{"id":9793,"date":"2018-07-10T15:41:58","date_gmt":"2018-07-10T19:41:58","guid":{"rendered":"http:\/\/studentwork.prattsi.org\/infovis\/?p=9793"},"modified":"2019-01-11T00:09:54","modified_gmt":"2019-01-11T05:09:54","slug":"brooklyn-where-the-restaurants-are","status":"publish","type":"post","link":"https:\/\/studentwork.prattsi.org\/infovis\/labs\/brooklyn-where-the-restaurants-are\/","title":{"rendered":"Brooklyn: Where the Restaurants Are"},"content":{"rendered":"

Introduction<\/h2>\n

Changing demographics due to the rising populations in Brooklyn have had an impact on businesses, in particular, restaurants. The type and number of restaurants in an area can be a good indicator of lifestyle and income of its residents.\u00a0 After recently moving back to Brooklyn, I have noticed an increase and change of cuisine of restaurants just in the past year I have been here.\u00a0 I felt that exploring types and number would provide an interesting viewpoint on the neighborhoods of the borough.<\/p>\n

For inspiration, I looked through the\u00a0NYU Furman Center’s 15th annual State of New York City\u2019s Housing and Neighborhoods in 2015.<\/a>\u00a0This was a special report by the Furman Center on gentrifying neighborhoods in Brooklyn.\u00a0 I used a similar\u00a0map for my visualization of restaurant activity.<\/p>\n

\"Classification<\/a>

Source: NYU Furman Center’s 15th Annual State of New York City\u2019s Housing and Neighborhoods in 2015<\/p><\/div>\n

Process<\/h2>\n

Data Collection<\/strong><\/p>\n

Searching through NYC Open Data<\/a> for information on restaurants,\u00a0I did not find any list of all active restaurants. Instead, I discovered the DOHMH New York City Restaurant Inspection Results dataset and was able to pull information I could use. \u00a0Because any restaurant that is active or opening would need to be inspected, I reasoned that this would be a good source. \u00a0I downloaded the dataset and then used OpenRefine to only include restaurants in Brooklyn. \u00a0The data is not ideal in that some locations are listed more than once, so the data is more of an indicator of restaurant activity than the actual number of businesses.<\/div>\n
<\/div>\n
\n
\"NYC

NYC Open Data (https:\/\/opendata.cityofnewyork.us\/data\/)<\/p><\/div>\n<\/div>\n

<\/div>\n
I also found a dataset with all the restaurants in the city that had sidewalk seating. \u00a0This dataset including square footage and the number of seats along with the location.\u00a0 These were the three values I was most interested in.\u00a0 I refined the data to only show active licenses in Brooklyn since applications and expired ones may not be in use. \u00a0I felt this data provided additional insight into the connection between restaurants and demographics. Not only were most places in a waterfront location as you would expect, but also in higher income and gentrified areas such as Williamsburg and Greenpoint.<\/div>\n
<\/div>\n
\n
\"DOHMH

