# Noemi Cabrera # 15 November 2021 # In this project, I practiced using the different methods I learned to open, close, convert # into a list, move the pointer, and write in a imported file. I created a weather program # combining these methods that imports and opens a file, appends additional data to the file, # and reads from the file to displays each city name and month average high temperature in Celsius. # One small difficulty I had was that an 'out of index' error displayed. After checking # everything in the code and checked if the new line for Rio de Janeiro was written in the file, # I realized the "\n" formatting character I placed in the line was causing the error. So, I # removed the '\n' when I wrote the text to the file.
# In this code, I created a program that displays the month average high temperature in Celsius of specific # cities located in a file. A file is imported using the curl statement. The file is named mean_temp. The # mean_temp.txt file is opened in 'a+' mode with the open() metho and then new text is added to it using # the .write() method. The pointer is set to the beginning of the file using seek(0).Then, the file is read line by # line with the readline() method. The file contents are converted into a list of items using the split() method, # which is stored in the headings variable. The headings list is printed. Lastly, the mean_temp file is read line # by line each saved as a string. Then, a while loop is used to display each city name and month average high # temperature in Celsius. To do this, the temp_list was created with the strings of the mean_temp file. The file is closed. #  create The Weather !curl https://raw.githubusercontent.com/MicrosoftLearning/intropython/master/world_temp_mean.csv -o mean_temp.txt mean_file = open("mean_temp.txt","a+") mean_file.write("Rio de Janeiro,Brazil,30.0,18.0") mean_file.seek(0) headings = mean_file.readline().split(",") print(headings,"\n") city_temp = mean_file.readline() while city_temp: temp_list = city_temp.split(',') print(headings + " for " + temp_list + " is " + temp_list + " Celsius") city_temp = mean_file.readline() mean_file.close()
% Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 222 100 222 0 0 1804 0 --:--:-- --:--:-- --:--:-- 1804 ['city', 'country', 'month ave: highest high', 'month ave: lowest low\n'] month ave: highest high for Beijing is 30.9 Celsius month ave: highest high for Cairo is 34.7 Celsius month ave: highest high for London is 23.5 Celsius month ave: highest high for Nairobi is 26.3 Celsius month ave: highest high for New York City is 28.9 Celsius month ave: highest high for Sydney is 26.5 Celsius month ave: highest high for Tokyo is 30.8 Celsius month ave: highest high for Rio de Janeiro is 30.0 Celsius