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The script was coded using Jupyter notebook.
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Two directory were created within this repository: WeatherPy and VacationPy.
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The OpenWeatherMap API and Google Places API were used.
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WeatherPy folder contains:
WeatherPy.ipynb
script.- An image folder that stores PNG files of 4 scatter plots created and linear regression plots created by
weatherpy
script. weatherpy_cities.csv
is the cities outsput from theweatherpy
script.
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VacationPyfolder contains:
VacationPy.ipynb
script.- An image folder that stores a heatmap and a marker heatmap that were created by
weatherpy
script.
Create a Python script to visualize the weather of 500+ cities across the world of varying distance from the equator. Create a series of scatter plots to showcase the following relationships:
- Temperature (F) vs. Latitude
- Humidity (%) vs. Latitude
- Cloudiness (%) vs. Latitude
- Wind Speed (mph) vs. Latitude
- Northern Hemisphere - Temperature (F) vs. Latitude
- Southern Hemisphere - Temperature (F) vs. Latitude
- Northern Hemisphere - Humidity (%) vs. Latitude
- Southern Hemisphere - Humidity (%) vs. Latitude
- Northern Hemisphere - Cloudiness (%) vs. Latitude
- Southern Hemisphere - Cloudiness (%) vs. Latitude
- Northern Hemisphere - Wind Speed (mph) vs. Latitude
- Southern Hemisphere - Wind Speed (mph) vs. Latitude
Use Jupyter gmaps and the Google Places API to plan future vacations based on weather data.
- Use the result of WeatherPy for finding ideal travel cities for this season. Present the result with a heatmap.
- Find and mark the hotels on the heapmap, see below.