Blog Post Find your desired community neighborhood in a city of Germany - RuikunLi/Capstone_Coursera GitHub Wiki

Table of contents

Introduction

When you live in Germany and want to explore your neighborhoods or you would like to move to a desired neighborhood in a city of Germany. For example, you are a non-Aachener who will work in Aachen next year and want to find your desired neighborhoods based on different venues. You can enter your priority of venues of a specific city and get the area with zip code which macths to your demand.

target audience

The people who live in germany and want to explore the neighborhood or move to another neighborhood or move to a new city.

Data

Description of the Data:¶

The following data is required to answer the issues of the problem:

  • List of Zipcode with corresponde geodata (latitud and longitud), population of the area.
  • Venues and its location of the city.
  • Foursquare API credential.
  • keyword venues from Foursquare API. You can find a list here.

How the data will be used to solve the problem

The data will be used as follows:

  • Use Geojson data of Germany to locate the centroid of a zip code area.
  • Use Foursquare and geopy data get desired venues
  • Addresses from locations will be converted to geodata( lat, long) using Geopy-distance and Nominatim.
  • Cluster the venues based on their location.
  • Create a list with keyword venues.
  • Use Folium to plot the data.

Methodology

There is one main method find_desired_community_germany to find desired community in the selected city with selected keyword venues.

find_desired_community_germany(city, foursquare_credential, keywordlist,limit=100, radius=500)
 
    @Param
                city, city name;
                foursquare_credential, list like, [CLIENT_ID,CLIENT_SECRET];
                keywordlist, list like, include the keyworde of interested venues, such as Supermarket, Bus Stop;
                limit, int, limit of foursquare searched venues of a point;
                radius, in meters.
    @Return
        a folium map of desired community.

And two subfunction for the ind_desired_community_germany.

  • getNearbyVenues(names, latitudes, longitudes, LIMIT=100, radius=500) to get the nearby venues.
  • find_desired_venues(keywordlist, City_venues) to find the desired venues with keywords in the keywordlist.

Result and Discussion

How to interpret the map.

  • colored maker shows the different venues cluster based on the location.
  • Polygon shows a desired community of a convex hull of a cluster.
  • Circle shows a desired community of a centroid of a convex hull based on customer given radius in meter.
  • Marker's popup is the venue name and its category.
  • Polygon and Circle's popup is the contained keyword venue of this community.

There are three case studies with different cities and different venues.

Case Study I

As I am study at RWTH Aachen of Germany, I would like to find my desired community in Aachen. As a Student, my selected keywords would be 'Supermarket', 'Restaurant', 'Café', 'Bus' etc. Aachen

Case Study II

My girlfriend and I lived in Köln an we love this city. So we would like to know if we move back to Köln in the future, where is our desired community. Our selected keywords would be 'Movie', 'Supermarket', 'Restaurant', 'Pharmacy', etc. Koeln

Case Study III

I lived in Duisburg for a while and a friend of mine would like to move to Duisburg. He study very hard therefore he want to find the community which may contain college facilities.The selected keywords would be 'Supermarket', 'College', 'Café', 'Zoo', etc. Duisburg

Conclusion

Purpose of this project is to find the desired community/neighborhood of a city in Germany. By given selected keywords of venues to explore venues from Foursquare API, then cluster them based on their location, draw convex hull and polygon to show the desired community/neighborhood.

Future version would add a filter of keywords, for example I want to filter the desired community which fulfill my requirements(all keywords contained).