Python tool in Alteryx
Python tool in alteryx is a great way to incorporate python code into the alteryx workflow. It gives us another distinct feature which one doesn't think of, when one starts making workflows using the most used tools i.e. the frequently used tools like the one we can encounter in "In/Out", "Preparation", "Join", "Parse" and "Transform".
Let's get into the details of python tool in alteryx
This is how python tool look like
in Alteryx. It requires one input (not mandatory to provide) and we have five
output terminals, through which we can have a look at 5 different dataframes
(it’s just table in python language)
We can use the python tool in two
different modes
1) Interactive
mode : When the workflow is run, Alteryx will print messages within the Jupyter
notebook and refresh the data available to the notebook. This is helpful for
developing code but less efficient. Use
Interactive mode to view inline errors and charts.
2) Production
mode : Used to optimize speed and efficiency when you don’t need to inline
error messaging.
Input data
Input data is read as pandas
dataframe (pandas is one of the various libraries that python has). The input
data is read by python tool using the command
df
= Alteryx.read("#1")
where df is the name of the
dataframe, which you can chose by yourself.
Analysis
Perform your analysis on the pandas
dataframe. Create new columns and you can delete redundant columns. You might
have to install some libraries and modules depending upon the nature of the
analysis, you’re going to perform. For
example, using the code below, I’m installing the Python library which allows you to encode and decode JSON Web
Tokens (JWT)
pip
install pyjwt
Features
You can also directly import a
script (jupyter notebook file i.e. .ipynb file). Jupyter Notebook (formerly
IPython Notebooks) is a web-based interactive computational environment for
creating notebook documents.
There are some tools present in
the Alteryx which don’t mandatorily need an input to provide the output and
python tool is one of them.
You can get more information about Jupyter notebook
here
https://jupyter.org/
Output
The output can be written to any
of the five output terminals that python tool provides. The command to write
the output in the third output terminal is as shown
Alteryx.write(df, 3)
Where df is the name of the dataframe.
This is basically everything you need to know to get going
with the python tool. Of course there are more advanced features which you’ll
eventually come across, when you start working with it.
One of the mantra to get familiarize with the new tools is
to go through the example given in the alteryx. On the right hand side upper
corner, you can search for the tool and click on example for the tool you want
to learn more about and go through it. This is a great way to see different use
cases of a tool and then you can make a strategy for how you can use the tool
for your needs.
Thanks for reading
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