"What's the weather like as we approach the equator?"
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I created a Python script to visualize the weather of 500+ cities across the world of varying distance from the equator. I utilized a simple Python library, the OpenWeatherMap API to create a representative model of weather across world cities.
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Created a series of scatter plots to show the following relationships:
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Temperature (F) vs. Latitude
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Humidity (%) vs. Latitude
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Cloudiness (%) vs. Latitude
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Wind Speed (mph) vs. Latitude
** Temperature vs Latitide Graph Image
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Conducted linear regression analyses on each relationship, but separated the data into the Northern Hemisphere (greater than or equal to 0 degrees latitude) and the Southern Hemisphere (less than 0 degrees latitude):
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Northern Hemisphere - Temperature (F) vs. Latitude
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Southern Hemisphere - Temperature (F) vs. Latitude
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Northern Hemisphere - Humidity (%) vs. Latitude
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Southern Hemisphere - Humidity (%) vs. Latitude
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Northern Hemisphere - Cloudiness (%) vs. Latitude
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Southern Hemisphere - Cloudiness (%) vs. Latitude
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Northern Hemisphere - Wind Speed (mph) vs. Latitude
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Southern Hemisphere - Wind Speed (mph) vs. Latitude
** I also created multiple linear regression plots.
** The Northern Hemisphere - Temperature (F) vs. Latitude Graph Image
** The Southern Hemisphere - Temperature (F) vs. Latitude Graph Image
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Used jupyter-gmaps and the Google Places API.
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Created a heat map that displayed the humidity for every city from the part I.
** Humidity Heat Map
- Narrowed down the DataFrame to find my ideal weather condition and dropped any rows that didn't contain all three conditions.
- Narrow down the cities with Max Temp > 65F, < 85F
- Narrow down the cities with Humidity < 55%
- Narrow down the cities with Ideal Wind Speed < 10mph
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Used Google Places API to find the first hotel for each city located within 5000 meters of my coordinates.
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Plotted the hotels on top of the humidity heatmap with each pin containing the Hotel Name, City, and Country.
** My ideal weather condition & Nearby hotel information