Stata 16 now integrates with Python. I’m pretty stoked about using some of the Python figure packages. Getting it up and running has been a bit of a challenge. Here’s how I got it to work.
Of note, some might find Anaconda a bit simpler to use than the traditional Python distribution. Anaconda is a commercial Python distribution that ships with integrated software intended for data scientists. I’m not entirely clear of the costs associated with Anaconda if you are from a university or research institution, so I’m trying to get up and running with the default version of Python. Plus, my goal is to use Python within Stata as I like the database management of Stata. Much of the extra stuff that comes with Anaconda isn’t of immediate use to me.
Installing the traditional Python distribution
First, you need to have Stata 16 or greater. This doesn’t work on earlier versions.
As of July 2020, Python apparently has two versions that are commonly used, the 2.x version and the 3.x version. The end-of-life of 2.x versions is this year, so I wouldn’t recommend using it (current highest version is 2.7). Instead, use the 3.x version, currently the 3.8 version. You can find it at the Python website’s download page.
Make sure to install the version matching your Stata install! Stata comes as 32 bit or 64 bit. In Stata, type -about- to see what version you have. You’ll see that mine is running the 64-bit version of Stata. If you have a relatively modern computer, you are probably running the 64-bit version as well. Windows can actually run either 32-bit or 64-bit versions if you have a 64-bit processor, so do yourself a favor and just check.
Make sure that you install the corresponding version of Python. The highlighted one (x86-64) is the 64 bit. The other one (x86) is the 32-bit version. For this example, since I have the 64-bit version of stata, I installed the x86-64, 64-bit version of Python.
I had originally installed the 32-bit version of Python and Stata couldn’t load it. Installing the 64-bit version of Python solved that.
For the love of Pete, check this PATH box when you install it.
PATH is a list of commands that can be run from the Windows command line, and where their relative program exists.
See this check box right here? Select it. If you don’t, you’ll have a heck of a time getting anything to run from the command line. This should be checked on default, I have no idea why it’s not.
If you forgot to check this box, uninstall Python and reinstall it after checking this box.
What the heck did I just install?
There are two Python shell apps/programs that came along with the default Python setup. IDLE is a more user-friendly Python shell. It resembles the command line in Stata, but it has the syntax highlighting of the Do file editor.
The app called “Python 3.8 (64-bit)” is the shell without any markup. If you want to play around with Python, I recommend using IDLE.
Making your first program in IDLE
Anything you run in Python should be from a script, or a *.py file. Pop one open from within IDLE by hitting Ctrl+N. Enter the following:
Then save it and run it (by pressing F5) and you’ll get the hello world!
How does that look in Stata?
Let’s do the same thing in a Stata do file. In order to open up the Python shell within Stata, you have to type –python– on its own line, your intended python code, then –end– on its own line. Here, I have entered:
python print("hello world!") end
Then just hit ctrl+d or the run button to get it to work in Stata!
How do I get the Pandas, Matplotlib, SciPy, Sklearn, and NumPy libraries installed?
Python by itself can do some stuff, but the heavy lifting for stats and visualization is from add-in libraries that aren’t included with the default Python and must be added in before doing much of anything else. (Note: Anaconda does come with those and is a Python installation geared towards science, but we’re doing the classic install here.) Installing these additional libraries can be done with the included pip library, which automates all downloads and installations. BUT pip it has to be called from the Windows command line, not in a Python shell (i.e., not in IDLE). You’ll know you’re in the shell if the line starts with this:
So if you type “pip install pandas” in the shell (after the “>>>”), you’ll get an error and you will not be getting pandas.
To pop up the Windows command line, hit the Start button then type “cmd” to open it up. Or hit windows key+r and type “cmd” to open it up. If you correctly checked the PATH checkbox in the install, you should get the version reported if you type the following in:
If you get some sort of error, it’s probably because you didn’t check the PATH box during the install. Uninstall Python then reinstall it and make for sure you check that stupid PATH box.
A note about the Windows 10 command line: If you type “Python” and hit enter, Windows pops up the Windows store and tries to get you to install the version of Python that they host. This is by far the dumbest Windows feature ever, and I have seen BOB. So, avoid ever typing the word “python” in the command line. Instead, use the handy “py” command, which does everything you’ll need it to do. Py is the python launcher.
To call pip, you want to type in “py” then “-m” then “pip” and its commands. the “-m” allows you to run library commands as a script. So, to install pandas, just type the following in to the command line:
py -m pip install pandas
You’ll see a screen like this:
…and ditto for the others (though it seems that NumPy installs along with pandas, it’s included here for completeness). When you are all done, you should have typed the following 5 lines individually:
py -m pip install pandas py -m pip install matplotlib py -m pip install numpy py -m pip install scipy py -m pip install sklearn
You only need to do this installation step once.
How do I use Pandas, Matplotlib, NumPy, Scikit-learn (sklearn), and SciPy in Stata?
Once the libraries are installed, you can then integrate them into your scripts. Each time you want to use them, you need to import them so you can call them. The convention is to import these using common so you don’t have to type “pandas” over and over again, you can just use “pd”. Ditto for other libraries:
python import pandas as pd import matplotlib.pyplot as plt import numpy as np import scipy as sp import sklearn as sk end
How do I use SFI to interface Stata and Python?
Stata and Python talk to each other using the Stata function interface, or SFI. MORE TO COME ON THIS.