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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:

  1. Go to the Notebooks view in the FA Developer app.

  2. Click the plus icon notebooks_plus_icon.pngto 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 notebooks_upload_icon.png.