PRAWNS

This package allows pollution data in a raster format for England to be linked with LSOAs, geographcal areas with associated national statistics such as Index of Multiple Deprivation (IMD) score. It currently accepts data in the format provided by the National Atmospheric Emissions Inventory (NAEI) for emissions, and specific publicly available data files for the national statistics.

Installation

You can install the development version of PRAWNS from GitHub with:

# install.packages("devtools")
devtools::install_github("Nathan-303/PRAWNS")

Input data

This package takes inputs with a particular data structure, and is designed to work with specified data sources. A full explanation of what to use is included in the setting_up_data_sources vignette

Outputs

This package produces csv files linking LSOAs to average emissions, as well as a variety of graphs using this data. Should further data processing be required, or additional data be used, the PRAWNS.csv object from create_prawns() or as a side effect of bulk_processor() can be further processed as it links all the data back to LSOA code.

Example

Create the standardised PRAWNS object used for all the graphing and analysis functions

create_prawns(raster_path= "Data/NOx_rasters_2019",
              shapefile_path = "Data/2011_LSOA_shapefile_20m_generalised",
              data_path= list.files("Data/LSOA_statistics"),
              key_variable = "LSOA19CD",
              key_variable_aliases =c("LSOA.code..2011.","?..LSOA11CD"),
              output_path="Outputs/create_prawns_1_0_0_test.csv",
              pollutant_data_name = "nox",
              year=2019,
              pollutant="NOx")
}

Get a graphical summary of the distribution of a pollutant in a city

city_summary(prawn_path = "Outputs/create_prawns_1_0_0_test.csv",
                   shape_path = "Data/2011_LSOA_shapefile_20m_generalised",
                   targets = "London",
                   output_path= "Outputs/geographic_summary1_0_0_test",
                    pollutant="NOx"
                  )

Calculate the difference between the most and least deprived deciles

stat_wrangler(prawn_path = prawn_path,deciles=c(1,10))