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How Python Helps Accountants Use Excel

Accounting often gets a bad rap from people who don’t work in the profession. Hollywood has frequently portrayed accountants as bookish number crunchers, surrounded by log books and file folders, toiling away with a calculator in their office. But accountants have never fit this image, and accountants in 2021 are immersed in Excel spreadsheets, not file cabinets or cluttered desks full of paper.

While Excel has been a fixture of the greater business community for years, more recently accountants and other business professionals are starting to learn how programming languages can further expand the possibilities of the ever popular spreadsheeting program. Chief among these useful languages is Python -- already beloved for its easy-to-read syntax and quick learning curve, Python has also been proving to be a valuable tool for accountants to manipulate Excel spreadsheets to work more efficiently.

Whether it’s calculating a client’s tax liability, computing interest or dividends on financial investments, or simply organizing income and expenditures to be ready for tax time, Python can automate the tedious parts of accounting and make it easier for accountants to process more clients’ work than ever before. Let’s take a closer look at how Python helps accountants use Excel, and some of the reasons why accountants may want to consider an online Python course to build their own skill set and make their job easier.

Why Is Python Useful For Working With Excel?
While the idea of learning how to code is probably both daunting and seemingly a waste of time to many accountants, Python offers some unique opportunities and appeals for these individuals. Here are some of the reasons why Python is such a good option, even for professionals who haven’t studied coding yet:

Python has simple syntax, which means that the language is as close to reading normal English as a programming language can get. This lets you avoid having to learn an entirely new way of reading and writing code.
Because Python is an open-source language, there are a multitude of libraries and other user-created tools available for free throughout the web. Instead of having to write everything from scratch, there are many out-of-the-box solutions you can use for any project, Excel automation being in that category.
Python is also renowned for its versatility -- it has proven useful for programmers working in a wide array of areas, including tech-intensive fields like data science, machine learning, and the Internet of Things (IoT)
Because Python has been popular among programmers worldwide for decades now, the global programmer community is robust. This means that not only are there the tools we mentioned earlier, but also multiple developer hubs and networking sites where you can get questions answered if you run into trouble.
Most important for accountants, Python can automate recurring tasks. The more often the data manipulation is required, the more value Python automation will provide.
Why Is Python Useful For Accounting Specifically?
Now that you know about the language, you may still not be convinced that taking Python classes online would be worth giving up your valuable free time for. So let’s look at some of the accounting-specific benefits it offers for your time and energy investment.

It Can Help You Work Far More Quickly
Accounts often underestimate the amount of time required for some routine data manipulation tasks on Excel. It is easy to get caught in the minutiae of a V-lookup or Index Match function here and a few text-to columns there, and suddenly find the time has slipped by. The time taken to manipulate the data can also be tedious, which can affect quality of work in a field where precision is critical. With more digitalization, data sets are becoming even more robust and testing Excel’s limits. This makes the benefits of programming even more important, as Python-powered automation can help accountants manipulate giant data sets with much more ease than doing it manually (such as creating tab after tab and bouncing between them to seek out relevant info).

Additionally, program results are easy to reproduce, since coding automatically provides an audit trail within the code itself. Anyone that can read a program you create can understand exactly what you did to the underlying data to manipulate it, even if some data has been deleted. This makes working with clients or colleagues even easier.

Data Integrity
Perhaps you are working on a colleague or client’s Excel file and there are numerous formulas in the workbook. Instead of copying it to your computer or somewhere else in your directory because you don’t want to damage or delete important portions of the file during the data manipulation process, Python can allow you to work on the file without manually opening it. Often, manual processes are where the critical errors occur, so automating this process can add security and a layer of safety to any data you are working with.

Delegation Powers
In years past, accountants were required at the data entry stage of every transaction process. Accountants needed to manually determine the General Ledger to pass double entry for each invoice. Now, even SMEs no longer require a qualified accountant for data entry with the advent of SAP Business One, SAGE and other similar online accounting software. These platforms allow a non-accountant to do data entry, while the accountant concentrates on manipulating and interpreting data.

This shift looks likely to continue in future years, as more non-accountants can focus on data entry and manipulation while accountants do less manipulation - instead preferring to focus on interpretation of data. Python allows accountants the ability to create systems for non-accountants to do these tasks. Subsequently, the non-accountant just has to run a few programs periodically and then the accountant can take it from there.

So What Does This All Mean For Accountants?
The traditional workflow of a modern accountant is evolving. To allow accountants to remain valuable in the future, professionals must not only be able to understand the output of analysed data, but also be able to utilize modern data science tools to produce the information and work with IT to create value for the organisations and clients they serve. In order to gain an appreciation of these tools, knowledge of even the basics of a programming language such as Python is critical.

While accounting programs at major universities have rapidly started to add basic programming tutorials to existing courses that already include a focus on Excel, if you are established in the field, going back to school is probably not a viable option for you.

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