"I'm having serious trouble figuring out how to start coding for these problems. I'd be more specific, but honestly, I'm horrible with this coding language and I have a hard time remembering things about it. The language being used here is Python, but it uses packages from Anaconda.
For this assignment, we were given multiple files: hw5.ipynb, sun_frame.pkl, sunrise.pkl, sunset.pkl, and a Microsoft Excel file that's called sunrise_sunset. I don't think this particular problem requires code that needs to access those files, but if it does, please let me know and give me your email address so I can send them to you. Additionally, I don't think any packages need to be used here, but it may require NumPy if there are any that need to be used.
I looked through the dataset provided by the link and I believe the problem wants us to organize the month columns so that each sunrise and sunset has a different column, such as Jan_r for sunrise and Jan_s for sunset.
and return it, Use the pd.read csv function: You will need to read the documentation to figure out what arguments to pass to make it work: The data in this file are from http:llaa usno navy mil/cgi- binlaa rstablew pIPID-AA&year-2018&task-O&state-AZ&place-Tucson: You should take look at this link so you understand what the numbers represent: Pandas will try to turn all of the data into ints and floats_ Make sure that read cSV keeps them as strings. The missing data are filled in as NaN's (Not Number), which count as floats_ We'Il fix that in the next function_"