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

Retrieve weather data using APIs, clean data with pandas, plot data onto a google map, and create a travel itinerary for users.

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

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

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

Using multiple API sources, create an app that allows users to filter through random locations based on their temperature range choices.

Analyze & visualize weather data. Generate destinations and travel maps using Google Maps Platform APIs.

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.

This Project analyzes top vacation cities based on weather data from Open Weather's API and is visualized using Google Map's 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.

Created a vacation itinerary across four different cities in the same country based on weather conditions. The itinerary was visualized as a map. Pins and markers were added with basic details for each city.

Unit 6 Challenge - Use of Python and APIs

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

A Python script to visualize data points of the weather for 500+ cities across the world of varying distance from the equator.

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.

Create an app that gives users an itinerary based on their weather preferences.