PavanKumpatalModuleSevenProject

# My name is Pavan Kumpatla and today's date is November 23, 2021. # This is Mod 7 Project # ...

# [] create The Weather !curl https://raw.githubusercontent.com/MicrosoftLearning/intropython/master/world_temp_mean.csv -o mean_temp.txt # imports city_file = open('mean_temp.txt', 'a+') # opens mean_temp.txt in a+ mode city_file.write('Rio de Janeiro,Brazil,30.0,18.0') # writes city_file.seek(0) # points to beginning headings = city_file.readline() # reads line heading = headings.split(',') # splits headings with "," city_temp = city_file.readline() # reads lines and stores it while city_temp: # while city_temp city = city_temp.split(',') # splits city_temp with "," print(heading[0].title(), 'of', city[0], heading[2], 'is', city[2], 'Celcius') # prints city_temp = city_file.readline() # reads line, stores city_file.close() # closes

  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                 Dload  Upload   Total   Spent    Left  Speed
100   222  100   222    0     0  15857      0 --:--:-- --:--:-- --:--:-- 15857
City of Beijing month ave: highest high is 30.9 Celcius
City of Cairo month ave: highest high is 34.7 Celcius
City of London month ave: highest high is 23.5 Celcius
City of Nairobi month ave: highest high is 26.3 Celcius
City of New York City month ave: highest high is 28.9 Celcius
City of Sydney month ave: highest high is 26.5 Celcius
City of Tokyo month ave: highest high is 30.8 Celcius
City of Rio de Janeiro month ave: highest high is 30.0 Celcius