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Use pandas to Visualize PowerShell Scripts in Python

The CData Python Connector for PowerShell enables you use pandas and other modules to analyze and visualize live PowerShell scripts in Python.

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

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

Connecting to PowerShell Scripts

Connecting to PowerShell scripts 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.

The ScriptLocation, under the Data section, must be set to a valid script location.

Follow the procedure below to install the required modules and start accessing PowerShell 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 PowerShell Scripts in Python

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

engine = create_engine("powershell:///?ScriptLocation='%Public%\Documents\CData PowerShell Scripts'&ExecuteQuery=True")

Execute SQL to PowerShell

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

df = pandas.read_sql("SELECT ProcessName, CPU FROM Process WHERE ProcessName = 'RemoteConnectorService'", engine)

Visualize PowerShell Scripts

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

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

Free Trial & More Information

Download a free, 30-day trial of the PowerShell Python Connector to start building Python apps and scripts with connectivity to PowerShell scripts. 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("powershell:///?ScriptLocation='%Public%\Documents\CData PowerShell Scripts'&ExecuteQuery=True")
df = pandas.read_sql("SELECT ProcessName, CPU FROM Process WHERE ProcessName = 'RemoteConnectorService'", engine)

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