A client has requested a script that makes use of geographical location data such as a location’s latitude and longitude. The client also needs to be able to reference data such as street names and ZIP Codes.

Question

In PythonAnywhere, pre-included and importable libraries are referred to as modules. Using the following “Batteries Included” page from the PythonAnywhere documentation, navigate through the list of available modules for some that you believe would help access the necessary data.

Note: You can click on a module name to learn more about it. You may want to search for terms such as “geo” to find modules related to geolocation.
Step 2: Choose Your Libraries

Choose a library you think would work best along with two more libraries that you would consider using for added features or as an alternative to the first choice. It’s always good to have a backup plan in case one technology doesn’t work out the way you had hoped!

Create a new document. Then, for each library, describe the relevant functions it enables. Next, explain why you think each of them would be a useful library to include. Be descriptive in your explanations.
Step 3: Test Your Module!

Time to test it out! Create a new script in PythonAnywhere named librarytest.py.

Navigate to the library’s documentation and perform a function. It doesn’t need to be related to the first prompt directly but, rather, should show that the library was imported and is functioning properly. You may need to research within the library’s documentation a little bit to find sample code to use.

Answer 1

Sure! Here's a detailed response based on your request.

Step 2: Choose Your Libraries

1. Geopy:

   • Relevant Functions:

     • geopy.geocoders.Nominatim: A class that allows you to convert addresses into geographic coordinates (latitude and longitude) and vice versa.
     • geopy.distance: This module provides functions to calculate distances between geographic coordinates.
     • geopy.exc: Handles exceptions related to geocoding.

   • Usefulness: Geopy is a strong choice for dealing with geographical data because it provides easy access to geocoding services, whether it's converting addresses to coordinates or getting addresses from coordinates. The ability to calculate distances between points is also highly beneficial, especially when considering proximity to features like stores or clients. Its simplicity in handling different geocoding providers makes it versatile for various applications.

2. Folium:

   • Relevant Functions:

     • folium.Map: Creates a map centered around specified coordinates.
     • folium.Marker: Allows you to place markers on the map, which can denote specific locations.
     • folium.PolyLine: Used for drawing lines between points, which is useful for visualizing routes or boundaries.

   • Usefulness: Folium is great for visualizing geographical data on interactive maps. By integrating Folium with Geopy, you could generate maps that not only show locations but also visualize routes or areas based on geospatial queries. Its ease of use and powerful visualization capabilities can enhance the client's ability to analyze and present geographical data in engaging ways.

3. GeoPandas:

   • Relevant Functions:

     • GeoDataFrame: Similar to a Pandas DataFrame, but designed specifically for geographic data.
     • read_file: Allows you to read geographic data files, such as shapefiles and GeoJSON, into a GeoDataFrame.
     • plot: Offers ways to easily visualize geographic data using matplotlib.

   • Usefulness: GeoPandas is particularly useful if there is a need to handle more complex geographical data formats and perform analysis on geographical datasets. Its functionality in overlaying geospatial data and combining it with data analysis tools such as Pandas makes it a powerful library. If the project grows in complexity and requires more in-depth spatial analysis, GeoPandas would be an excellent addition.

Step 3: Test Your Module!

Below is an example of how to create the librarytest.py script in PythonAnywhere using Geopy. This script will demonstrate that Geopy is installed and functioning properly.

# librarytest.py
from geopy.geocoders import Nominatim

# Create a geolocator object
geolocator = Nominatim(user_agent="geoapiExercises")

# Test geocoding
location = geolocator.geocode("1600 Amphitheatre Parkway, Mountain View, CA")
print("Address:", location.address)
print("Latitude and Longitude:", (location.latitude, location.longitude))

Instructions for Testing:

1. Create a new file in PythonAnywhere named librarytest.py.
2. Copy the above code snippet into the file.
3. Save the file and run it.

If everything is functioning properly, you should see the address and corresponding latitude and longitude printed on your console. This confirms that the Geopy library was successfully imported and can access geolocation services as intended.