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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 Grade
Step1:  2) What's the current wind speed? How much warmer does it feel than it actually is?
Step2:  3) The first daily forecast is the forecast for today. For the place you decided on up above, how much of the moon is currently visible?
Step3:  4) What's the difference between the high and low temperatures for today?
Step4:  5) Loop through the daily forecast, printing out the next week's worth of predictions. I'd like to know the high temperature for each day, and whether it's hot, warm, or cold, based on what temperatures you think are hot, warm or cold.
Step5:  6) What's the weather looking like for the rest of today in Miami, Florida? I'd like to know the temperature for every hour, and if it's going to have cloud cover of more than 0.5 say "{temperature} and cloudy" instead of just the temperature.
Step6:  7) What was the temperature in Central Park on Christmas Day, 1980? How about 1990? 2000?
Tip
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Python Code:
Make a request from the Forecast.io API for where you were born (or lived, or want to visit!)
import requests
!pip3 install requests
#new york
response = requests.get("https://api.forecast.io/forecast/94bc3fa3628bfad686b10e7054c67f71/40.7141667, -74.0063889")
data = response.json()
print(data)
Explanation: Grade: 6.5 / 7
End of explanation
# TA-COMMENT: (-0.5) You don't give us the current wind speed! 
type(data)
data.keys()
print(data['currently'])
print(data['currently']['temperature']-data['currently']['apparentTemperature'])
Explanation: 2) What's the current wind speed? How much warmer does it feel than it actually is?
End of explanation
print(data['daily'])
type(data['daily'])
data['daily'].keys()
print(data['daily']['data'][0])
type(data['daily']['data'])
print(data['daily']['data'][0]['moonPhase'])
Explanation: 3) The first daily forecast is the forecast for today. For the place you decided on up above, how much of the moon is currently visible?
End of explanation
weather_today = data['daily']['data'][0]
print(weather_today['temperatureMax']-weather_today['temperatureMin'])
Explanation: 4) What's the difference between the high and low temperatures for today?
End of explanation
print(data['daily']['data'])
daily_data = data['daily']['data']
weather_next_week = data['daily']['data']
for weather in weather_next_week:
    print(weather['temperatureMax'])
    if weather['temperatureMax'] > 84:
        print("it's a hot day.")
    elif weather['temperatureMax'] > 74 and weather['temperatureMax'] < 83:
        print("it's a warm day.")
    else:
        print("it's a cold day.")
Explanation: 5) Loop through the daily forecast, printing out the next week's worth of predictions. I'd like to know the high temperature for each day, and whether it's hot, warm, or cold, based on what temperatures you think are hot, warm or cold.
End of explanation
import requests
response = requests.get("https://api.forecast.io/forecast/94bc3fa3628bfad686b10e7054c67f71/25.7738889, -80.1938889")
data = response.json()
print(data['hourly'])
data['hourly'].keys()
data['hourly']['data']
for cloudcover in data['hourly']['data']:
    if cloudcover['cloudCover'] > 0.5:
        print(cloudcover['temperature'], "and cloudy")
    else:
        print(cloudcover['temperature'])
    
Explanation: 6) What's the weather looking like for the rest of today in Miami, Florida? I'd like to know the temperature for every hour, and if it's going to have cloud cover of more than 0.5 say "{temperature} and cloudy" instead of just the temperature.
End of explanation
import requests
response = requests.get("https://api.forecast.io/forecast/94bc3fa3628bfad686b10e7054c67f71/40.7141667, -74.0063889,346550400")
data = response.json()
print(data['currently']['temperature'])
response = requests.get("https://api.forecast.io/forecast/94bc3fa3628bfad686b10e7054c67f71/40.7141667, -74.0063889,662083200")
data = response.json()
print(data['currently']['temperature'])
response = requests.get("https://api.forecast.io/forecast/94bc3fa3628bfad686b10e7054c67f71/40.7141667, -74.0063889,977702400")
data = response.json()
print(data['currently']['temperature'])
Explanation: 7) What was the temperature in Central Park on Christmas Day, 1980? How about 1990? 2000?
Tip: You'll need to use UNIX time, which is the number of seconds since January 1, 1970. Google can help you convert a normal date!
Tip: You'll want to use Forecast.io's "time machine" API at https://developer.forecast.io/docs/v2
End of explanation
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