Python + Dataverse Series – #06: Data preprocessing steps before running Machine Learning Algorithms

Hi Folks,

If you were already a Power Platform Consultant and new to working with Python, then I would encourage to start from the beginning of this series.

Python + Dataverse Series – How to run Python Code in Vs Code

Now in this series, we entered an interesting part where Machine learning algorithms were run to analyze Dataverse Data and in this post we will understand why to scaling, feature scaling is a critical preprocessing step for many machine learning algorithms because it ensures that all features contribute equally to the model’s outcome, prevents numerical instability, and helps optimization algorithms converge faster to the optimal solution

Primarily before running any Machine Learning Algorithm, we need to do some data preprocessing like scaling the data, in this case we will use a formula which is used to scale using min–max normalization (feature scaling to the [0, 1] range).

#preprocessing step before running machine learning algorithms
from azure.identity import InteractiveBrowserCredential #using Interactive Login
from PowerPlatform.Dataverse.client import DataverseClient #installing Python SDK for Dataverse
import numpy as np #import Numpy Library to perform calculations
# Connect to Dataverse
credential = InteractiveBrowserCredential()
client = DataverseClient("https://ecellorsdev.crm8.dynamics.com", credential) #Creates Dataverse Client
# Fetch account data as paged batches
account_batches = client.get(
"account",
select=["accountid", "revenue"],
top=10,
) #Fetches top 10 accounts with accountid, revenue columns
revenues = []
for batch in account_batches:
for account in batch:
if "revenue" in account and account["revenue"] is not None:
revenues.append(account["revenue"])
revenues = np.array(revenues)
#Normalize the revenue
if len(revenues) > 0:
min_rev = np.min(revenues)
max_rev = np.max(revenues)
normalized_revenues = (revenues – min_rev) / (max_rev – min_rev)
print("Normalized Revenues:", normalized_revenues)
#visualize the result
import matplotlib.pyplot as plt
plt.plot(normalized_revenues, marker='o')
plt.title('Normalized Revenues from Dataverse Accounts')
plt.xlabel('Account Index')
plt.ylabel('Normalized Revenue')
plt.grid()
plt.show()
view raw preprocessing step before running machine learning algorithms hosted with ❤ by GitHub

You can download the Python Notebook below if you want to work with VS Code

https://github.com/pavanmanideep/DataverseSDK_PythonSamples/blob/main/Python-PreProcessingStepBeforeMachineLearning.ipynb

Hope you found this useful…

Cheers,

PMDY

Python + Dataverse Series – How to run Python Code in Vs Code

Hi Folks,

As you folks know that Python currently is the number #1 programming language with a massive, versatile ecosystem of libraries for data science, AI, and backend web development. This post kicks off a hands‑on series about working with Microsoft Dataverse using Python. We’ll explore how to use the Python SDK to connect with Dataverse, automate data operations, and integrate Python solutions across the broader Power Platform ecosystem. Whether you’re building data-driven apps, automating workflows, or extending Power Platform capabilities with custom logic, this series will help you get started with practical, real‑world examples.

https://www.microsoft.com/en-us/power-platform/blog/2025/12/03/dataverse-sdk-python/

With the release of the Dataverse SDK for Python, building Python-based logic for the Power Platform has become dramatically simpler. In this post, we’ll walk through how to download Python and set it up in Visual Studio Code so you can start building applications that interact with Dataverse using Python. Sounds exciting already. Let’s dive in and get everything set up..

1. Download and install Python from official website below and then install it in your computer.

    https://www.python.org/ftp/python/3.14.3/python-3.14.3-amd64.exe

    2. Install VS Code

    Important: During installation, make sure to check “Add Python to PATH”. This ensures VS Code can detect Python automatically.

    3. After installation, open VS Code and install the Python extension (Microsoft’s official one). This extension enables IntelliSense, debugging, and running Python script

    4. That’s it, you are now able to run Python logic inside Vs Code

    5. Create or Open a Python file in the system, opened a sample file below

    5. If you want to run Python Programmes in your VS Code, follow below options

    a. Select Start Debugging

    b. You will be prompted a window like below

    You can select the first option highlighted above, it automatically runs your Python Code

    This is very easy to setup…

    If you want to continue reading this series, check out the next article.

    Python + Dataverse Series – #01 – Console Application using Python

    Hope this helps…

    Cheers,

    PMDY