Python coding exercise: please include comments to further my understanding Goal #1: import financial data given into your program provided to you as a CSV formatted text file Use the following data...

Python coding exercise: please include comments to further my understanding

Goal #1: import financial data given into your program provided to you as a CSV formatted text file

Use the following data for testing (the following is only a sample of the data; there are over 4000 rows of data):
*Note: The data you will read in is linear by date (but, non-contiguous due to holidays and weekends,) reflecting a timeline of stock performance in chronological order; however your program should run through the days in the data from the earliest date to the most recent

Write the code in the clearest and most efficient way possible however you need to but need the required function named test_data() that relies on calling other functions you have written. It should have the following characteristics:

def test_data(filename, col, day): """A test function to query the data you loaded into your program. Args: filename: A string for the filename containing the stock data, in CSV format. col: A string of either "date", "open", "high", "low", "close", "volume", or "adj_close" for the column of stock market data to look into. The string arguments MUST be LOWERCASE! day: An integer reflecting the absolute number of the day in the data to look up, e.g. day 1, 15, or 1200 is row 1, 15, or 1200 in the file. Returns: A value selected for the stock on some particular day, in some column col. The returned value *must* be of the appropriate type, such as float, int or str. """

The code will be tested and should give output similar to the following:

>>> val = test_data("AAPL.csv", "close", 25)

>>> val
4.073661
>>> type(val)



>>>

There should be a main function but it shouldn't do anything yet when called:


def main():
pass # Do nothing, just passing through!
if __name__ == '__main__':
main()

goal #2: write the function transact() that should operate as the docstring describes
*note: you need to look up the pricing of a current day and column before calling this function (choose any column you want)

you can use test_data() to lookup pricing to test transact() only in this section

def transact(funds, stocks, qty, price, buy=False, sell=False): """A bookkeeping function to help make stock transactions. Args: funds: An account balance, a float; it is a value of how much money you have, currently. stocks: An int, representing the number of stock you currently own. qty: An int, representing how many stock you wish to buy or sell. price: An float reflecting a price of a single stock. buy: This option parameter, if set to true, will initiate a buy. sell: This option parameter, if set to true, will initiate a sell. Returns: Two values *must* be returned. The first (a float) is the new account balance (funds) as the transaction is completed. The second is the number of stock now owned (an int) after the transaction is complete. Error condition #1: If the `buy` and `sell` keyword parameters are both set to true, or both false. You *must* print an error message, and then return the `funds` and `stocks` parameters unaltered. This is an ambiguous transaction request! Error condition #2: If you buy, or sell without enough funds or stocks to sell, respectively. You *must* print an error message, and then return the `funds` and `stocks` parameters unaltered. This is an ambiguous transaction request! """>>> cash_balance = 1000 >>> stocks_owned = 25 >>> price = test_data("AAPL.csv", "close", 42) >>> price 4.357143 >>> >>> cash_balance, stocks_owned = transact(cash_balance, stocks_owned, 3, price) Ambigious transaction! Can't determine whether to buy or sell. No action performed. >>> print(cash_balance, stocks_owned) 1000 25 >>>

other information:

1. It would be good form to have separate functions to open, read, and parse the CSV file all to be called inside test_data().


2. Do not ask the user for a filename. Unit test your function by calling it inside the interpreter with the filename for your data you want to use.


3. Lists are virtually required here, so make sure you call help(list) in the Python interpreter to know what a list can do for you!


4. You willnot be allowed to edit the CSV file directly. You can only change the data after you read it in using your Python program.


5. The stock data isn’t contiguous in its dates listed. You will have gaps that correspond to weekends or market holidays. Do not count those missing dates as part of your day number counting.