The purpose of this project is to collect, analyze and visualize weather data across cities worldwide and to provide travelers with a tool that will allow them to determine their travel destination based on weather conditions.
This project analyzes top vacation cities based on weather data from Open Weather's API and is visualized using Google Map's API.
Maps visualizing relationship between weather data and hotel locations
Analysis using Jupyter Notebook, CityPy, Pandas Dataframe, Matplotlibs, Jupyter GMaps, and Google APIs.
Top vacation cities are analyzed using data from Open Weather API. It is then visualized using Google Maps API.
I used Python, Jupyter Notebook and the city PI module to get the cities for more than 700 random latitudes and longitudes then I requested on the open weather map API and retrieve the JSON weather data from these cities. I then added the weather data to the Panda’s dataframe. From there I used Matplotlib to create a series of scatter plots to s…
Use APIs to visualize weather data
Using OpenWeatherMap API, retrieve the JSON weather data from different cities. Using Matplotlib, create a series of scatter plots showing relationship between the latitude and a variety of weather parameters for over 1500 cities around the world. Perform statistical calculations on the weather parameters using linear regression to predict futur…
API and Weather Data visualization: Data Visualization based on weather data, vacation itinerary and vacation search
This project is in two parts. First, WeatherPy visualizes the weather of 500+ cities across the world of varying distances from the equator, using Python script, CityPy, and OpenWeatherMap APIs. The second part, VacationPy, uses Jupiter-Gmaps and the Google Places API to create a heatmap and filter down cities.
Analyze World Weather and Create a Travel Itinerary using Pandas, Matplotlib, SciPy statistics., Citipy, Weather Map API, Gmaps API and Jupyter Notebook.
Python-based NumPy & SciPy Statistical Analysis of Latitude Position vs Weather Performed on a 500+ City Data Set Created by Python CityPy & OpenWeatherMap API Representative of Weather Worldwide
Visualizing weather and Gmaps locations using a live API
Python API Requests & JSON Traversals Visualizing the Weather of 500+ World Cities using OpenWeatherMap API
Analysis using Jupyter Notebook, CityPy, Pandas Dataframe, Matplotlibs, Jupyter GMaps, and Google APIs.
Dashboard that contains visualizations of weather data from approximately 500 cities around the world.
Analyzing weather patterns with respect to latitude.
This project is in two parts. The first part (WeatherPy) visualizes the weather of 500+ cities across the world of varying distance from the equator, using Python script, CityPy and OpenWeatherMap APIs. The second part (VacationPy) uses jupyter-gmaps and the Google Places API to create a heatmap of these cities, filter down to the cities with an…
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