The WHOData project aims to tidy the World Health Organisation's (WHO) mortality data using R. This is a group exercise to help some newcomers learn about cleaning and manipulating data using the R tidyverse (https://github.com/tidyverse/tidyverse). Please install the tidyverse before you start.
The following steps can be used as guide to work your way through this challenge. Please use the WHOMortalityData.Rmd file to get started as it outlines some of the key steps.
- Data source: http://www.who.int/healthinfo/mortality_data/en/
- It is assumed that data has been downloaded
- Install the tidyverse packages using
install.packages("tidyverse") - Reading in the WHO mortality data
- Reading the International Classificaion of Diseases data
- Keep the neoplasm, melanoma, lymphoma and leukaemia data for ICD10 part 1
- Tranform the data into long format for the number of deaths
- Transform the population data in long format
- Merge the long population data to the long neoplasm data
- Care has to be taken with respect to the format of the age groups.
- Combine the youngest age groups into a new 0-4 years.
- Calculate the mortality rate per 100,000 population in a new variable
- rate = (100000*deaths)/pop
- Write a function that will extract data based on country, cause of death, year and sex
- If any of these are left blank then all the data is extracted
- A data frame containing the requested data should be returned.
- Next steps will defined later
- Sumamry graphs
- Summary tables