*Coding in Python A comma-separated value file stocks_data.csv download contains historical data on the Adjusted Closing Price for 3 stocks daily from Jan 2, 2009 to Dec 31,2018. The stocks are Apple (APPL), Microsoft (MSFT) and IBM (IBM). A snippet from the data file looks like the following: Symbol Date Adj. Close MSFT 4/16/2014 35.807358 MSFT 6/21/2010 20.752356 IBM 2/10/2009 68.930023 AAPL 2/14/2018 164.227203 IBM 6/13/2017 141.24379 IBM 12/26/2017 142.835663 MSFT 4/1/2009 15.053272 AAPL 4/17/2009 15.445643
*Coding in Python
A comma-separated value file stocks_data.csv download contains historical data on the Adjusted Closing Price for 3 stocks daily from Jan 2, 2009 to Dec 31,2018. The stocks are Apple (APPL), Microsoft (MSFT) and IBM (IBM).
A snippet from the data file looks like the following:
| Symbol | Date | Adj. Close |
|---|---|---|
| MSFT | 4/16/2014 | 35.807358 |
| MSFT | 6/21/2010 | 20.752356 |
| IBM | 2/10/2009 | 68.930023 |
| AAPL | 2/14/2018 | 164.227203 |
| IBM | 6/13/2017 | 141.24379 |
| IBM | 12/26/2017 | 142.835663 |
| MSFT | 4/1/2009 | 15.053272 |
| AAPL | 4/17/2009 | 15.445643 |
You can see that each row has a symbol, date and closing price, but the stock data is not sorted by symbol, date or price.
Your task has two main parts:
Part I
For each stock, print the following information to the console and to a text file called stock_summary.txt:
- the max price and date it occurs
- the min price and date it occurs
- the average (mean) price
Part 2
Print to the console and append to the output file stock_summary.txt:
- The stock among the 3 with the highest overall closing price and its date
- The stock among the 3 with the lowest overall closing price and its date
Example output looks like the following. Your output must match the format, but replace the placeholders with specific values.
AAPL
----
Max: price date
Min: price date
Ave: mean
IBM
----
Max: price date
Min: price date
Ave: mean
MSFT
----
Max: price date
Min: price date
Ave: mean
Highest: Symbol price date
Lowest: Symbol price date
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