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Usage

library(idmc)

The simple use for the idmc package is to retrieve the data from the API directly into R.

df <- idmc_get_data()
df
#> # A tibble: 20,289 × 26
#>        id country  iso3  latitude longitude centroid displacement_type qualifier
#>     <int> <chr>    <chr>    <dbl>     <dbl> <chr>    <chr>             <chr>    
#>  1 120233 United … USA      31.1     -93.2  [31.114… Disaster          total    
#>  2 120186 United … USA      39.1     -94.5  [39.092… Disaster          total    
#>  3 120191 United … USA      44.9    -123.   [44.912… Disaster          total    
#>  4 120197 Dominic… DOM      19.3     -70.0  [19.281… Disaster          total    
#>  5 120195 Dominic… DOM      19.3     -70.0  [19.281… Disaster          total    
#>  6 120110 France   FRA      44.5       6.47 [44.498… Disaster          more than
#>  7 120124 Indones… IDN      -7.46    109.   [-7.458… Disaster          total    
#>  8 120188 United … USA      30.7     -93.5  [30.706… Disaster          total    
#>  9 120208 Viet Nam VNM      22.8     105.   [22.779… Disaster          total    
#> 10 120047 Philipp… PHL       6.85    124.   [6.8514… Disaster          total    
#> # ℹ 20,279 more rows
#> # ℹ 18 more variables: figure <int>, displacement_date <date>,
#> #   displacement_start_date <date>, displacement_end_date <date>, year <int>,
#> #   event_name <chr>, event_start_date <date>, event_end_date <date>,
#> #   category <chr>, subcategory <chr>, type <chr>, subtype <chr>,
#> #   standard_popup_text <chr>, event_url <chr>, event_info <chr>,
#> #   standard_info_text <chr>, old_id <chr>, created_at <date>

This data frame, with variables described in the API documentation, includes 1 row per event. We can normalize this to daily displacement, assuming uniform distribution of displacement between start and end date, for all countries and type of displacement. idmc_transform_daily().

idmc_transform_daily(df)
#> # A tibble: 611,660 × 5
#>    iso3  country    displacement_type date       displacement_daily
#>    <chr> <chr>      <chr>             <date>                  <dbl>
#>  1 AB9   Abyei Area Conflict          2018-01-01                  0
#>  2 AB9   Abyei Area Conflict          2018-01-02                  0
#>  3 AB9   Abyei Area Conflict          2018-01-03                  0
#>  4 AB9   Abyei Area Conflict          2018-01-04                  0
#>  5 AB9   Abyei Area Conflict          2018-01-05                  0
#>  6 AB9   Abyei Area Conflict          2018-01-06                  0
#>  7 AB9   Abyei Area Conflict          2018-01-07                  0
#>  8 AB9   Abyei Area Conflict          2018-01-08                  0
#>  9 AB9   Abyei Area Conflict          2018-01-09                  0
#> 10 AB9   Abyei Area Conflict          2018-01-10                  0
#> # ℹ 611,650 more rows

While there are a few other parameters you can play around with in these functions, this is the primary purpose of this simple package.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.