The goal of this project is to gain more practice with file I/O, lists and functions. Background Data mining is the process of sorting through large amounts of data and picking out relevant information. Everyone from financial analysts to scientists use it to extract information from enormous data sets.
These large data sets and the trend of analyzing them has come to be know as “Big Data” http://en.wikipedia.org/wiki/Big_data In this project, we want to do some preliminary data mining of the prices of Apple stock. Your program will calculate the monthly average prices of Apple stock from 1984 to 2013. You will report facts about the monthly highs and lows for this data. Project Specifications 1. A file of Apple’s daily stock’s prices will be given to you, whose name is table.csv (we pulled it off the web).
This file could be opened by notepad or similar text editor, and is delimited by commas. If you open it with Excel, it will show you the data as a spreadsheet. 2. You must implement the following functions:
a) get_input_descriptor() In this function, you are required to repeatedly prompt for the name of an input file until the user enters filename and the file can be opened for input. Return a file descriptor attached to the opened file.
b) get_data_list(file_object, column_number) In this function, you are required to read the file of Apple’s data.
The function is flexible as it can read the data for any column of the data (0 through 6). If you read column 6, you are gathering the data for the “Adjusted Daily Close”. If you read column 5, you are gathering data for the “Volume” that day. The function returns a list that consists of tuples. Each tuple is of the form: (date, column_data), the first value is a string, the second is a float. For example: (‘201302-08′, 474.98) if we were collecting data from column 6.
c) average_data(list_of_tuples) In this function the parameter is a list, the list of tuples generated by get_data_list above. You will average the data for each month, and generate a list of tuples. A tuple here will have the form: (data_avg, date), the first is a float, the second is a string. For example: (2972945.4545454546, ’07:1985’). Note the date in the returned list does not contain a day any more. Because each month has multiple entries the biggest challenge is to collect the data for each month together. One way to is to have variables “current_month” and “current_year” and update them when the month changes.
That is, read lines summing data for the “current_month” until you encounter a new month. Encountering a new month means that you are done summing data for the “current_month” so you can calculate an average for the “current_month”. After calculating the average, you can now set “current_month” to a new month and start summing values for the new “current_month.”
d) main() In this function, you:
• call get_input to get a file descriptor
• prompt for the column to average
• call the get_data function
• call the average_data function
• print the highest 6 averages (for the column selected) and the lowest 6 averages. Print that data with the month-year information.
Deliverables proj04.py – your source code solution (remember to include your section, the date, project number and comments).
1. Please be sure to use the specified file name, ie. “proj04.py”
2. Save a copy of your file in your CSE account disk space (H drive on CSE computers).
3. You will electronically submit a copy of the file using the “handin” program: http://www.cse.msu.edu/handin/webclient List of Files to Download table.csv
1. When reading the input file, you should be careful about the first line which does not contain any data.
2. Remember the split() function, which takes as an argument the character to split on, and returns a LIST of STRINGS. Splitting on commas, i.e. split(‘,’), is useful for csv files.
3. Remember to convert strings to numbers.
4. Since there are so many fields, do some testing (e.g. output some parsed data) to make sure that you get the correct data.
5. The sorted() function should be useful. The sorted() function sorts on the first value in each tuple. my_list = [ (3,2), (1,2), (2,5)] sorted_list = sorted(my_list) # sorted_list will be [(1,2), (2,5), (3,2)], sorts on first value in each tuple
6. Remember to close your files after you have opened them file_obj.close() # Very important to close the file!
7. To create a tuple, remember you just use a comma, so a 2-item tuple could be created like this: my_tuple = (x,y) When you store your date and monthly average, it would probably be easiest to store the date in a string already properly formatted, e.g. “11-2007”.
To append this tuple to a list you can just say my_list.append(my_tuple). Then to access the different items in the tuple you index into the list twice, so for example if you appended the above tuple as the first item in a list: my_list would return x my_list would return y Example Output In : main() Open what file:fred Bad file name, try again Open what file:irving Bad file name, try again Open what file:table.csv
What column:6 Lowest 6 for column 6 Date:08-1985, Value: 1.70 Date:09-1985, Value: 1.77 Date:06-1985, Value: 1.84 Date:10-1985, Value: 1.90 Date:07-1985, Value: 1.93 Date:11-1985, Value: 2.19 Date:05-1985, Value: 2.21 Highest 6 for column 6 Date:09-2012, Value:674.54 Date:08-2012, Value:635.39 Date:10-2012, Value:628.17 Date:04-2012, Value:597.19 Date:07-2012, Value:592.33 Date:03-2012, Value:569.11