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  1. API reference
  2. Welcome
    1. Getting started
    2. Get Flexmonster
    3. Quick start
    4. System requirements
    5. Troubleshooting
    6. Managing license keys
    7. Migrating from WebDataRocks to Flexmonster
  3. Integration with frameworks
    1. Available tutorials
    2. Integration with Angular
    3. Integration with React
    4. Integration with Vue
    5. Other integrations
      1. Integration with Python
        1. Integration with Django
        2. Integration with Jupyter Notebook
      2. Integration with React Native
      3. Integration with Blazor
      4. Integration with AngularJS (v1.x)
      5. Integration with TypeScript
      6. Integration with R Shiny
      7. Integration with jQuery
      8. Integration with Ionic
      9. Integration with Electron.js
      10. Integration with Webpack
      11. Integration with RequireJS
  4. Connecting to Data Source
    1. Supported data sources
    2. JSON
      1. Connecting to JSON
      2. Connecting to JSON using Flexmonster Data Server
      3. Data types in JSON
    3. CSV
      1. Connecting to CSV
      2. Connecting to CSV using Flexmonster Data Server
      3. Data types in CSV
    4. Database
      1. Connecting to SQL databases
      2. Connecting to a MySQL database
      3. Connecting to a Microsoft SQL Server database
      4. Connecting to a PostgreSQL database
      5. Connecting to an Oracle database
    5. Flexmonster Data Server
      1. Introduction to Flexmonster Data Server
      2. Getting started with Flexmonster Data Server
      3. Flexmonster Admin Panel Guide
      4. Data sources guide
      5. Security and authorization guide
      6. The Data Server as a DLL
        1. Getting started with the Data Server as a DLL
        2. Referencing the Data Server as a DLL
        3. Implementing the API controller
        4. Implementing the server filter
        5. Implementing the custom parser
        6. DLL configurations reference
        7. The controller's methods for request handling
      7. The Data Server as a console application
        1. Installing the Data Server as a console application
        2. Configurations reference
        3. Data sources guide
        4. Security and authorization guide
      8. Troubleshooting the Data Server
    6. MongoDB
      1. Introduction to Flexmonster MongoDB Connector
      2. Getting started with the MongoDB Connector
      3. Embedding the MongoDB Connector into the server
      4. Configuring the MongoDB Connector
    7. Microsoft Analysis Services
      1. Connecting to Microsoft Analysis Services
      2. Getting started with Flexmonster Accelerator
      3. Referencing the Accelerator as a DLL
      4. Configuring the authentication process
      5. Configuring a secure HTTPS connection
      6. Troubleshooting
    8. Custom data source API
      1. Introduction to the custom data source API
      2. A quick overview of a sample Node.js server
      3. A quick overview of a sample .NET Core server
      4. Implement your own server
        1. Implementing the custom data source API server
        2. Implementing filters
        3. Supporting more aggregation functions
        4. Supporting multilevel hierarchies
        5. Returning data for the drill-through view
        6. Testing your custom data source API server
    9. Elasticsearch
      1. Connecting to Elasticsearch
      2. Configuring the mapping
    10. Pentaho Mondrian
      1. Connecting to Pentaho Mondrian
      2. Getting started with the Accelerator
      3. Configuring Mondrian roles
      4. Configuring username/password protection
      5. Configuring a secure HTTPS connection
      6. Troubleshooting
    11. Connecting to other data sources
  5. Accessibility
    1. Accessibility overview
    2. Keyboard navigation
  6. Configuring the component
    1. Available tutorials
    2. Getting started with the report
    3. Configure the data source
      1. Data source
      2. Mapping
    4. Define which data to show
      1. Slice
      2. Custom sorting
      3. Calculated values
    5. Manage Flexmonster’s functionality
      1. Options
      2. Configuring global options
    6. Format fields
      1. Number formatting
      2. Date and time formatting
      3. Conditional formatting
    7. Save component configs
      1. Get the report from the component
      2. Set the report for the component
      3. Share the report
      4. Export and print
  7. Charts
    1. Available tutorials
    2. Flexmonster Pivot Charts
    3. Integration with Highcharts
    4. Integration with amCharts
    5. Integration with Google Charts
    6. Integration with FusionCharts
    7. Integration with any charting library
  8. Customizing
    1. Available tutorials
    2. Customizing the Toolbar
    3. Customizing appearance
    4. Customizing the context menu
    5. Customizing the grid
    6. Customizing the pivot charts
    7. Localizing the component
  9. Security
    1. Security in Flexmonster
    2. Security aspects of connecting to an OLAP cube
      1. Ways of connecting to an OLAP cube
      2. The data transfer process
      3. Data security
      4. Data access management
  10. Updating to the latest version
    1. Updating to the latest version
    2. Release notes
    3. Migration guide from 2.8 to 2.9
    4. Migration guide from 2.7 to 2.8
    5. Migration guide from 2.6 to 2.7
    6. Migration guide from 2.5 to 2.6
    7. Migration guide from 2.4 to 2.5
    8. Migration guide from 2.3 to 2.4
    9. Migration guide from 2.2 to 2.3
  11. Flexmonster CLI Reference
    1. Overview
    2. Troubleshooting the CLI
    3. flexmonster create
    4. flexmonster add
    5. flexmonster update
    6. flexmonster version
    7. flexmonster help
  12. Documentation for older versions
Table of contents

