Python not recognizing pyarrow version properly

Title: Troubleshooting Python's Inaccurate pyarrow Version Detection
Introduction:
Sometimes, when working with PyArrow in Python, you might encounter issues where Python does not recognize the installed PyArrow version correctly. This can lead to compatibility problems and runtime errors in your projects. In this tutorial, we will discuss common reasons for this problem and provide steps to troubleshoot and resolve it.
Prerequisites:
Common Reasons for Inaccurate PyArrow Version Detection:
Multiple Python Environments: You might have multiple Python environments, and the one you are using in your code may not have PyArrow installed. Alternatively, you may have multiple versions of PyArrow installed across different environments.
Virtual Environments: If you are using a virtual environment, the installed packages can differ from the system-level packages.
Outdated PyArrow Version: You might be using an outdated PyArrow version that is not compatible with your code.
Incomplete Installation: The PyArrow installation might not be complete, or some components could be missing.
Conflicting Dependencies: Other Python packages or dependencies might be causing conflicts with PyArrow, leading to version detection issues.
Troubleshooting and Resolving the Issue:
1. Check the Installed PyArrow Version:
Before we proceed, let's check the PyArrow version installed in your Python environment. You can do this using the following code:
Ensure that the version matches what you expect. If not, proceed with the following steps.
2. Verify the Python Environment:
Make sure it points to the environment with the correct PyArrow installation.
3. Update or Reinstall PyArrow:
For pip:
For conda:
4. Virtual Environments: