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Defining SciPyR Models

Infoveave supports custom analysis with Python on the SciPyR workbench to run large statistical models. The SciPyR workbench makes it easier and more accurate to build out custom analysis over the Infoveave datasources.

Accessing SciPyR Book

New SciPyR Workbook

To perform SciPyR analysis in Infoveave, follow these steps

  1. Access the SciPyR section by clicking on Analysis SciPyR. You will see a list of all SciPyR books, including those created by you or shared with you.
  2. To create a new SciPyR book based on Python, click on New SciPyR Book button . New SciPyR Book dialog box will display.

Selecting python workbook

Add SciPyR Book

Initiate the creation of a new Python Workbook by providing a unique name.

  1. Assign a Name for SciPyR Workbook.
  2. Click on Save to start creating your custom analysis in Infoveave. This will directly take you to the SciPyR workbook.
  3. Upon opening the SciPyR Workbook, you can begin writing your Python program directly in the Workbook.
  4. To start writing your Python program, select the default cell and start writing your Python program.
  5. To expand your analysis, add new cells by simply clicking the plus icon near the drop-down.
  6. Use the drop-down menu in the Workbook to select Code when writing Python code and Markdown when adding headings or titles.

Connecting to datasource for exploratory data analysis

Integrate SQL queries to your analysis through the Insert Query feature.

To insert SQL queries on DataSources into the SciPyR Workbook, follow the below steps Insert Query

  1. Click on the Insert Query icon in the SciPyR Workbook. Insert Query popup comes up.
  2. From the dropdown menu, select the desired data source that contains the SQL data.
  3. Write the SQL query you need in the provided workspace area.
  4. Click on the Execute query icon to execute the SQL query and see the results.
  5. If you want to insert the query to the SciPyR Workbook, click the Save button after executing the query.
  6. After this run the query. This will insert the query and its results into the Workbook for further analysis and reporting. insert query

Editing the inserted query

Click on Edit Query icon .

Building model & generating insights

Customize your analysis by adding, editing, and running cells, focusing on building your machine learning model within the SciPyR Workbook. Utilize the flexibility of manipulating cells to refine and tailor your analysis, leading to the generation of valuable insights from the data.

  • Customize the analysis by adding and editing cells within the SciPyR Workbook.
  • Incorporate Python code specific to your analysis requirement.
  • Execute individual cells, by simply select the cell and click on the Run icon .
  • You can also run the entire set of cells together by clicking the icon, to execute the complete analysis.
  • To refresh the kernel, click on the icon.
  • To save the SciPyR as a PDF file in the local storage, click on View PDF button. Save PDF
  • To save the analysis, click Save.
  • Go to Analysis SciPyR to see the saved analysis.

You have the flexibility to add cells above or below existing ones, move cells around, copy/duplicate cells, and delete cells to customize your analysis as needed.