Integration with Jupyter Notebook

This tutorial will help you integrate Flexmonster with Jupyter Notebook applications. Follow these steps to set up a simple project.

Prerequisites

To run a simple application, you will need the Jupyter Notebook. For simplicity, you can use the web version of it, which doesn’t require anything to be installed on your computer. You can also follow this guide and install the Notebook yourself.

After that, choose one of the following options:

  1. Run a simple Jupyter Notebook and Flexmonster sample from GitHub
  2. Integrate Flexmonster into a Jupyter Notebook application

Run a simple Jupyter Notebook and Flexmonster sample from GitHub

Step 1. Download the .zip archive with the sample or clone it from GitHub with the following command:

git clone https://github.com/flexmonster/pivot-jupyter-notebook

Step 2a. If using the desktop version of the Jupyter Notebook, run it with the following command:

jupyter notebook

The Jupyter Notebook will be automatically launched in your browser.

Step 2b. Now, upload the Flexmonster_in_Jupyter_Notebook.ipynb file to the Jupyter Notebook. The file will appear in the Files tab.

Step 3. Run the sample project by selecting the Cell section in the navigation bar and clicking on the Run all option.

Integrate Flexmonster into a Jupyter Notebook application

To integrate Flexmonster into a Jupyter Notebook app, follow these steps:

Step 1. If you don’t have an existing Python 3 notebook, open the Jupyter Notebook and create a new Python 3 file.

Step 2. Import the following libraries to work with HTML and JSON in Python, as well as Pandas for data manipulation:

from IPython.display import HTML
import json
import pandas as pd

Step 3. Define some data with Pandas and convert it to JSON using the orient="records" parameter. This will present the data in the format that Flexmonster requires:

data = pd.DataFrame([["Lemon cake", 30, 4.99],["Apple pie", 45, 6.99], ["Raspberry jam", 70, 3.99]],index=['row 1', 'row 2', 'row 3'], columns=['Product', 'Quantity', 'Price per Item'])
json_data = data.to_json(orient="records")

Step 4. Define Flexmonster:

flexmonster = {
"container": "pivotContainer",
"componentFolder": "https://cdn.flexmonster.com/",
"report": {
"dataSource": "json",
"data": json.loads(json_data)
}
}

Step 5. Convert the flexmonster object to a JSON-formatted string:

flexmonster_json_object = json.dumps(flexmonster)

Step 6. Define a function to display Flexmonster in HTML (e.g., pivot):

def pivot(flexmonster_json_object):
#the format function is needed to insert the Flexmonster object into the script
    code = '''
      <script src="https://cdn.flexmonster.com/flexmonster.js"></script>
     <h1>Flexmonster Integration with the Jupyter Notebook</h1>
     <div id="pivotContainer"></div>
      <script>
       new Flexmonster({});
     </script>
     '''.format(flexmonster_json_object)
#convert the code string to HTML
   return HTML(code)

Step 7. Display the component using the previously defined pivot function:

pivot(flexmonster_json_object)

Step 8. Run the notebook by selecting the Cell section in the navigation bar and clicking on the Run all option.

The component will appear in an output cell right under the one containing the pivot function call.

What’s next?

You may be interested in the following articles: