Comparing Scarborough and Etobicoke neighbourhoods

Jack's GTA Hike 

View of Toronto from the edge of Etobicoke

Introduction / Business Problem

Jack Murphy is a unique, fictitious character and a successful business owner in the ‘entertainment and adventures’ industry. He has  hiking business across many cities in the US and has decided to open a branch of it in the Greater Toronto Area (GTA). He is oscillating between two boroughs for his new branch: Scarborough and Etobicoke. Jack has certain criteria he would like to ensure are met, and the location that most satisfies these requirements will be his choice to lease in. Jack, and two employees from marketing/advertising, will be reviewing this report, and the accuracy of the story told by the data provided will be needed for advertising the launch of Jack’s GTA Hike. This information may continue to be used in future marketing and advertising campaigns if evidently successful, to continue attracting customers. One criterion he would like met, is the presence of hotels. A variety of hotels would be most preferable, and with a price range to accommodate his customers' financial abilities. Another criterion is the presence of at least one coffee shop that is open early and closes late. Jack believes that this would be most convenient for his customers who may want a coffee in the early mornings and/or who may want a tea when they get back in the evenings. The final criterion is a convenience store. One that supplies ibuprofen for a headache, a toothbrush, a cold drink or a quick snack. 

The customers who sign up for Jack's GTA hike would meet up at the business location where a shuttle bus will be waiting to escort them to one of the hike locations. Customers are responsible for their own accommodation, and morning and evening coffee but Jack’s Hike would provide water, meals and snacks throughout the day. Jack will use the availability of hotels, coffee shops and drugstores near Jack's GTA Hike in his marketing campaign, and therefore the accuracy of the report is of utmost importance. Jack prides himself in his dependability and accuracy in advertising; he aims to under-promise and over-deliver. The accuracy of this report is very important for Jack.

Data Description

The Toronto map was constructed by first creating a DataFrame from https://en.wikipedia.org/wiki/List_of_postal_codes_of_canada:_M. This provided the Toronto postal codes, boroughs and neighbourhoods. I converted this into a dataframe. I then used GeoSpatial coordinates and retrieved longitude and latitude of Toronto postal codes. I combined the two tables and created a new dataframe with all criteria: postal codes, borough, neighbourhoods, longitudes and latitudes.

I got the list of venues in each neighbourhood from Foursquare, and then used my limited number of premium calls for as few coffee shops' hours of operation as possible for my analysis.

Before analyzing the neighbourhoods in Scarborough and Etobicoke, and since they are both boroughs of Toronto, I thought it best to get a clearer idea of all the boroughs of Toronto. After viewing a map of that area, I clustered the neighbourhoods in Etobicoke and in Scarborough respectively, viewed below, by using folium library. 

Etobicoke Map of clustered neighbourhoods

Scarborough Map of clustered neighbourhoods

Data description continued

In Tables 1 and Table 2 below you will notice that the venue category column includes cafe (which I attached as part of the coffee shop numbers below), and pharmacy, grocery store and deli (which I included in the 'stores' venue category below).

After viewing the neighbourhood clusters I created a dataframe to view top venues in each, by using Foursquare. It wasn't very clear if I would easily find hotels so I limited the search, and created a new dataframe with only the selected three venues (hotels, coffee shops, and stores) within the two boroughs, Etobicoke and Scarborough. 

In summary: In each Scarborough and Etobicoke I collected:

- The neighbourhoods of each borough, and into a dataframe and map

- The venues in each neighbourhood and into a dataframe each

- Reduced the dataframes to only include venue categories that can be summarized in: coffee shops, stores and hotels

First round: I collected the data in the venues for Coffee Shops, Stores and Hotels

Second round: I went back to my data collection and edited it to collect coffee shops, cafes, stores and hotels as I noticed in the top venues a few cafes.

Third and fourth rounds: I went back again and again as I reconsidered the numbers of stores I was getting in each location and as compared to a previous output. I concluded that stores could fall under the venue category 'pharmacy' or 'grocery store', 'convenience store' or 'deli'.

The tables below show the results for each borough. 
The venues were divided per category and grouped by neighbourhood, and .count() added as a column to show the total number of venues under this category.

ETOBICOKE:

	Neighbourhood	Venue Category	count
0	Albion Gardens,Beaumond Heights,Humbergate,Jam...	Café	2
1	Albion Gardens,Beaumond Heights,Humbergate,Jam...	Coffee Shop	4
2	Albion Gardens,Beaumond Heights,Humbergate,Jam...	Grocery Store	2
3	Albion Gardens,Beaumond Heights,Humbergate,Jam...	Hotel	6
4	Bloordale Gardens,Eringate,Markland Wood,Old B...	Café	3
5	Bloordale Gardens,Eringate,Markland Wood,Old B...	Coffee Shop	4
6	Bloordale Gardens,Eringate,Markland Wood,Old B...	Grocery Store	4
7	Bloordale Gardens,Eringate,Markland Wood,Old B...	Hotel	1
8	Kingsview Village,Martin Grove Gardens,Richvie...	Café	3
9	Kingsview Village,Martin Grove Gardens,Richvie...	Coffee Shop	6
10	Kingsview Village,Martin Grove Gardens,Richvie...	Grocery Store	4
11	Kingsview Village,Martin Grove Gardens,Richvie...	Hotel	4
12	Northwest	Café	3
13	Northwest	Coffee Shop	7
14	Northwest	Grocery Store	4
15	Northwest	Hotel	6
16	The Kingsway,Montgomery Road,Old Mill North	Café	6
17	The Kingsway,Montgomery Road,Old Mill North	Coffee Shop	4
18	The Kingsway,Montgomery Road,Old Mill North	Grocery Store	3
19	The Kingsway,Montgomery Road,Old Mill North	Hotel	1
20	Westmount	Café	3
21	Westmount	Coffee Shop	4
22	Westmount	Grocery Store	5
23	Westmount	Hotel	4

