空间数据科学 (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任何产品需要大量的分析和研究。 设计任何建筑物也是如此。 在开始设计任何建筑物之前，我们会收集有关设计位置的信息，检查预算，并研究目标受众的背景以及他们的好恶。

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

在设计任何空间时，您需要遵循一些初步步骤，例如预算分析，客户需求，表单和概念开发，站点分析和分区。

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.

站点分析是预设计过程中的主要步骤之一。 它涉及分析和评估地形，水道，树木，人造特征，场地边界，栖息地，风环流，与主要道路，街道和小径的连通性，与最近的设施或便利设施的距离，气候条件和天气状况。

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.

在我的建筑设计课程中，我们被分配去在我们的家乡设计一家餐厅，但要有非常基本的要求。 拥有选择场地，概念，形式，建筑材料和所提供美食的完全自由，这需要大量的思考和创造力。

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难，因为这也需要大量的研究来确定地点，因为餐厅开业后也应该在业务上取得成功。 因此，我没有选择我最喜欢的餐厅或城市最受欢迎的餐厅或咖啡馆的位置作为我的网站，而是想到了实施数据科学来分析位于印度西部马哈拉施特拉邦浦那的餐厅的数据，然后使用Machine学习找到理想的地点。

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.

对于数据SciencË需要大量数据的结果是精确的，所以我收集的关于餐馆在Pune通过Zomato API的，人口数据，污染数据的数据，并考虑目前的情况来看，我甚至用了地理空间数据来自各种可用来源的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数据的用处不大，因为案件和收容区的数量每天都在变化。 因此，无论餐厅位于哪个区域，都应采取预防措施。

为了进行分析，我使用了以下因素来确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

   等级

2. Votes

   投票数

3. Geolocation of the Restaurant

   餐厅的地理位置

4. Locality / Neighbourhood

   地区/邻里

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

   每平方米价格 每个邻里的商业用地的脚

6. Cost for two people

   两个人的费用

7. Type of the Restaurant

   餐厅类型

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.

我观察并分析了位置分析和预测的每个因素，只考虑了对我来说很重要的因素。 可能还有更多因素，但是由于数据可用性限制，我仅使用了上述因素。

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.

找到理想的地点很重要，但这不是在规划阶段要考虑的唯一因素，您还应该确定要提供的服务，土地或租金的价格以及理想的成本。 还应该对这些因素进行明智的分析，因为仅定位站点不会吸引您的客户，并且对您在何处以什么价格提供什么样的价格也很重要。

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，如果基于预算的理想地点是“商务和办公”区域，那么休闲用餐将是一个合适的类型，并且两个人的费用可能会更高，因此，如果您愿意，您可以投资更多的东西，例如正式的家具和菜单正计划在有许多学校，学院和教练班的地区开设餐厅，因此咖啡馆可能是最好的选择，因为学生更喜欢便宜的食物和闲逛的好地方。 在实际分析之前，这只是一个粗略的想法或示例。

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.

人气和等级是判断餐厅的两个不同因素，人气可以通过票数看出。 当涉及到热门地区时，科德鲁德是咖啡馆，饭店和餐馆最受欢迎的地区，因为它是一个人口稠密的地区，有数所大学和学校。 Kothrud之后是Viman Nagar，然后是Hinjawadi。 辛贾瓦迪(Hinjawadi)是一个由许多办事处组成的公司地点。

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.

地方性或邻居性或郊区性都是广义的术语。 这是排名最高的10个提供优质食物的特定地点的列表，因为它们的评级高于4。等级象征着客户的满意度，而投票数则告诉我们那家餐厅的平均客座率。

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.

该图说明了每个地区的平均评分，并进行了相应排名。 科斯鲁德(Kuthrud)是受欢迎的餐饮中心，但就美味佳肴和优质服务而言，班纳(Barer)排名第一。 在确定餐厅位置时，这可能是至关重要的因素。

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.

并非每种类型的餐厅到处都有。 人气和等级是决定理想地点的主要因素，但餐厅的类型在成功中也起着至关重要的作用。 Kothrud可能是浦那最受欢迎的地区，但不一定每种餐厅都可以在那工作。 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。 一种类型在特定位置的受欢迎程度取决于居住在那里的观众的类型。 Baner和Aundh是年轻一代的热门聚会场所，因此Microbrewery，Pub和Dessert Parlour在这里吸引了更多观众。

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.

食物的价格永远不会决定餐厅的受欢迎程度或等级。 但是此图根据额定值显示了理想范围的价格。 评级为4.0 <两个人的理想费用应为₹600-₹1200。 浦那没有餐厅曾被评为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.

当确定理想的餐厅地点时，下一次要考虑的方面是预算。 商业用地的价格甚至没有接近。 瓦卡德拥有最昂贵的商业用地，其次是巴勒瓦迪 。 土地的价格在决定餐厅的成功与否方面不起作用，但是预算选择在选择地点时也很重要。

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.

大致了解哪种类型的餐厅在浦那很受欢迎。 快速小吃和休闲餐饮在浦那颇受欢迎，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)

我使用一种机器学习算法训练了这些数据，并部署了Web应用程序。 用户可以根据自己的选择选择输入值，并且可以预测基于输入值的理想位置。 (我已经使用Shiny.io部署了Web应用程序)

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

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