Comparison with IPyStata¶
stata_kernel
is faster with larger datasets¶
stata_kernel
takes a different approach to communication with Stata. With IPyStata
on macOS and Linux, to run each segment of code
 Your data has to be moved from Python to Stata
 Run the commands in Stata
 Return the data to Python to save it for the next command
This process is prohibitive with larger amounts of data. In contrast, stata_kernel
controls Stata directly, so it generally is no slower than using the Stata program itself.
stata_kernel
provides more features¶
stata_kernel
is a pure Jupyter kernel, whereas IPyStata is a Jupyter magic within the Python kernel. This means that with stata_kernel
 You don't have to include
%%stata
at the beginning of every cell.  You get features like autocompletion and being able to use
;
as a delimiter.  You see intermediate results of longrunning commands without waiting for the entire command to have finished.
 You can create multiple graphs in the same cell without having to name each of them individually. (Order of the graphs is also guaranteed).
 You don't have to have any knowledge whatsoever of Python ^{1}.

Python is amazing language, and if you want to move on to bigger data, I highly recommend learning Python. Now that
stata_kernel
is installed, if you want to start a Python notebook instead of a Stata notebook, just choose New > Python 3 in the dropdown menu. ↩