*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

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*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:

  1. the max price and date it occurs
  2. the min price and date it occurs
  3. the average (mean) price

Part 2

Print to the console and append to the output file stock_summary.txt:

  1. The stock among the 3 with the highest overall closing price and its date
  2. 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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