Trying out an example using read_dkan from the daltare/dkanTools package

https://rdrr.io/github/daltare/dkanTools/man/read_dkan.html#heading-4

We use data from the Safety Net Almanac data in the Urban Data Catalog: https://datacatalog.urban.org/dataset/safety-net-almanac-data

The Safety Net Almance is online to show examples of how the graphics should look: http://safetynet.urban.org

We use the dkanTools package, documentation here: https://rdrr.io/github/daltare/dkanTools/

First get some libraries we usually like to use then install the dkanTools package (once) and use the library(dkanTools)

library(ggplot2)
library(urbnthemes)
library(extrafont)
library(tidyverse)
library(sys)
#install.packages("remotes")                   # 
#remotes::install_github("daltare/dkanTools")  # we'll install once and then comment out
library(dkanTools)

Try accessing a datastore

Populate three dataframes: df_graphic, df_data, and df_meta.

The df_graphic dataframe gives us parameters for the graphic, like title, subtitle, notes, and the “statid” of the statistic being used. The df_data dataframe gives us the data, filtered by the statid from df_graphic The df_meta dataframe gives us the metadata for the statid, but the information from the graphic should override (don’t use this much)

Following the example from https://rdrr.io/github/daltare/dkanTools/f/README.md (which gave a 404) use our SNAP data from Safety Net Almanac instead of the California data portal

The read_dkan() function is what we need, see here https://rdrr.io/github/daltare/dkanTools/man/read_dkan.html

# the resource ids used for programs are listed below
# resource ids for the graphics and the metadata for statistics will stay the same (until they change!?)
#
#  'SNAP'       '6fc0556b-de8b-41b9-a535-33243f2eb490' 
#  'TANF'       'a77378a2-f26b-4802-be45-d558ea47b65b'
#  'EITC'       '8ecae928-c689-48cc-8953-6d4e0afc31bd'
#  'ECON'       'f4041439-66ea-49cf-9b41-685c6036ed93'
#  'SSI'        '47df5bf5-0305-4df1-98dd-a2320941ecd3'
#  'CCDF'       '441d6b32-d52f-4cbf-acf7-bff14fd06bc1'
#  'HUD'        '06eac4b8-dbcd-41bf-81ce-1b15c771d048'
#  'UI'         '951d6ace-51d1-4956-beaa-df5db9f1e9ae'
#  'MEDICAID'   '6ae37f37-bbe5-4961-a092-abe8742742e8'
# 
# for this example, use SNAP program data, graphic ID 26, which retrieves data for statid 193 from 1999 through 2012
# which should look like this https://datatools.urban.org/safetynet/Data/Series_Line/template.cfm?GraphicID=26
#
# you can change mygraphicid to values like the following, to get various SNAP graphics:
#
# GraphicID Title
#   4         SNAP Caseloads as Monthly Average of Individuals, 1969-2012   
#   6         SNAP Total Benefits Paid, 1969-2012   
#   7         SNAP Federal and State Program Costs, 1969-2012   
#  26         SNAP National Participation Rate, 1999-2010   
#  47         SNAP Caseloads as Monthly Average of Households, 1989-2011    
# 149         SNAP Federal and State Program Costs, 1969-2012   
#
mygraphicid <- 149
my_graphic_resource_id  <- 'aa7c5ea3-ff23-494d-8bbf-a7496a0541bc'  # resource id for Safety Net Graphics definitions data
my_data_resource_id     <- '6fc0556b-de8b-41b9-a535-33243f2eb490'  # resource id for SNAP program data
my_meta_resource_id     <- '4ea56583-1376-4a4e-93d3-757b736ea964'  # resource id for Statistics Reference meta data in SNA

df_graphic  <- read_dkan(base_URL='https://datacatalog.urban.org/', resource_id = my_graphic_resource_id, filter_fields = c('graphicid'), filter_values = mygraphicid )
df_data     <- read_dkan(base_URL='https://datacatalog.urban.org/', resource_id = my_data_resource_id, filter_fields = c('statid'), filter_values = df_graphic['statid']) 
df_meta     <- read_dkan(base_URL='https://datacatalog.urban.org/', resource_id = my_meta_resource_id, filter_fields = c('statid'), filter_values = df_graphic['statid'])

ok, now that we have the three dataframes, let’s try a ggplot

#
# following the calls, we should have the dataframes from the read_dkan function 
mytitle     <-  df_graphic["title"]
mysubtitle  <-  df_graphic["subtitle"]
mynotes     <-  paste("Source:",df_graphic["graphic_source"], "\n" , "Note:",df_graphic["graphic_note"])
mylegend_y  <-  df_graphic['yaxis_label']
my_s1_scaler <- as.double(df_graphic['s1_scaler'])

mydata <- df_data  

# pass the data and labels to ggplot
ggplot(data = mydata, mapping = aes(x = year, y = as.double(data)*my_s1_scaler, group=1)) +
  geom_line() +
  scale_y_continuous(labels = scales::comma) +
  scale_x_discrete() +
  theme(axis.text.x = element_text(angle = 45)) +
  labs(title = mytitle,
       subtitle = mysubtitle,
       caption = mynotes,
       x = "Year",
       y = mylegend_y )

Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.