How to Prepare Your Data - KDnuggets

It is rare that you get data in exactly the right form you need it. Often you'll need to create some new variables, rename existing ones, reorder the observations, or just drop registers in order to make data a little easier to work with. This is called data wrangling (or preparation), and it is a key part of Data Science. Most of the time data you have can't be used straight away for your analysis: it will usually require some manipulation and adaptation, especially if you need to aggregate other sources of data to the analysis. In essence, raw data is messy (usually unusable at the start), and you'll need to roll up your sleeves to get to the right place.