# 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.