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sedtR
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<!-- README.md is generated from README.Rmd. Please edit that file --> # sedtR <!-- badges: start --> [](https://lifecycle.r-lib.org/articles/stages.html#experimental) [](https://www.gnu.org/licenses/gpl-3.0) <!-- badges: end --> ### Purpose of `sedtR`: The `sedtR` package allows R programmers to easily interact with Urban’s [Spatial Equity Data Tool](https://apps.urban.org/features/equity-data-tool/) (SEDT) [public application programming interface](https://ui-research.github.io/sedt_documentation/api_documentation.html) (API). ## Background ### What is the Spatial Equity Data Tool? The SEDT enables local, state, and federal leaders, as well as the general public, to upload their own point spatial data and quickly assess whether place-based programs and resources – such as parks, libraries, wi-fi hotspots or electric vehicle charging stations – are equitably distributed across neighborhoods and demographic groups. The tool – launched in 2020 and expanded in 2021 – has been used by a wide variety of experts and nonexperts alike to assess equity in the distribution of local programs and resources. For example, the Bloomington Pedestrian and Bicycle Safety Commission analyzed sidewalk funding allocations, and advocates in Cincinnati identified economic and racial inequities in car crash locations. ### Why Create a Public API and `sedtR`: Through engagements with local government and nonprofit users, we identified a key barrier. Organizations wanted to embed the SEDT within their own tools and data workflows and thus make the Tool a core part of institutional processes. However, before the API’s release in March of 2024, Tool users would have had to visit Urban’s website and use the GUI interface to upload one dataset at a time whenever new analyses were needed. The release of the API overcomes this barrier by allowing programmatic access to the Tool. We wrote `sedtR` to wrap the public API’s endpoints in user-friendly R code. We are hopeful that `sedtR` makes it easy for researchers, analysts, and policymakers to incorporate SEDT calculations into R workflows. The SEDT enables local, state, and federal leaders, as well as the general public, to upload their own point spatial data and quickly assess whether place-based programs and resources – such as parks, libraries, wi-fi hotspots or electric vehicle charging stations – are equitably distributed across neighborhoods and demographic groups. ## Installation You can install the development version of sedtR from [GitHub](https://github.com/) with: ``` r # install.packages("devtools") devtools::install_github("UrbanInstitute/sedtR") ``` ## Example The following example illustrates using the `call_sedt_api()` function on Minneapolis, MN bikeshare data stored on the Urban Institute’s [Data Catalog](https://datacatalog.urban.org/). ``` r library(sedtR) #> Loading sedtR - using the production API ``` ``` r # Call sedt API with wrapper function sedt_response <- call_sedt_api( resource = "https://equity-tool-api.urban.org/sample-data/minneapolis_bikes.csv", geo = "city", acs_data_year = 2021 ) #> getting output file ``` A resource can be a path or URL for an existing delimited (`csv` or `tsv`) file with coordinate columns, a spatial data file that can be read with `sf::read_sf()`, a `sf` object, or a URL for a