df <- df %>%
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group_by(date)
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plot_ly(
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df,
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x = df$date,
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y = df$new_deaths,
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name = "New deaths",
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type = "scatter",
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mode = "lines"
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) %>%
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add_lines(
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y = df$new_vaccinations,
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name = "New vaccines"
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)
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# World - deaths by country -----------------------------------------------
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plot_ly(
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cov,
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x = cov$date,
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y = cov$new_deaths,
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name = "New deaths",
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type = "scatter",
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mode = "lines",
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connect_gaps = TRUE,
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color = cov$location
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)
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