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lease Program in python and leave comments to help explain here is the google drive with the Test.xlsm file: https://drive.google.com/drive/folders/16utzb5_h7yMCN8_13E_JqasfcpykZOYr?usp=sharing The objective is to create a code in Python that can extract the columns highlighted in blue and output them to a .txt file. The code should be able to generate the text file with the columns that are highlighted in blue and store them on a seperate folder. Below shows how the Test.xlsm file looks like as well as how the text file should look like when the code extracts and outputs it. The attached images is how we want to format the text file when/after extracting the columns highlighted in blue. The code should name the output text file according to the sheet name

lease Program in python and leave comments to help explain here is the google drive with the Test.xlsm file: https://drive.google.com/drive/folders/16utzb5_h7yMCN8_13E_JqasfcpykZOYr?usp=sharing The objective is to create a code in Python that can extract the columns highlighted in blue and output them to a .txt file. The code should be able to generate the text file with the columns that are highlighted in blue and store them on a seperate folder. Below shows how the Test.xlsm file looks like as well as how the text file should look like when the code extracts and outputs it. The attached images is how we want to format the text file when/after extracting the columns highlighted in blue. The code should name the output text file according to the sheet name

Database System Concepts
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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Please Program in python and leave comments to help explain

here is the google drive with the Test.xlsm file: https://drive.google.com/drive/folders/16utzb5_h7yMCN8_13E_JqasfcpykZOYr?usp=sharing

The objective is to create a code in Python that can extract the columns highlighted in blue and output them to a .txt file.  The code should be able to generate the text file with the columns that are highlighted in blue and store them on a seperate folder. Below shows how the Test.xlsm file looks like as well as how the text file should look like when the code extracts and outputs it.

The attached images is how we want to format the text file when/after extracting the columns highlighted in blue. The code should name the output text file according to the sheet name " Correct-L.txt " and its header should contain " Band Group Number Time " just so we know where it begins or when the next column is.

*Correct-L.txt - Notepad File Edit Format View Help Band Group Number Time 1000 2000 3000 4452 5698 6521.00 7854.00 8000.00 9000.00 10000.00 11000.00 12000.00 13000.00 14000.00 15000.00 16000.00 17000.00 18000.00 19000.00 20000.00 21000.00 22000.00 23000.00 24000.00 25000.00 26000.00 27000.00 28000.00 29000.00 30000.00 31000.00 32000.00 33000.00 -380.00 Band Group Number Time - 175.56 - 102.5
Transcribed Image Text:*Correct-L.txt - Notepad File Edit Format View Help Band Group Number Time 1000 2000 3000 4452 5698 6521.00 7854.00 8000.00 9000.00 10000.00 11000.00 12000.00 13000.00 14000.00 15000.00 16000.00 17000.00 18000.00 19000.00 20000.00 21000.00 22000.00 23000.00 24000.00 25000.00 26000.00 27000.00 28000.00 29000.00 30000.00 31000.00 32000.00 33000.00 -380.00 Band Group Number Time - 175.56 - 102.5
*Correct-L.txt - Notepad File Edit Format View Band Group Number T - 175.56 - 102.5 - 188.63 - 258.36 -214.21 246.00 258.78 271.56 284.34 297.12 309.90 322.68 335.46 348.24 361.02 373.80 386.58 399.36 412.14 424.92 437.70 450.48 463.26 476.04 488.82 501.60 514.38 527.16 539.94 552.72 565.50 578.28 591.06 603.84 616.6233333 629.4033333 642.1833333
Transcribed Image Text:*Correct-L.txt - Notepad File Edit Format View Band Group Number T - 175.56 - 102.5 - 188.63 - 258.36 -214.21 246.00 258.78 271.56 284.34 297.12 309.90 322.68 335.46 348.24 361.02 373.80 386.58 399.36 412.14 424.92 437.70 450.48 463.26 476.04 488.82 501.60 514.38 527.16 539.94 552.72 565.50 578.28 591.06 603.84 616.6233333 629.4033333 642.1833333
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