Pablo-source/Shiny-app-using-COVID-data

Compute 10,000 population rates for COVID19 Confirmed, Death and Recovered cases

Closed this issue · 2 comments

Compute 10,000 population rates for each of the metrics in METRICS_FOR_POP_RATES file using previously created cleansed country population figures for year 2019.

  • Contry level population figures for 2019
    WDI_countries_pop_2019_clean <- WDI_countries_pop_2019_no_NA
    WDI_countries_pop_2019_clean

write.csv(WDI_countries_pop_2019_clean,here("original_data_processed","WDI_countries_pop_2019_clean.csv"), row.names = TRUE)

We will merge WDI_countries_pop_2010_clean file to incorporate individual country population figures to the Confirmed, Death and Recovered figures with previous file METRICS_FOR_POP_RATES.

The calculations we will introduce will follow a formula similar to this one below:
Population rates for each of the COVID19 recorded metrics (Confirmed, Deaths, Recovered) cases.
CONFR =ceiling((ifelse(ConfM==0,0,ConfM/population)*10000)),
DEATHR =ceiling( (ifelse(DeathfM==0,0,DeathfM/population)*10000)),
RECR = ceiling((ifelse(RecfM==0,0,RecfM/population)*10000)),

Started today working on this new script to compute population rates for each COVID-19 Metrics:

Created new R script called “02 Covid_metrics_population_rates.R” to merge original METRICS_FOR_POP_RATES.csv file stored in \original_data_processed with WDI_countries_pop_2019_clean.csv file stored in the same folder. This new R script will replace existing “02 Leaf and pop figures_SHINY.R” file.

closing issue, I will create new one after checking some COUNTRY names to merge both METRICS and POPULATION files