The type of data that you are working with is a very large piece of data science. It must precede most of your analysis because the type of data you have impacts the type of analysis that is even possible!
Whenever you are faced with a new dataset, the first three questions you should ask about it are the following:
Is the data organized or unorganized?
For example, does our data exist in a nice, clean row/column structure?
Is each column quantitative or qualitative?
For example, are the values numbers, strings, or do they represent quantities?
At what level of data is each column?
For example, are the values at the nominal, ordinal, interval, or ratio level?
The answers to these questions will not only impact your knowledge of the data at the end, but will also dictate the next steps of your analysis. They will dictate the types of graphs you are able to use and how you interpret them in your upcoming data models. Sometimes we will have to convert from one level to another in order to gain...