How to Visualize Nuclia 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 Nuclia-connected Python applications and scripts for visualizing Nuclia data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Nuclia data, execute queries, and visualize the results.

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

Connecting to Nuclia Data

Connecting to Nuclia 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

Nuclia uses API key authentication for accessing Knowledge Box data. To obtain an API key:

1. Log in to the Nuclia Cloud Dashboard at https://nuclia.cloud
2. Navigate to your Knowledge Box settings
3. Go to the Service Accounts section
4. Create a new service account or copy an existing API key

After obtaining your API key, set the following connection properties:

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your Nuclia service account API key.
• KbId: Set this to your Knowledge Box UUID.
• Zone: Set this to your Nuclia deployment zone (e.g., aws-us-east-2-1).

Example Connection String

Profile=C:\profiles\Nuclia.apip;AuthScheme=APIKey;APIKey=your_service_account_key;KbId=your_kb_uuid;Zone=aws-us-east-2-1;

Connecting to Nuclia

Once the authentication is configured, you can connect to Nuclia and query data from any of the available tables such as Resources, KnowledgeBox, LabelSets, and ProcessingStatus.

Follow the procedure below to install the required modules and start accessing Nuclia 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 Nuclia Data in Python

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

engine = create_engine("api:///?Profile=C:\profiles\Nuclia.apip&AuthScheme=APIKey&APIKey=your_service_account_key&KbId=your_kb_uuid&Zone=aws-us-east-2-1")

Execute SQL to Nuclia

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 KnowledgeBox WHERE  = ''", engine)

Visualize Nuclia Data

With the query results stored in a DataFrame, use the plot function to build a chart to display the Nuclia 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 Nuclia 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\Nuclia.apip&AuthScheme=APIKey&APIKey=your_service_account_key&KbId=your_kb_uuid&Zone=aws-us-east-2-1")
df = pandas.read_sql("SELECT ,  FROM KnowledgeBox WHERE  = ''", engine)

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