1/19/2024 0 Comments Gps tracks to kmz pythonAPI_key = 'Enter your API key here' #enter the key you got from Google. Once you are done, write the following code to calculate the time/duration. Additionally, you use for every project that requires Google APIs. To get the API key, go to Google Distance Matrix API. Let's assume that (-2,0123469, 29,377851) is the origin this is the first entry in our randomly generated data set. The second step to complete our task is to calculate the time or duration of driving from every location of the hundred random locations we created to the origin. Let's import our library that we just installed import googlemaps pip install -upgrade google-auth-oauthlib Through that process, we will need authorization. Since we will have to use Google API, we will need a key. Then, we install simplejson: pip install simplejsonįinally, we install the google-auth-oauthlib. Let's start with gmaps: pip install googlemaps To complete our task, we will need a few things: Google maps library (gmaps), simplejson library, and the Google API key to access the distance matrix. That is the format required by the code we will use later so, we can only comply.ĭata = pd.read_excel(r'data.xlsx', 'data') You'll notice that I added a new column called coordinates that joined both latitude and longitude data in one column. Again, you can get the data here, if you want to use mine. No fancy tools!įirst, we import the pandas library and then load the data. As always, the idea is to achieve this in the simplest way possible. The idea is that we can use these results as variables for further analysis (e.g: think of regression analyses that require distances as variables). We'll achieve this in three simple tasks: (1) importing libraries and loading data (2) calculating durations/times and (3) finally adding the corresponding distances (you can start with distance if you like) to the list. Our task is to make a list of distances (and times) for all the data points (100 data points) we randomly created and used in the previous article. Google API service uses driving distance (although you can choose to use "walking" distance), which means it will calculate the distance based on the actual fastest routes or paths using the actual road network system (where applicable!). The reason we use Google APIs is that it gives you the right/actual distance, as opposed to straight-line distances (known as Euclidian distances) offered by most tools. We will use very simple Python codes together with Google APIs. In this article, we are going to see the quickest - and arguably the simplest - way to get the distance between one specific location and many others, and the time it takes to travel that distance. In our previous article, we mapped 100 data points at random locations in Rwanda.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |