Data Acquisition
| Dataset Name | Attributes | Data Type | Source |
| Free and low-cost food programs | List of all food assistance programs in Vancouver with XY Coordinate fields | Tabular | City of Vancouver Open Data Portal |
| Dissemination Area Boundary Files 2016 | Dissemination Area (DA) for all of Canada | Shapefile | Statistics Canada |
| Low Income Population Data | Number of families in the bottom half of the distribution of family income by decile group | Tabular | Canadian Census Analyser (CHASS) |
| Indigenous Population Data | Population with Registered or Treaty Indian Status per DA | Tabular | Canadian Census Analyser (CHASS) |
| Senior Population Data | Total number of both sexes aged 65 and older per DA | Tabular | Canadian Census Analyser (CHASS) |
| Youth Population Data | Total number of both sexes between the age of 0-24 per DA | Tabular | Canadian Census Analyser (CHASS) |
| Women Population Data | Total number of females between the age of 25-64 per DA | Tabular | Canadian Census Analyser (CHASS) |
| Total Population Data | Total number of people per DA | Tabular | Canadian Census Analyser (CHASS) |
Data Wrangling
Following the data acquisition, the free and low-cost program file was opened in excel and inspected for inconsistencies or errors in the data. Using excel, I created a new field “Population Served” and assigned a value of 0 for low income, 1 for women, 2 for youth, 3 for indigenous and 4 for senior food programs. I carefully assigned values to each food program based on the population that they served and it was to be used to separate the points in ArcGIS. These categories were determined by the common populations that the programs served. I removed programs serving HIV/AID individuals as they are exclusive and require a doctor’s referral. The programs serving Indigenous elders and Chinese seniors were aggregated into the seniors category. The programs that were not specified were included in the low-income category.
I imported the file into ArcGIS and used the “XY Table to Point tool” to create points on the map that would represent the food assistance programs. Using a “select by attribute” query on the “population served” field allowed the points to be separated into subpopulation layers. If “population served” is equal to “_” was used to search and then I exported the selected features into a new layer. This process was repeated for each subpopulation and I had 6 layers in total; one for each subpopulation as well as one for the total food programs.
The rest of the files were then imported into ArcGIS. The Dissemination Area (DA) Boundary file was queried for DAs in Vancouver since the original shapefile was DA for all of Canada. After exporting the Vancouver DAs into a new layer, the census data for each subpopulation were joined using the DAUID field. The data for youth, which is both sexes from ages 0 to 24, had to be calculated because the census categorizes using a different number scheme. Columns containing age data for 0-14, 15-19 and 20-24 were added together to represent the number of youth in each DA.