Click here to download this page as a Jupyter Notebook.
pip install kxy
git clone https://github.com/kxytechnologies/kxy-python.git & cd ./kxy-python & pip install .
kxy package only supports Python 3. Replace
pip3 in the commands above, as needed.
All heavy-duty computations, including but not limited to solving any maximum-entropy optimization problem, are run on our serverless infrastructure and require an API key. The API key is set by running the command
as a one-off, and following the instructions.
To request a demo and get a trial API key, email email@example.com.
Working with Pandas DataFrames¶
The most convenient way of using the
kxy package is through pandas DataFrame objects. All our analyses are available as methods of pandas DataFrame objects, under the
kxy accessor (i.e. as
df.kxy.<method_name>). To access these, all you need is to import the
kxy package alongside
import pandas as pd import kxy
Checkout the Examples section for tutorials with code snippets.
Working with Numpy Arrays¶
If you prefer working with numpy arrays, you might want to familiarize yourself with methods in the lower level namespaces
and/or the higher level namespaces
depending on your usecase.
Working with the Low Level RESTFul API¶
To directly access our serverless compute infrastructure through its RESTFul API take a look at