Study on the relationship between geolocation and weather condition, using OpenWeatherMap API

A case study using python to collect data from an API request then employing the data to make recommendations based on user input.

Google Maps and OpenWeather APIs used with random geographical points generated; importing into Python and Javascript for transformation; using citypy to find closest towns; plotted on Map; planned round-trip driving route

Utilizing various Python scripts and libraries to visualize the weather in over 500 world cities and displaying the results on a heatmap, after which writing additional code to map hotels (within our given parameters) that would make for an ideal vacation.

Weather Analysis with Python and OpenWeatherMap

Plotted 4 weather variables to understand what the climate is like around the world.

Created a Python script to visualize the weather of 500+ cities across the world of varying distance from the equator by utilizing Python library - citipy, and the OpenWeatherMap API, to create a representative model of weather across world cities.

Travel app development with Python (Scipy, citipy, Pandas, Matplotlib) and APIs

Utilizing Jupyter notebooks and python to create a vacation itinerary of 4 cities based on maximum and minimum temperatures, and display the points on google maps with updated popup markers displaying essential information for each location.

For this project, I created a Python script to visualize the weather of 500+ cities across the world of varying distance from the equator. To accomplish this, I utilized a simple Python library, the OpenWeatherMap API, and a little common sense to create a representative model of weather across world cities.

Analyze & visualize the weather data of 500+ cities across the world. Generate destinations and travel maps using Google Maps Platform APIs.

Python API project: Pandas; CityPy; Python Requests; APIs; JSON Traversals; try/except; Python functions; Matplotlib; Linear Regression; heatmaps, Google Maps API.

For this project, I created a Python script to visualize the weather of 500+ cities across the world of varying distance from the equator. To accomplish this, I utilized a simple Python library, the OpenWeatherMap API, and a little common sense to create a representative model of weather across world cities.

Unit 6 Challenge - Use of Python and APIs

Explored weather data correlations using Python, APIs, and visualizations. Planned vacations based on ideal conditions.

Found weather data for random cities using OpenWeatherMap API and citipy module. Created user input to filter cities list, click on city and see a Hotel name, the city, country and current weather in the city. Created travel itinerary that shows route between four chosen cities using Google Directions API.

Allows clients to input info about location and average weather temperature to identify potential travel locations and nearby hotels. Users are then prompted to choose up to four cities to create a travel itinerary, which is then plotted using the Google Maps API.

Weather and Vacation Analysis: Explore the relationship between latitude and weather variables. Generate scatter plots and regression models. Filter weather data to find cities with desired conditions. Locate nearby hotels for vacation planning. Python, Jupyter Notebook, Pandas, Matplotlib, Citipy, OpenWeatherMap API, Geoapify API.

Perform API calls to OpenWeatherMap to query weather data and plot results.