DOHMH NYC Restaurant Inspection Results Dataset<\/p><\/div>\n<\/div>\n

<\/div>\n
\n
Data Visualization<\/strong><\/div>\n
<\/div>\n
Using the first dataset with the health inspections, I was able to create a map that displayed density of activity by zip code. \u00a0I also created a bar graph that displayed the popularity of cuisines from this same dataset. Since the type of cuisine was random and sometimes granular, I grouped several values together in Tableau. \u00a0For example, under the label \u201cLatin\u201d, I have included Brazilian and Peruvian restaurants.\u00a0 Because both of these charts are generated by the same data, clicking on one zip code in the density map will update the cuisines bar chart, illustrating which ones are more popular in that zip code.<\/div>\n
<\/div>\n
The sidewalk seating map shows the location and indicates the number of seats with the marker size.\u00a0 The darker the color the greater the square footage. Because the circle markers are outlines, you can easily see the density in certain areas. \u00a0Being generated by a different dataset, this map does not react to changes in the other two.<\/div>\n
<\/div>\n<\/div>\n
\n
Tools<\/strong><\/div>\n
OpenRefine.org<\/a>\u00a0– Editing datasets<\/div>\n
Tableau Public – Creating data visualizations<\/div>\n
Evernote.com<\/a>\u00a0– Saving notes and links<\/div>\n
<\/div>\n
Sources<\/strong><\/div>\n
NYC Open Data<\/a> – Collection of NYC datasets (https:\/\/opendata.cityofnewyork.us\/data\/<\/a>)<\/div>\n
DOHMH New York City Restaurant Inspection Results (July 3, 2018)\u00a0\u00a0 \u00a0(https:\/\/data.cityofnewyork.us\/Health\/DOHMH-New-York-City-Restaurant-Inspection-Results\/43nn-pn8j<\/a>)<\/div>\n
Sidewalk Caf\u00e9 Licenses and Applications (July 3, 2018) (https:\/\/data.cityofnewyork.us\/Business\/Sidewalk-Caf-Licenses-and-Applications\/qcdj-rwhu<\/a>)<\/div>\n<\/div>\n
<\/div>\n
\n

Results<\/h2>\n
\n
Tableau Public Dashboard & Workbook<\/strong><\/div>\n
Brooklyn: Where the Restaurants Are<\/a><\/div>\n
<\/div>\n<\/div>\n<\/div>\n
\n
\"Brooklyn:<\/a>

Source: NYC Open Data. Visualizations based on the DOHMH NYC Restaurant Inspection Results and Sidewalk Caf\u00e9 Licenses datasets from the NYC Open Data site.<\/p><\/div>\n<\/div>\n

\n
A quick view of the dashboard gives a clear idea of where the most restaurants are located along with additional information on popular cuisines and sidewalk seating. It features the map of inspection activity by zip code along with a bar graph of the cuisines to the right. Additionally, there is a sidewalk seating map to the right below the bar graph. I felt the sidewalk data was a supporting element in relation to the activity. \u00a0I chose not to include my graph on the number of inspections increasing over time since my other charts were not historic. Of course, the overall number of restaurant inspections increasing\u00a0makes perfect sense considering the rise in population, incomes, and\u00a0gentrification.<\/div>\n
<\/div>\n

Future Considerations<\/h2>\n
I would have liked to show a greater relationship between the changes in businesses and gentrification. \u00a0This could have been done between datasets that include zip codes. \u00a0Using the zip as the link between tables, many more relationships could be discovered. \u00a0Many datasets use districts rather than zip codes which makes creating connections between them more challenging.<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

Introduction Changing demographics due to the rising populations in Brooklyn have had an impact on businesses, in particular, restaurants. The type and number of restaurants in an area can be a good indicator of lifestyle and income of its residents.\u00a0 After recently moving back to Brooklyn, I have noticed an increase and change of cuisine…<\/p>\n","protected":false},"author":533,"featured_media":9794,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[340,149],"tags":[194,197,195,196,123,156],"coauthors":[348],"class_list":["post-9793","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-charts","category-labs","tag-openrefine-tableaupublic","tag-brooklyn","tag-nyc-open-data","tag-restaurants","tag-tableau-public","tag-tableaupublic"],"jetpack_featured_media_url":"https:\/\/i0.wp.com\/studentwork.prattsi.org\/infovis\/wp-content\/uploads\/sites\/3\/2018\/07\/NYUFurmanCenter_Gentrify.jpg?fit=696%2C699&ssl=1","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/paBdcV-2xX","_links":{"self":[{"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/posts\/9793","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/users\/533"}],"replies":[{"embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/comments?post=9793"}],"version-history":[{"count":3,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/posts\/9793\/revisions"}],"predecessor-version":[{"id":9811,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/posts\/9793\/revisions\/9811"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/media\/9794"}],"wp:attachment":[{"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/media?parent=9793"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/categories?post=9793"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/tags?post=9793"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/coauthors?post=9793"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}