The weather data is consumed from OpenWeatherMap API.
A sample of ~600 cities is randomly selected with following ranges for latitude(-90, 90) and longitude (-180, 180).
Various scatter plots are drawn to compare the relationship between latitude vs Temparature, Humidity, Cloudiness & Wind Speed.
Various Linear Regression Plots are drawn to compare the weather pattern between Nothern Hemisphere (latitude > 0) and Southern Hemishpere (latitude >= 0)
The restaurant data is consumed from Geoapify API.
A hotel map is drawn for cities filtered for ideal weather condition (Max temp > 18 and Max Temp < 24 and Wind Speed < 5).
- Source Code -
WeatherPy/WeatherPy.ipynb
VacationPy/VacationPy.ipynb - Config - config/api_keys.py
- APIs - OpenWeatherMap API Geoapify API
- Output -
output_data/cities.csv
output_data/Fig1.png
output_data/Fig2.png
output_data/Fig3.png
output_data/Fig4.png
- Obtain API keys for OpenWeather Map & Geoapify APIs
- Open a terminal
- Confirm condo version
conda --version - Confirm jupyter version
jupyter --version - Activate conda environment
conda activate dev - Launch Jupyter Notebook jupyter notebook
- Jupyter Notebook is opened in a browser
- Copy config/api_keys.py.template to config/api_keys.py
- Update config/api_keys.py with API keys for OpenWeather Map & Geoapify APIs
- Open "WeatherPy/WeatherPy.ipynb" file using Jupyter Notebook
- Click on 'Cell > Run All' to run
- Open "VacationPy/VacationPy.ipynb" file using Jupyter Notebook
- Click on 'Cell > Run All' to run
This repo was published for educational purpose only. Copyright 2023 edX Boot Camps LLC. All rights reserved.