空間數據科學 (Spatial Data Science)

Designing any product requires a lot of analysis and research. It is also true for designing any building. Before we begin to design any building, we collect information about the location where we are designing, we check the budget, we do research about the background of the target audience and their likes and dislikes.

d esigning任何產品需要大量的分析和研究。 設計任何建筑物也是如此。 在開始設計任何建筑物之前，我們會收集有關設計位置的信息，檢查預算，并研究目標受眾的背景以及他們的好惡。

In designing any space you need to follow some preliminary steps, like budget analysis, client requirements, form & concept development, site analysis, and zoning.

在設計任何空間時，您需要遵循一些初步步驟，例如預算分析，客戶需求，表單和概念開發，站點分析和分區。

Site Analysis is one of the major steps in the pre-designing processes. It involves analysis and evaluating topography, watercourses, trees, manmade features, site boundaries, habitats, wind circulations, connectivity to main roads, streets and pathways, distance to closest facilities or amenities, climatic conditions, and weather patterns.

站點分析是預設計過程中的主要步驟之一。 它涉及分析和評估地形，水道，樹木，人造特征，場地邊界，棲息地，風環流，與主要道路，街道和小徑的連通性，與最近的設施或便利設施的距離，氣候條件和天氣狀況。

In my Architectural Design course, we were given the assignment to design a restaurant in our home town, with very minimum and basic specifications. Having complete freedom to choose the site, concept, form, building materials, and cuisine offered, it required a lot of thinking and creativity.

在我的建筑設計課程中，我們被分配去在我們的家鄉設計一家餐廳，但要有非常基本的要求。 擁有選擇場地，概念，形式，建筑材料和所提供美食的完全自由，這需要大量的思考和創造力。

But it is very difficult to locate the ideal location in such a big city as it also requires a huge amount of research to locate a site because the restaurant should also be successful in business after it starts to function. So instead of choosing my favorite or city’s most popular restaurant’s or cafe’s location as my site, I thought of implementing Data Science for analyzing the data of the restaurants in Pune (my home city, in the western Indian state of Maharashtra) and then using Machine Learning to locate the ideal site.

但是，要在如此大的城市中找到理想的位置非常困難，因為這也需要大量的研究來確定地點，因為餐廳開業后也應該在業務上取得成功。 因此，我沒有選擇我最喜歡的餐廳或城市最受歡迎的餐廳或咖啡館的位置作為我的網站，而是想到了實施數據科學來分析位于印度西部馬哈拉施特拉邦浦那的餐廳的數據，然后使用Machine學習找到理想的地點。

For Data Science you need a large amount of data for the results to be precise, so I collected data about restaurants in Pune through Zomato API’s, population data, pollution data, and keeping in mind the current situation, I even used the geospatial data of COVID-19 cases, from various available sources.

對于數據Scienc?需要大量數據的結果是精確的，所以我收集的關于餐館在Pune通過Zomato API的，人口數據，污染數據的數據，并考慮目前的情況來看，我甚至用了地理空間數據來自各種可用來源的COVID-19案例。

But the COVID-19 data was of not that use as the number of cases and containment zones change every day. So whatever area the Restaurant is in, precautions should be taken.

但是，COVID-19數據的用處不大，因為案件和收容區的數量每天都在變化。 因此，無論餐廳位于哪個區域，都應采取預防措施。

為了進行分析，我使用了以下因素來確定城市中的理想位置： (For the analysis, I used the following factors to locate the ideal location in the city:)

1. Ratings

   等級

2. Votes

   投票數

3. Geolocation of the Restaurant

   餐廳的地理位置

4. Locality / Neighbourhood

   地區/鄰里

5. Price Per Sq. Feet of the Commercial plot of each Neighbourhood

   每平方米價格 每個鄰里的商業用地的腳

6. Cost for two people

   兩個人的費用

7. Type of the Restaurant

   餐廳類型

I observed and analyzed each and every factor for location analysis and prediction, and only considered the factors that were important for me. There can be many more factors but due to data availability constraints, I used the above-mentioned factors only.

我觀察并分析了位置分析和預測的每個因素，只考慮了對我來說很重要的因素。 可能還有更多因素，但是由于數據可用性限制，我僅使用了上述因素。

Locating the ideal site is important but it is not the only factor to be considered in the planning phase, you should also decide what you are going to serve, price of the land or the rent and what should be the ideal cost. These factors should also be analyzed wisely as only locating the site will not get you customers and rating it is also important where you serve what and for what price.

找到理想的地點很重要，但這不是在規劃階段要考慮的唯一因素，您還應該確定要提供的服務，土地或租金的價格以及理想的成本。 還應該對這些因素進行明智的分析，因為僅定位站點不會吸引您的客戶，并且對您在何處以什么價格提供什么樣的價格也很重要。

For example, if the ideal location based on your budget is the “Business and Office” area then Casual Dining would be an appropriate Type and the cost for two people can be more so you can invest more things like formal furniture and menu, if you are planning for a restaurant in an area which has many schools, colleges, and coaching classes then Cafe might be the best alternative as students prefer cheap food and a good place for hanging out. This is just a rough idea or an example, before actual analysis.

