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

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

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 a Python script to visualize the weather of over 500 cities of varying distances from the equator, and use the data skills to plan future vacations

This project is a Python-based analysis of weather data and vacation planning using APIs, JSON traversals, and Python libraries. The goal is to visualize weather patterns across cities and assist in vacation decision-making based on specific weather conditions.

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

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.

Demonstrate how to query an API and perform analysis to identify differences in climate near the equator

Including weather data to the travel search criteria through an API call from Open Weather Maps and Google Places

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

Identify potentiel travel destinations and nearby hotels to help create travel itinerary for customers based on their weather preferences.

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

The project’s objective is to improve a travel app to give customers a way to decide their travel destination and ideal hotel based on weather preferences.

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.

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

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.

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

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

Unit 6 Challenge - Use of Python and APIs

Analyzed and visualized the weather data of 500+ cities across the world. Generated destinations and travel maps using Google Maps Platform APIs.