While many things will stay the same, our rebrand will result in changes beyond a new name. Any extra column can be closed by closing all the file tabs inside it.We have some wonderful news: RStudio is now Posit! 🎉 The original column in the image contains the “result” window. The selected column (contains first_notebook.R in the image below) is highlighted by a thin, blue, dashed line. Note: You will only have a single Console that will display the output of the column you select (by clicking inside it) and execute. I show below how the RStudio workspace looks like on adding two extra columns. It proves very useful in comparing two or more codes or referring to another code/s. Now, RStudio allows you to similarly configure your workspace window with up to a maximum of three additional source columns (where you can open scripts). It avoids constantly switching among tabs, allowing comparison of several adjacent documents, code, data, etc. Terminal and iTerm2 users might have used the feature of splitting the workspace vertically in separate windows.

Photo by Eric Prouzet on Unsplash 4) Multiple Source Columns in the IDE Workbench Below, you can see the environment pane that displays the content of variables (constants, lists, dictionaries, etc.), python modules, and the user-defined functions (like “square”). Similar to R, the environment pane can now display the contents of Python variables, objects, and functions. ii) Python Support in the Environment Pane The documentation on how exactly to do this is inadequate, though. You can now choose the default Python Interpreter for compiling your Python code, written within the RStudio, from the ones installed on your system. RStudio 1.4 introduces several additions to the Python support: i) Choosing Python Interpreter

I was also jealous of RStudio for its ease of viewing the DataFrames (can conveniently sort and filter things). It took me quite some time to get acquainted with the analysis and visualization of R DataFrames.

I come from a Python background with an affection for Jupyter. The world of data science is mostly bifurcated into Python and R, the former being the diversified leader. Photo by David Clode on Unsplash 2) Improved Python Integration

Python code in rstudio