例如，如果基于預算的理想地點是“商務和辦公”區域，那么休閑用餐將是一個合適的類型，并且兩個人的費用可能會更高，因此，如果您愿意，您可以投資更多的東西，例如正式的家具和菜單正計劃在有許多學校，學院和教練班的地區開設餐廳，因此咖啡館可能是最好的選擇，因為學生更喜歡便宜的食物和閑逛的好地方。 在實際分析之前，這只是一個粗略的想法或示例。

Popularity and Rating are two different factors for judging a Restaurant, popularity can be seen through the number of votes. When it comes to popular localities Kothrud is the most popular locality for cafes, restaurants, and eateries as it is a densely populated area with several colleges and schools. Kothrud is followed by Viman Nagar and then Hinjawadi. Hinjawadi is a corporate location consisting of a high number of offices.

人氣和等級是判斷餐廳的兩個不同因素，人氣可以通過票數看出。 當涉及到熱門地區時，科德魯德是咖啡館，飯店和餐館最受歡迎的地區，因為它是一個人口稠密的地區，有數所大學和學校。 Kothrud之后是Viman Nagar，然后是Hinjawadi。 辛賈瓦迪(Hinjawadi)是一個由許多辦事處組成的公司地點。

Locality or neighborhood or suburb are all broader terms. This is the list of top 10 specific locations that serve good food as they have a rating of above 4. Rating symbolizes customer satisfaction whereas the number of votes tells us the average footfall of that restaurant.

地方性或鄰居性或郊區性都是廣義的術語。 這是排名最高的10個提供優質食物的特定地點的列表，因為它們的評級高于4。等級象征著客戶的滿意度，而投票數則告訴我們那家餐廳的平均客座率。

This graph tells the average rating of each locality and is ranked accordingly. Kothrud is a popular eatery hub, but in terms of great food and good service, Baner occupies the top position. This can be a crucial factor while deciding the location for a restaurant.

該圖說明了每個地區的平均評分，并進行了相應排名。 科斯魯德(Kuthrud)是受歡迎的餐飲中心，但就美味佳肴和優質服務而言，班納(Barer)排名第一。 在確定餐廳位置時，這可能是至關重要的因素。

Not every type of restaurant works everywhere. Popularity and Rating are major factors for deciding the ideal location but the type of restaurant also plays a crucial role in success. Kothrud might be the most popular locality in Pune but not necessarily every restaurant type will work there. For example, Casual Dining has the most number of votes in Viman Nagar, Dessert Parlour, or Bar has popularity in Baner. The popularity of a type in a specific location depends on the type of audience living there. Baner and Aundh are popular hangout places for a younger generation so Microbrewery, Pub, and Dessert Parlour gain more audience here.

并非每種類型的餐廳到處都有。 人氣和等級是決定理想地點的主要因素，但餐廳的類型在成功中也起著至關重要的作用。 Kothrud可能是浦那最受歡迎的地區，但不一定每種餐廳都可以在那工作。 例如，在Viman Nagar，Dessert Parlour中，Casual Dining的投票最多，而在Baner中，Bar的投票最多。 一種類型在特定位置的受歡迎程度取決于居住在那里的觀眾的類型。 Baner和Aundh是年輕一代的熱門聚會場所，因此Microbrewery，Pub和Dessert Parlour在這里吸引了更多觀眾。

The cost of the food never decides the popularity or rating of a restaurant. But this graph shows an ideal range price depending on the rating. For the rating to be 4.0 < the ideal cost for two people should range from ?600 — ?1200. No restaurant in Pune was ever rated 5.0.

食物的價格永遠不會決定餐廳的受歡迎程度或等級。 但是此圖根據額定值顯示了理想范圍的價格。 評級為4.0 <兩個人的理想費用應為?600-?1200。 浦那沒有餐廳曾被評為5.0。

When locating an ideal restaurant site is done the next time aspect for consideration is the budget. The price of commercial lands is not even close to similar. Wakad has the costliest commercial land, followed by Balewadi. The price of the land does not play any role in deciding the success of the restaurant but budget planning is also important while choosing the location.

當確定理想的餐廳地點時，下一次要考慮的方面是預算。 商業用地的價格甚至沒有接近。 瓦卡德擁有最昂貴的商業用地，其次是巴勒瓦迪 。 土地的價格在決定餐廳的成功與否方面不起作用，但是預算選擇在選擇地點時也很重要。

This gives a general idea of which type of restaurants are popular in Pune. Quick Bites and Casual Dining are popular in Pune, the city being an educational hub as well as the IT hub.

大致了解哪種類型的餐廳在浦那很受歡迎。 快速小吃和休閑餐飲在浦那頗受歡迎，浦那既是教育中心，又是IT中心。

I trained this data in one of the Machine Learning algorithms and deployed the web application. Users can choose the input values as per their choice and the ideal locality based on the input values is predicted. (I have deployed the web application using shiny.io)

我使用一種機器學習算法訓練了這些數據，并部署了Web應用程序。 用戶可以根據自己的選擇選擇輸入值，并且可以預測基于輸入值的理想位置。 (我已經使用Shiny.io部署了Web應用程序)

https://localitypredictor.shinyapps.io/restolocator/

https://localitypredictor.shinyapps.io/restolocator/