I personnaly rename my datasets with a generic name such as “dat”, others use “df” (for dataframe), “data”, or even “my_data”. Avoid special characters and long names (as you will have to type the name of your dataset several times).

Name: set the name of your data set (default is the name of the file).

Below, the import options you will most likely use: If this is not the case, you can change the import options at the bottom of the window (below the data preview) corresponding to the information you gathered when looking at the raw data. If your data have been correctly imported, you can click on “Import”. No matter what type of file and how you import it, there is one gold standard regarding how datasets are structured: columns correspond to variables, rows correspond to observations (in the broad sense of the term) and each value must have its own cell:įrom this window, you can have a preview of your data, and more importantly, check whether your data seems to have been imported correctly.There are several other ways to import an Excel file (probably even some I am not aware of), but I present the two most simple yet robust ways to import such files.I focus here only on Excel files as it is the most common type of file for a dataset How to import a dataset often depends on the format of the file (Excel, CSV, text, SPSS, Stata, etc.).

I also discuss about the main advantages and inconvenients of both methods. In this article I present two different ways to import an Excel file (i) via the text editor and (ii) in a more “user-friendly” way. As you will most likely use R with your own data, being able to import it into R is crucial for any user. However, it would not be so powerful and useful without the possibility to import datasets into R.

As we have seen in this article on how to install R and RStudio, R is useful for many kind of computational tasks and statistical analyses.

How to import excel file in ms project