MODULE 6
RESOURCES
Jupyter notebook, Numpy, Pandas Library, CitiPy, matplotlib library, Python requests, Google maps API's, SciPy and JSON Traversals IMAGE: obtained from: https://www.pngwing.com/en/free-png-bleiq
OVERVIEW
The purpose of this assignment was to perform API retrieval of metadata, analyze and present visualizations for Jack's PlanMyTrip app and some Beta testers. The first part was the retreival of weather data. The second entailed the implementation of input statements to filter the weather data for four selected, preferred cities. In order to complete the travel itinerary, a travel route was created, as well as a marker layer map for additional information.
RESULTS
In part one, the weather database was created considering the following data:
- latitude and longitude
- max temperature
- percent humidity
- percent cloudiness
- wind speed
- current weather description
Step 1: Weather Data
The figures below (figures 1 to 4) reveal the weather parameters of max temp, humidity, cloudiness and wind speed per latitudes for various cities. This was completed to analyze different weather patterns in various places around the world, in varying hemispheres.
Figure 1: City Latitude and Max temp
Figure 2: City Latitude and Humidity
Figure 3: City Latitude and Cloudiness
Figure 4: City Latitude and Wind Speed
SUMMARY
After the data was analyzed, an itinerary with descriptive information was created, as described below.
Step 2: Create a Customer Travel Destinations Map
In figure 5, a destinations map with markers was created in order to present the potential cities for preferred travel destinations.
Figure 5: WeatherPy Vacation (Search)
Step 3: Create Travel Itinerary Maps
In figure 6, a travel map was created for sample destinations. Because Jack and his Beta tester friend have friends and family in Arizona, California and Mexico, the cities chosen were: Buckeye, Sonoita, Providencia and lastly, for relaxation, Cabo San Lucas. A travel itinerary with weather data per city was included in the map.
Figure 6: WeatherPy Travel map
Figure 7 (below), markers were populated to include hotel names, the current weather conditions and max temp for their preferred planned cities in the USA.
Figure 7: WeatherPy Travel Map with Markers
REFERENCES: BCS, Google, Stackoverflow, GitHub