Skip to content

Latest commit

 

History

History
103 lines (84 loc) · 3.26 KB

CONTRIBUTING.md

File metadata and controls

103 lines (84 loc) · 3.26 KB
Raw

Quick Contributions:

Add a dataset to the app! Currently, 15 of approximately 200 datasets have been cleaned and incorporated into the app. The full list is here: ods_dataset_lookup.

After forking this repo

  1. Pick a dataset from the list and investigate it using either the opendatascot library or finidng the dataset on statistics.gov.scot. Make sure the dataset fits the following criteria:

    • does not currently exist within the app
    • has associated datazones - health boards (S08....), or local authorities (council areas, S12....)

  2. Get to know the data

    • decide which variables should be able to be explored by the user in the app

  3. Decide what changes must be made to the dataset to bring it into accordance with the standard for the app. Expected form:

area_code reference_area area_type exploratory_vars (depends on dataset) value units
S12000033 Aberdeen City Local Authority 2005-2007 Count 1000 Persons
S12000033 Aberdeen City Local Authority 2005-2007 Ratio 0.62 Persons Per 1000

For consistency in the ui, explanatory vars should be limited to 4 (max.) and any reference period/year vars should be listed first.

  1. Clean and wrangle the data so that it is in the standard form for the app. Variables should be snake_case. Values should be in Title Case.

Have a look at and follow the style of cleaning_script.

  1. Update the cleaning script

  2. Update the file list_of_dfs.R

The first level of the list contains categories or "themes" from statistics.gov.uk. Each category is a list of lists. When adding the now-cleaned dataset follow this pattern:

"dataset_name(from statistics.gov)" = list(
  data = read_csv("data/clean_data/clean_dataset.csv"),
  explorable_vars = c("var_1", "var_2"),
  reverse_colours = FALSE (default is light colour for low numbers, to reverse this, change this value to TRUE),
  by_pop = FALSE, (if it's useful to allow the user to compare the value/1000 people then set this to TRUE),
  url = "link_to_data",
  notes = c("The data was collected every three years.", "In the app, each element of this vector is given a new paragraph")
)

e.g.

"Council House Sales" = list(
  data = read_csv("data/clean_data/council_house_sales.csv"),
  explorable_vars = c("year", "dwelling_type"),
  reverse_colours = FALSE,
  by_pop = TRUE,
  url = "",
  notes = ""
)

  1. Test the app (both for your added dataset and previous (working) datasets)

  2. Open pull request

It's recommended to create a Git branch for each PR and please limit one dataset addition per pull request.

Thoughtful Contributions:

Alterations to the app. (e.g. more functionality.)

Making use of the opendatascot package for more readable and maintainable practice.