Prepping Your Data Set Best Practicesīefore you start thinking about how to load your Excel files and spreadsheets into R, you need to first make sure that your data is well prepared to be imported. Tip : if you are a beginning R programmer, you can go through our tutorial, which not only explains how to import and manipulate Quandl data sets, but also provides you with interactive exercises to slowly submerge you into Quandl.
It offers millions of free and open financial, economic, and social datasets and might prove to be an easier option, especially for beginners who are not yet familiar with the field of data analysis. Another option is Quandl, a search engine for numerical data.For this tutorial, make sure to save whatever data that you find on the Internet has a file extension that can be opened with Excel. The following list can be a useful help when you’re not sure where to find data on the Internet.
The latter can be somewhat challenging if you intend to analyze your data thoroughly after importing, as you will need to get a hold on a dataset that is as complete and qualitative as possible!
There are basically two options to do this: either you have a dataset of your own, or you download one from the Internet. As a first step, it is, therefore, a good idea to have a data set on your personal computer. What this tutorial eventually comes down to is data: you want to import it fast and efficiently to R.
It is an easily accessible tool for organizing, analyzing and storing data in tables and has widespread use in many different application fields all over the world. As most of you know, Excel is a spreadsheet application developed by Microsoft.