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Why use Python instead of Excel?

March 9, 2019

Nowadays professional teams are in big business. They always come to face a lot of data, and that data requires a lot of analytics at every step. From managing the day to day activities, to engage with the customers, to put the winning product on the market, to perform customer behavior analytics. One of the most common tools used by business analysts is Excel, or more generally, spreadsheets.

These tools allow an analyst to visually interact with data, to perform simple and somewhat complex analysis, and to visualize the data. The analytic result they produce can provide many benefits. But the fact is they can't simplify some analysis and for this spreadsheets are not ideal for modern day analytics. Modern day analytics mostly relies on programming and working with Big data and their analysis Python is very popular and useful to the modern day Data Analysts.

Now we'll try to explore why it's better to more rely on programming language like Python instead of using tradition spreadsheets like Excel.

Imagine we are trying to trace an analysis through a litany of spreadsheets where data had been cut and pasted between different worksheets and the details are not documented. Hereafter, we will use a notebook, which allows a combination of the documentation, analysis code, and the analysis results including visualizations to be combined into a single cohesive package that can be shared, reused, and can be informed to others of exactly what was done.

Excel. It's always everywhere in the business world. And that's because it makes it easy to process data in a visually intuitive manner. Yet there's problems with using Excel, not the least of which is that it isn't good at dealing with lots of data. But there's other reasons as well.

So what are the main points? And why we should want to think about using Python in particular, rather than Excel? Of course the blog starts with the obligatory picture of a Python.

So, the main point about using Python rather than Excel is this idea that Excel loses the audit trail. There's no way to know for sure what exactly was done in a spreadsheet when people have specified cells, or cut and pasted data. Instead when you process data with a code, you can see every line of that code.

Now we could choose other languages but Python has many benefits. One thing this open-sourced programming language is enriched with versatile libraries and this language is also easier to learn than other scripting language. Also we have big community of Python enthusiasts who are always there for us.

Another widely used language for mainly statistical analysis is R. Like R, Python is also a High-Level language means it's interpreted. It's also said that Python is better for navigating through network, manipulating files and talking to the computer operating system so we can automate our programs. Python uses the indentation of each line of code to define where loops and functions start and end, so it's straightforward to read and error-check.