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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:
 1) Make a request from the Forecast.io API for where you were born (or lived, or want to visit!).
Tip
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?
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Python Code:
#api KEY =  c9d64e80aa02ca113562a075e57256d7
https://api.forecast.io/forecast/c9d64e80aa02ca113562a075e57256d7/10.4806,66.9036
import requests
response = requests.get("https://api.forecast.io/forecast/c9d64e80aa02ca113562a075e57256d7/10.4806,66.9036")
forecast = response.json()
print(forecast.keys())
print(forecast['timezone'])
print(forecast['latitude'],forecast['longitude'] )
Explanation: 1) Make a request from the Forecast.io API for where you were born (or lived, or want to visit!).
Tip: Once you've imported the JSON into a variable, check the timezone's name to make sure it seems like it got the right part of the world! Tip 2: How is north vs. south and east vs. west latitude/longitude represented? Is it the normal North/South/East/West?
Graded = 6/7
End of explanation
print(forecast['currently'])
print("The current wind speed is", forecast['currently']['windSpeed'], "miles per hour")
print("Right know in Caracas the temperature feels like",forecast['currently']['apparentTemperature'])
print("Right know in Caracas the temperature is",forecast['currently']['temperature'])
print("It feels about", forecast['currently']['apparentTemperature']-forecast['currently']['temperature'], "degrees warmer than the actual temperature")
Explanation: 2) What's the current wind speed? How much warmer does it feel than it actually is?
End of explanation
print(forecast['daily'].keys())
forecast['daily']['data']
print(type(forecast['daily']['data']))
print(forecast['daily']['data'][0])
first_daily_forecast = forecast['daily']['data']
for item in first_daily_forecast[:1]: 
    print("In the first daily forecast", item['moonPhase'], "of the moon is currently visible")
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
for item in first_daily_forecast[:1]:
    print("The min temperature for the day is:", item['temperatureMin'], "degrees Fahrenheit")
    print("The max temperature for the day is:", item['temperatureMax'], "degrees Fahrenheit")
    print("The difference between min and max temperatures is", item['temperatureMax']-item['temperatureMin'],"degrees Fahrenheit" )
Explanation: 4) What's the difference between the high and low temperatures for today?
End of explanation
for item in first_daily_forecast:
    if item['temperatureMax'] > 80:
        print("The high temperature for today is", item['temperatureMax'],"degrees Farenheit" )
        print("It is going to be hot.")
    else:
        print("The high temperature for today is", item['temperatureMax'],"degrees Farenheit" )
        print("It won't be as hot as it normally is, luckily.")
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/c9d64e80aa02ca113562a075e57256d7/25.7742700,-80.1936600")
miami_forecast = response.json()
print(forecast_miami.keys())
print(type(miami_forecast['hourly']))
print(miami_forecast['hourly'].keys())
print(miami_forecast['hourly']['data'][0])
miami_forecast_today = miami_forecast['hourly']['data']
print("Here is an estimation of how the weather in Miami will look within the next few hours")
for item in forecast_miami_today:
    if item['cloudCover'] > 0.5:
        print("It will be", item['temperature'],"degrees Farenheit and overcast.")
    else:
        print("It will be", item['temperature'], "degrees Farenheit")
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/c9d64e80aa02ca113562a075e57256d7/40.7829,73.9654,346550400")
forecast_1980 = response.json()
print(forecast_1980.keys())
print(1980_forecast['daily'].keys())
print(forecast_1980['daily']['data'])
christmas_temp_1980 = forecast_1980['daily']['data']
for item in christmas_temp_1980:
    print("On Christmas Day, 1980, temperatures ranged between", item['temperatureMax'], "and", item['temperatureMin'], "degrees Farenheit at Central Park")
import requests
response = requests.get("https://api.forecast.io/forecast/c9d64e80aa02ca113562a075e57256d7/40.7829,73.9654,662083200")
forecast_1990 = response.json()
print(forecast_1990.keys())
christmas_temp_1990 = 1990_forecast['daily']['data']
for item in christmas_temp_1990:
    print("On Christmas Day, 1990, temperatures ranged between", item['temperatureMax'], "and", item['temperatureMin'], "degrees Farenheit at Central Park")
import requests
response = requests.get("https://api.forecast.io/forecast/c9d64e80aa02ca113562a075e57256d7/40.7829,73.9654,977702400")
forecast_2000 = response.json()
print(forecast_2000.keys())
christmas_temp_2000 = forecast_2000['daily']['data']
for item in christmas_temp_2000:
    print("On Christmas Day, 2000, temperatures ranged between", item['temperatureMax'], "and", item['temperatureMin'], "degrees Farenheit at Central Park")
Explanation: 7) What was the temperature in Central Park on Christmas Day, 1980? How about 1990? 2000?
End of explanation
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