SCARBOROUGH:

	Neighbourhood	Venue Category	count
0	Agincourt	Coffee Shop	5
1	Agincourt	Hotel	1
2	Agincourt	Pharmacy	4
3	Cedarbrae	Coffee Shop	11
4	Cedarbrae	Grocery Store	1
5	Cedarbrae	Hotel	1
6	Cedarbrae	Pharmacy	3
7	Clarks Corners,Sullivan,Tam O'Shanter	Coffee Shop	5
8	Clarks Corners,Sullivan,Tam O'Shanter	Grocery Store	1
9	Clarks Corners,Sullivan,Tam O'Shanter	Hotel	2
10	Clarks Corners,Sullivan,Tam O'Shanter	Pharmacy	3
11	Cliffcrest,Cliffside,Scarborough Village West	Coffee Shop	7
12	Cliffcrest,Cliffside,Scarborough Village West	Hotel	1
13	Cliffcrest,Cliffside,Scarborough Village West	Pharmacy	2
14	Guildwood,Morningside,West Hill	Coffee Shop	8
15	Guildwood,Morningside,West Hill	Convenience Store	1
16	Guildwood,Morningside,West Hill	Grocery Store	3
17	Guildwood,Morningside,West Hill	Hotel	1
18	Guildwood,Morningside,West Hill	Pharmacy	3
19	Scarborough Village	Coffee Shop	10
20	Scarborough Village	Convenience Store	1
21	Scarborough Village	Grocery Store	4
22	Scarborough Village	Hotel	1
23	Scarborough Village	Pharmacy	8
24	Woburn	Coffee Shop	13
25	Woburn	Convenience Store	1
26	Woburn	Grocery Store	2
27	Woburn	Hotel	1
28	Woburn	Pharmacy	5

Data visualiation

The below two bar graphs summarize the data discussed:  

Results 

Clarks', in Scarborough, is the only neighbourhood in Scarborough that has more than one hotel. Woburn and Scarborough Village have 10 more more coffee shops and 8 or more stores, but both these neighbourhoods have only one hotel each, which means that Jack will not have a price range for his customers. 

The bar graph suggests we look into the Kingsview, Northwest and Westmount neighbourhoods in Etobicoke. The remaining three neighbourhoods do not have the same number of options but in the case that the coffee shop hours or the hotel price range do not meet Jack's criteria, we have an option to consider Albion Gardens.

Scarborough's Clarks' neighbourhood hotels:

Etobicoke's Northwest neighbourhood hotels:

For hours of operation of the coffee shops, I used an external source.

Discussion

Northwest in Etobicoke, and Clark's in Scarborough are the top contenders for each borough. 

Jack only asked for three criteria. Even though there are more stores and coffeeshops in other neighbourhoods in Scarborough, I only calculated coffee shop hours for the neighbourhood that had more than one hotel option. I also found that the hotel in Clarks' had a price range as requested by Jack, so I did not need to revisit.

Etobicoke had many viable neighbourhoods. I chose the top contenders and narrowed it down from there based on the number of coffee shops, stores and the price ranges of hotels. 

Jack had not requested too many options, and given he was keen on either borough I decided to compare the closest, that a neighbourhood came to meeting his criteria, in each of the two boroughs.

Given the limited number of premium calls to Foursquare, it seemed at first that Scarborough m's Clarks' might be the recommended destination. However, I pulled more coffee shops' hours in Northwest, Etobicoke and found a 24 hour Tim Hortons' (coffee shop)! This brought Northwest back into the comparison. 

Conclusion

Clarks' has 5 coffee shops, one of which is known to be open 24 hour, 4 stores and 2 hotels. The hotels range in price between $104 and $135

Northwest has 10 coffee shops, 4 stores and 6 hotels. One of the coffee shops was also found to be 24 hours and the hotel prices range from $112 to $135

While the price range between the two hotels in Clark's Scarborough is $8 more than the price range between the hotels in Northwest, Etobicoke, I proceed to recommend Northwest in Etobicoke as the neighbourhood for Jack's GTA Hike.This neighbourhood provides 3 times as many hotels which range in price just a little less than Clark's hotels, and Northwest has several stores around for customers' day to day needs as well as the 24hour coffee shop so customers can visit as early or as late as they need.

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