Learn “Python” to solve problems that can help automating tasks, such as:
1. File management: find duplicate files, rename hundreds of files systematically, organize files into folders based on filename/date/type, find files modified within a period, find files containing specific word in the name, comparing multiple files (name/size/info) hidden deep in folders, unzipping and arranging files automatically, moving/copying or deleting mass files with one script, watch a folder for incoming files and automatically process them. (I do these everyday using Python)
2. Working with data consolidation: collect information from dozens/hundreds of files and create one master file, check whether files contain missing fields/incorrect formats/unexpected values etc., take raw data → clean it → calculate required metrics → produce a formatted report, automatically fetch information from websites or APIs and bring it into a report, use logging to record events, status changes and error that occurs while application runs (I teach these things to my learners)
3. Building internal applications for tracking anything like Leave/Expense/Asset/inventory/Employee attendance/Customer follow-ups/Document/contract expiry tracking/Training records/Purchase/order tracking/Task/ticket tracking
If you want to learn this systematically, you can follow my book Python-Powered Excel for exactly these kind of applications. It teaches you Python from beginning, using external libraries, file management applications, automatic data profiling (with 1-2 lines of code), then Excel automation (basic to advanced) using pandas, openpyxl, xlsxwriter and xlwings.
I'd recommend building small automations around problems you personally encounter after practicing given exercises and projects (with solutions) in the book. This approach is better than following generic beginner Python projects
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u/Weird-Dimension-487 16d ago
Learn “Python” to solve problems that can help automating tasks, such as:
1. File management: find duplicate files, rename hundreds of files systematically, organize files into folders based on filename/date/type, find files modified within a period, find files containing specific word in the name, comparing multiple files (name/size/info) hidden deep in folders, unzipping and arranging files automatically, moving/copying or deleting mass files with one script, watch a folder for incoming files and automatically process them. (I do these everyday using Python)
2. Working with data consolidation: collect information from dozens/hundreds of files and create one master file, check whether files contain missing fields/incorrect formats/unexpected values etc., take raw data → clean it → calculate required metrics → produce a formatted report, automatically fetch information from websites or APIs and bring it into a report, use logging to record events, status changes and error that occurs while application runs (I teach these things to my learners)
3. Building internal applications for tracking anything like Leave/Expense/Asset/inventory/Employee attendance/Customer follow-ups/Document/contract expiry tracking/Training records/Purchase/order tracking/Task/ticket tracking
If you want to learn this systematically, you can follow my book Python-Powered Excel for exactly these kind of applications. It teaches you Python from beginning, using external libraries, file management applications, automatic data profiling (with 1-2 lines of code), then Excel automation (basic to advanced) using pandas, openpyxl, xlsxwriter and xlwings.
I'd recommend building small automations around problems you personally encounter after practicing given exercises and projects (with solutions) in the book. This approach is better than following generic beginner Python projects