convert csv to json to allow special characters in string variables

2_process.R

@@ -70,6 +70,11 @@ p2_targets <- list(
                # distinct(determinant, .keep_all = TRUE) |> 
                readr::write_csv('public/determinant_uncertainty.csv')
              ),
+tar_target(p2_unc_determinant_json,
+           read_csv(p2_unc_agg_summary_csv) |>
+             toJSON(pretty = TRUE) |>
+             write("public/determinant_uncertainty.json")
+           ),
 tar_target(`p2_unc_agg_summary_ind_csv`,
            p2_unc_agg_ind_summary |>
              left_join(p2_top_trend_ind_stats) |>
@@ -103,9 +108,13 @@ tar_target(`p2_unc_agg_summary_ind_csv`,
                   "B03001_003", "B01001_002", "B01001_026")
              ),
   tar_target(p2_census_acs5_data,
-             get_census_data(geography = 'county', variable = p2_census_acs5_layers,
-                             states = p1_census_states, year = 2022, proj = p1_proj, 
-                             survey_var = "acs5",  percent_rename = FALSE),
+             get_census_data(geography = 'county', 
+                             variable = p2_census_acs5_layers,
+                             states = p1_census_states, 
+                             year = 2022, 
+                             proj = p1_proj, 
+                             survey_var = "acs5",  
+                             percent_rename = FALSE),
              pattern = map(p2_census_acs5_layers),
              iteration = "list"
              ),
@@ -131,9 +140,13 @@ tar_target(`p2_unc_agg_summary_ind_csv`,
 tar_target(p2_census_acs5sub_age_layers,
              c("S0101_C02_022", "S0101_C02_023", "S0101_C02_024", "S0101_C02_028")),
 tar_target(p2_census_acs5sub_age_data,
-           get_census_data(geography = 'county', variable = p2_census_acs5sub_age_layers,
-                           states = p1_census_states, year = 2022, proj = p1_proj,
-                           survey_var = "acs5",  percent_rename = TRUE),
+           get_census_data(geography = 'county', 
+                           variable = p2_census_acs5sub_age_layers,
+                           states = p1_census_states, 
+                           year = 2022, 
+                           proj = p1_proj,
+                           survey_var = "acs5",  
+                           percent_rename = TRUE),
            pattern = map(p2_census_acs5sub_age_layers),
            iteration = "list"),
 # income related variables 
@@ -141,9 +154,13 @@ tar_target(p2_census_acs5sub_age_data,
 tar_target(p2_census_acs5sub_income_layers,
            c("S1901_C01_014")),
 tar_target(p2_census_acs5sub_income_data,
-           get_census_data(geography = 'county', variable = p2_census_acs5sub_income_layers,
-                           states = p1_census_states, year = 2022, proj = p1_proj, 
-                           survey_var = "acs5", percent_rename = TRUE),
+           get_census_data(geography = 'county', 
+                           variable = p2_census_acs5sub_income_layers,
+                           states = p1_census_states, 
+                           year = 2022, 
+                           proj = p1_proj, 
+                           survey_var = "acs5", 
+                           percent_rename = TRUE),
            pattern = map(p2_census_acs5sub_income_layers),
            iteration = "list"),
 # education related variables 
@@ -152,9 +169,13 @@ tar_target(p2_census_acs5sub_income_data,
 tar_target(p2_census_acs5sub_education_layers,
            c("S1501_C01_003", "S1501_C01_009")),
 tar_target(p2_census_acs5sub_education_data,
-           get_census_data(geography = 'county', variable = p2_census_acs5sub_education_layers,
-                           states = p1_census_states, year = 2022, proj = p1_proj, 
-                           survey_var = "acs5", percent_rename = FALSE),
+           get_census_data(geography = 'county', 
+                           variable = p2_census_acs5sub_education_layers,
+                           states = p1_census_states, 
+                           year = 2022, 
+                           proj = p1_proj, 
+                           survey_var = "acs5", 
+                           percent_rename = FALSE),
            pattern = map(p2_census_acs5sub_education_layers),
            iteration = "list"),
 
@@ -164,9 +185,13 @@ tar_target(p2_census_acs5sub_education_data,
 tar_target(p2_census_acs5_household_layers,
            c("B25010_001", "B25064_001")),
 tar_target(p2_census_acs5sub_household_data,
-           get_census_data(geography = 'county', variable = p2_census_acs5_household_layers,
-                           states = p1_census_states, year = 2022, proj = p1_proj, 
-                           survey_var = "acs5", percent_rename = FALSE),
+           get_census_data(geography = 'county', 
+                           variable = p2_census_acs5_household_layers,
+                           states = p1_census_states, 
+                           year = 2022, 
+                           proj = p1_proj, 
+                           survey_var = "acs5", 
+                           percent_rename = FALSE),
            pattern = map(p2_census_acs5_household_layers),
            iteration = "list"),
 # percent households variable
@@ -193,9 +218,13 @@ tar_target(p2_census_acs5profile_household_sf,
 tar_target(p2_census_acs5_income_by_race_layers,
            c("B19013A_001", "B19013B_001", "B19013C_001", "B19013D_001", "B19013E_001", "B19013I_001")),
 tar_target(p2_census_acs5sub_income_by_race_data,
-           get_census_data(geography = 'county', variable = p2_census_acs5_income_by_race_layers,
-                           states = p1_census_states, year = 2022, proj = p1_proj, 
-                           survey_var = "acs5", percent_rename = FALSE),
+           get_census_data(geography = 'county', 
+                           variable = p2_census_acs5_income_by_race_layers,
+                           states = p1_census_states, 
+                           year = 2022, 
+                           proj = p1_proj, 
+                           survey_var = "acs5", 
+                           percent_rename = FALSE),
            pattern = map(p2_census_acs5_income_by_race_layers),
            iteration = "list"),
 # Disability status
@@ -204,9 +233,13 @@ tar_target(p2_census_acs5sub_income_by_race_data,
 tar_target(p2_census_acs5_disability_layers,
            c("S1810_C03_001", "S1810_C02_001")),
 tar_target(p2_census_acs5sub_disability_data,
-           get_census_data(geography = 'county', variable = p2_census_acs5_disability_layers,
-                           states = p1_census_states, year = 2022, proj = p1_proj, 
-                           survey_var = "acs5", percent_rename = FALSE),
+           get_census_data(geography = 'county', 
+                           variable = p2_census_acs5_disability_layers,
+                           states = p1_census_states, 
+                           year = 2022, 
+                           proj = p1_proj, 
+                           survey_var = "acs5", 
+                           percent_rename = FALSE),
            pattern = map(p2_census_acs5_disability_layers),
            iteration = "list")
 )
\ No newline at end of file

_targets.R

@@ -14,7 +14,8 @@ tar_option_set(packages = c('tidyverse',
                             'showtext',
                             'readr',
                             'cowplot',
-                            'rmapshaper'))
+                            'rmapshaper',
+                            'jsonlite'))
 
 # Phase target makefiles
 source("0_config.R")