FeatureLayer. Any input spatial data file or object *must* use POINT geometry. `call_sedt_api()` returns a list object that contains a `sf` object storing the geographic disparity scores: ``` r sedt_response$geo_bias_data |> head() #> sig_diff_seniors data_prop diff_cb_renter_hh diff_pop prop_children #> 1 TRUE 0.00000 0.000 -0.008 0.01043 #> 2 FALSE 0.00506 -0.004 -0.007 0.01378 #> 3 TRUE 0.00000 -0.002 -0.008 0.00746 #> 4 TRUE 0.00000 -0.003 -0.011 0.01193 #> 5 TRUE 0.00000 0.000 -0.008 0.00486 #> 6 FALSE 0.00253 -0.002 -0.002 0.00533 #> diff_no_internet diff_under_200_poverty_line GEOID diff_pov #> 1 -0.006 -0.008 27053000101 -0.003 #> 2 -0.008 -0.010 27053000102 -0.005 #> 3 -0.007 -0.006 27053000300 -0.007 #> 4 -0.007 -0.009 27053000601 -0.005 #> 5 -0.006 -0.002 27053000603 -0.002 #> 6 0.001 -0.002 27053001100 -0.001 #> diff_seniors diff_children prop_under_200_poverty_line prop_cb_renter_hh #> 1 -0.007 -0.010 0.00809 0.00049 #> 2 -0.004 -0.009 0.01458 0.00937 #> 3 -0.008 -0.007 0.00563 0.00158 #> 4 -0.015 -0.012 0.00855 0.00316 #> 5 -0.007 -0.005 0.00243 0.00024 #> 6 0.000 -0.002 0.00517 0.00487 #> prop_no_internet prop_pop #> 1 0.00552 0.00786 #> 2 0.01252 0.01152 #> 3 0.00728 0.00753 #> 4 0.00735 0.01091 #> 5 0.00622 0.00761 #> 6 0.00198 0.00493 #> geometry #> 1 -93.31950, -93.31419, -93.30431, -93.29919, -93.29921, -93.29906, -93.30668, -93.31943, -93.31943, -93.31944, -93.31950, 45.05125, 45.05124, 45.05118, 45.05114, 45.04392, 45.03766, 45.03935, 45.04217, 45.04397, 45.04760, 45.05125 #> 2 -93.29919, -93.29409, -93.29153, -93.28223, -93.28083, -93.28343, -93.28321, -93.28270, -93.28673, -93.28811, -93.28811, -93.29041, -93.29403, -93.29489, -93.29906, -93.29921, -93.29919, 45.05114, 45.05113, 45.05113, 45.05116, 45.04357, 45.03536, 45.03345, 45.03243, 45.03151, 45.03151, 45.03272, 45.03473, 45.03646, 45.03674, 45.03766, 45.04392, 45.05114 #> 3 -93.31879, -93.30856, -93.30848, -93.30833, -93.31343, -93.31853, -93.31862, -93.31870, -93.31879, 45.03546, 45.03545, 45.03132, 45.02409, 45.02410, 45.02409, 45.02772, 45.03134, 45.03546 #> 4 -93.26411, -93.26238, -93.26210, -93.25998, -93.25992, -93.24985, -93.24739, -93.24218, -93.23711, -93.23711, -93.23712, -93.23712, -93.23711, -93.24748, -93.24734, -93.26071, -93.26311, -93.26269, -93.26411, 45.02760, 45.02760, 45.02944, 45.03051, 45.03554, 45.03555, 45.03555, 45.03558, 45.03561, 45.02766, 45.02405, 45.02397, 45.02044, 45.02038, 45.01677, 45.01682, 45.01682, 45.02101, 45.02760 #> 5 -93.23712, -93.23711, -93.23711, -93.22693, -93.22690, -93.22690, -93.22688, -93.22687, -93.22686, -93.22686, -93.22961, -93.23328, -93.23712, -93.23712, 45.02405, 45.02766, 45.03561, 45.03567, 45.02773, 45.02771, 45.02410, 45.02047, 45.01951, 45.01892, 45.01922, 45.02226, 45.02397, 45.02405 #> 6 -93.24748, -93.23711, -93.23713, -93.23715, -93.24225, -93.24734, -93.24734, -93.24748, 45.02038, 45.02044, 45.01682, 45.01320, 45.01318, 45.01316, 45.01677, 45.02038 #> prop_pov prop_seniors sig_diff_cb_renter_hh sig_diff_children sig_diff_pop #> 1 0.00345 0.00684 FALSE TRUE TRUE #> 2 0.01036 0.00938 FALSE TRUE TRUE #> 3 0.00721 0.00799 FALSE TRUE TRUE #> 4 0.00515 0.01453 FALSE TRUE TRUE #> 5 0.00160 0.00700 FALSE TRUE TRUE #> 6 0.00384 0.00330 FALSE FALSE TRUE #> sig_diff_no_internet sig_diff_pov disp_name #> 1 FALSE FALSE Census Tract 1.01, Minneapolis, MN #> 2 FALSE FALSE Census Tract 1.02, Minneapolis, MN #> 3 FALSE TRUE Census Tract 3, Minneapolis, MN #> 4 TRUE TRUE Census Tract 6.01, Minneapolis, MN #> 5 TRUE FALSE Census Tract 6.03, Minneapolis, MN #> 6 FALSE FALSE Census Tract 11, Minneapolis, MN #> sig_diff_under_200_poverty_line weighted_counts #> 1 TRUE 0 #> 2 TRUE 2 #> 3 TRUE 0 #> 4 TRUE 0 #> 5 TRUE 0 #> 6 FALSE 1 ``` A data frame with demographic information used in the analysis is also returned: ``` r sedt_response$demo_bias_data |> head() #> census_var data_value summary_value diff_data_city #> 1 pct_no_internet 8.78435 7.752 1.03235 #> 2 pct_under_200_poverty_line 37.70731 33.240 4.46731 #> 3 pct_all_other_races 6.23852 6.280 -0.04148 #> 4 pct_less_hs_diploma 10.10677 9.295 0.81177 #> 5 pct_under18_unins 4.50332 3.074 1.42932 #> 6 pct_under18_pov 19.22721 21.193 -1.96579 #> data_value_sd summary_value_margin sig_diff geo geo_fips geo_display #> 1 0.54109 0.508 FALSE city 2743000 Minneapolis, MN #> 2 0.74891 0.955 TRUE city 2743000 Minneapolis, MN #> 3 0.32612 0.395 FALSE city 2743000 Minneapolis, MN #> 4 0.62023 0.532 FALSE city 2743000 Minneapolis, MN #> 5 1.49243 0.495 FALSE city 2743000 Minneapolis, MN #> 6 2.10830 1.697 FALSE city 2743000 Minneapolis, MN #> geo_mo baseline_pop #> 1 null total_pop #> 2 null total_pop #> 3 null total_pop #> 4 null total_pop #> 5 null under18_pop #> 6 null under18_pop ``` The package allows users to visualize the geographic disparity scores and demographic disparity scores with `create_map()` and `create_demo_chart()`, respectively. Like the interactive visualizations on the \[SEDT website\] (<https://apps.urban.org/features/equity-data-tool/>), these functions allow users to visualize different geographic or demographic disparity scores. `create_map()` allows interactive or static visualizations. ``` r create_map(sedt_response$geo_bias_data, interactive = FALSE, # optional, defaults to TRUE save_map = FALSE, #optional, defaults to FALSE. If TRUE, provide file_path col_to_plot = "diff_pop") #optional, default is "diff_pop" #> tmap mode set to plotting ``` <img src="man/figures/README-unnamed-chunk-5-1.png" width="100%" /> ``` r create_demo_chart(sedt_response$demo_bias_data, group = "total", # optional, default is "total" save_chart = FALSE) # optional, default is FALSE. If TRUE provide file_path ``` <img src="man/figures/README-unnamed-chunk-6-1.png" width="100%" /> By default, these functions do not save the resulting images, but both provide arguments (`save_map` and `save_chart`) which take logicals and allow a user to save the outputted visualization. ## Where Can I Learn More: The Spatial Equity Data Tool has comprehensive documentation in the form of an [online book](https://ui-research.github.io/sedt_documentation/). Most notably, there is a chapter [specifically devoted to the API](https://ui-research.github.io/sedt_documentation/api_documentation.html). It provides more in-depth `sedtR` code and outputs. Other particularly relevant chapters cover [common API errors and warnings](https://ui-research.github.io/sedt_documentation/common_errors_warnings.html), [how to interpret Tool results](https://ui-research.github.io/sedt_documentation/interpreting_results.html), and a [description of data appropriate for the Tool](https://ui-research.github.io/sedt_documentation/resource_datasets.html). ## Feedback: Please provide feedback by opening [GitHub Issues](https://github.com/UrbanInstitute/sedtR/issues) or contacting us at <sedt@urban.org>.
