The goal of this project is to utilize the CitiPy Python Library and the OpenWeatherMap API to create a representative model of weather across world cities.

Used Citipy and OpenWeatherMap API to create a representative model of weather across world cities. Applied jupyter-gmaps and the Google Places API to anaylze and plot ideal vacation locations. 🌴

The project was an introduction to using APIs and parsing their responses using python and PANDAS and Matplotlib libraries.

The aim of this project is display travel-related information, such weather data and accommodation data, on a map.

Using Python API calls to get ideal Vacation Spot

Created a Python script to visualize the weather of 500+ cities across the world of varying distance from the equator.

Practice exercise from Georgia Tech Data Analytics Boot Camp. Analysis, graphs & maps based on random latitudes/longitudes from Python Citipy library and Open Weather Map API.

An analysis of changes of weather patterns from around the world using python and APIs.

A closer look of weather conditions in 500+ cities across the world are evaluated relative to their distance from the equator. Citipy API and Python is used to collect and evaluate the data. Project fulfilled for Georgia Tech Data Science and Analytics certificate.

An exercise on getting the weather data of about 600 cities using OpenWeatherMap API, filtering the data and creating a heatmap for the cities that fulfil certain criteria.

Collecting data for travel tech company on predicting best time of year to plan vacations. Weather map API with Google Maps, Citipy module, and MatPlotlib.

Analysis of global weather patterns for vacation planning using citipy, OpenWeather API, and Google Maps API.

Finding an ideal vacation destination using OpenWeatherMap API.

Web application to show weather distribution in 500+ randomly generated cities across the world

Creating a Python script to visualize the weather of 500+ cities across the world of varying distance from the equator. The idea is to create a representative model of weather across world cities.

Preapare a travel app. Add weather information and filter available data to identify potential travel destinations and nearby hotels

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.

Map visualisations of cities and accommodation across 500 random locations, along with weather conditions and their relationship to latitude.