Data analysis
Jupyter Notebook (https://jupyter-notebook.readthedocs.io/en/stable/) is a tool that allows you to perform various data analytics and manipulation tasks through on-the-fly Python scripting. Notebooks in FA provide you with the following features:
secure access to notebooks based on FA user roles, where each user operates in an individual computing environment
sharing documents with other FA users who have access to Notebooks
access to the most common Python libraries to perform financial and data analysis:
core data: numpy, pandas, scipy, sci-kit learn, statsmodels
data visualization: plotly, seaborn, matplotlib
finance: quandl, pyfolio, quantlib, TA-lib
access to the FA APIs
Note
FA Solutions does not provide support for data analysis scripting but enables it with Jupyter Notebook.
Getting started
Prerequisites
FA Back version 3.12 or newer
Jupyter Notebook enabled in your installation
FA user account with access to Notebooks
some coding skills (or willingness to learn)
getting familiar with Jupyter Notebook documentation: https://jupyter-notebook.readthedocs.io/en/stable/
Accessing Notebooks
Notebooks are accessed via FA Developer App: Notebooks view.
Creating your first notebook
To get started:
Go to the Notebooks view in the FA Developer app.
Click the plus icon
to open a new launcher and create a new notebook.
Check the ???section for samples that show how to fetch data to notebooks via FA APIs. You can upload the samples to your own notebooks by clicking the Upload files button 
.