How to Visualize Miro Data in Python with pandas

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData API Driver for Python, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build Miro-connected Python applications and scripts for visualizing Miro data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Miro data, execute queries, and visualize the results.

With built-in optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Miro data in Python. When you issue complex SQL queries from Miro, the driver pushes supported SQL operations, like filters and aggregations, directly to Miro and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to Miro Data

Connecting to Miro data looks just like connecting to any relational data source. Create a connection string using the required connection properties. For this article, you will pass the connection string as a parameter to the create_engine function.

Using API Key Authentication

Miro uses API Key authentication with an access token. To generate an access token:

1. Log in to your Miro account
2. Navigate to Settings > Your apps
3. Click "Create new app" or select an existing app
4. Configure the required permissions (e.g., boards:read, teams:read)
5. Install the app and generate an access token
6. Copy the generated access token (it will only be shown once)

After obtaining your access token, set the following connection properties:

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your access token.

Connecting to Miro

Once the authentication is configured, you can connect to Miro and query data from any of the available tables such as Boards, Items, Teams, Organizations, and more.

Follow the procedure below to install the required modules and start accessing Miro through Python objects.

Install Required Modules

Use the pip utility to install the pandas & Matplotlib modules and the SQLAlchemy toolkit:

pip install pandas
pip install matplotlib
pip install sqlalchemy

Be sure to import the module with the following:

import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engine

Visualize Miro Data in Python

You can now connect with a connection string. Use the create_engine function to create an Engine for working with Miro data.

engine = create_engine("api:///?Profile=C:\profiles\Miro.apip&AuthScheme=APIKey&ProfileSettings='APIKey=your_access_token'")

Execute SQL to Miro

Use the read_sql function from pandas to execute any SQL statement and store the resultset in a DataFrame.

df = pandas.read_sql("SELECT ,  FROM Boards WHERE BoardId = '3074457361234567890'", engine)

Visualize Miro Data

With the query results stored in a DataFrame, use the plot function to build a chart to display the Miro data. The show method displays the chart in a new window.

df.plot(kind="bar", x="", y="")
plt.show()

Free Trial & More Information

Download a free, 30-day trial of the CData API Driver for Python to start building Python apps and scripts with connectivity to Miro data. Reach out to our Support Team if you have any questions.

Full Source Code

import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engin

engine = create_engine("api:///?Profile=C:\profiles\Miro.apip&AuthScheme=APIKey&ProfileSettings='APIKey=your_access_token'")
df = pandas.read_sql("SELECT ,  FROM Boards WHERE BoardId = '3074457361234567890'", engine)

df.plot(kind="bar", x="", y="")
plt.show()