WeatherPy

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A Python script that visualizes the weather of 500+ cities across the world of varying distance from the equator. To accomplish this, uses a simple Python library, the OpenWeatherMap API, to create a representative model of weather across world cities.

Prerequisites

This script requires imports of the following:

import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import requests
import time
from pprint import pprint
import datetime
from citipy import citipy

Import API key (must obtain an API key from OpenWeatherMap API)

from api_keys import api_key

Summary

Whether financial, political, or social -- data's true power lies in its ability to answer questions definitively. Using Python requests, APIs, and JSON traversals, this script answers a fundamental question: "What's the weather like as we approach the equator?"

This script builds 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

The notebook does the following:

• Randomly selects at least 500 unique (non-repeat) cities based on latitude and longitude.
• Performs a weather check on each of the cities using a series of successive API calls.
• Includse a print log of each city as it's being processed with the city number and city name.
• Saves both a CSV of all data retrieved and png images for each scatter plot.