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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. Then, I used Jupyter notebook, Google Maps, and Google Places API, and created a heat map of humidity. Finally, I created my ideal weather condition on the map, used Google Places API to find the hotel information for each city.

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API-Project

"What's the weather like as we approach the equator?"

Part I - WeatherPy

  • 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.

  • Created a series of scatter plots to show the following relationships:

  • Temperature (F) vs. Latitude

  • Humidity (%) vs. Latitude

  • Cloudiness (%) vs. Latitude

  • Wind Speed (mph) vs. Latitude

** Temperature vs Latitide Graph Image

Temperature-Latitude

  • 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):

  • 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

** I also created multiple linear regression plots.

** The Northern Hemisphere - Temperature (F) vs. Latitude Graph Image

Temp_Latitude_N_Hemisphere

** The Southern Hemisphere - Temperature (F) vs. Latitude Graph Image

Temp_Latitude_S_Hemisphere

Part II - VacationPy

  • Used jupyter-gmaps and the Google Places API.

  • Created a heat map that displayed the humidity for every city from the part I.

** Humidity Heat Map

humidity_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
  • Used Google Places API to find the first hotel for each city located within 5000 meters of my coordinates.

  • 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

hotel_map

About

I created a Python script to visualize the weather of 500+ cities across the world of varying distance from the equator. Then, I used Jupyter notebook, Google Maps, and Google Places API, and created a heat map of humidity. Finally, I created my ideal weather condition on the map, used Google Places API to find the hotel information for each city.

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