Added anomaly detection script and requirements file

[swastik-21]

Hi,
I’ve added a simple anomaly detection script under ai_modules/anomaly_detection.py. Right now it uses a z-score approach to flag unusual values in water usage data. The threshold can be adjusted so it works with different datasets.
I also created a requirements.txt so dependencies can be installed more easily.
Tested locally with sample data, and it correctly flagged extreme outliers. This is an initial version, so open to feedback or suggestions on improvements.
Thanks

[swastik-21]

@microsoft-github-policy-service agree

[QuantumAlchemist03]

Added a few suggestions for improvements. Overall looks good!

[QuantumAlchemist03]

The anomaly detection function is clear and well-documented. A few suggestions:

1. Consider adding a check for std == 0 to avoid division by zero errors.
2. In the example usage, it might help to explain why z_thresh=2.0 is chosen (e.g., more sensitive to outliers).
3. Optionally, you could mention that this method assumes a roughly normal distribution for data.

[QuantumAlchemist03]

This requirements.txt is clear and version-pinned, which is great for reproducibility. A few suggestions:

1. Double-check if numpy==2.3.2 and pandas==2.3.2 are compatible; sometimes older versions of one library may conflict with the other.
2. Consider whether all dependencies (like six or tzdata) are actually used in the project — removing unused packages can simplify the environment.
3. Optionally, you could mention Python version compatibility, e.g., if this works for Python 3.11 or higher.