What is the better to pre-process data, MS-Excel or Python/R While handling data, many anomalies occur that might change the results. For example, outliers, missing values, etc. So in this context, what is the better tool to pre process data? A visual tool like MS-Excel or programming tool like R or Python
I mean most of the time it's very much about preference really.

If you want any indication on when to use what:


MS-Excel can only handle so much data. Good for quick analysis of small data but neither good for production or middle to large amounts of data
R great tool for calculating stuff, running models, etc. Pre-Processing is good, lots of libraries to use. Some people don't like using R for production pipelines but I know companies where this is working just fine
Python is a great overall language for pre-processing and creating production worthy data pipelines. So if you want to have a scalable, reusable pre prcessing pipeline this is certainly one of the ways to go


Of course Excel has the lowest learning curve compared to R and Python. The latter ones are similar in that.