docs: added hml seg example to analysis modules page #110
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WalkthroughThis update enhances the documentation and code for HML segmentation. The documentation now includes a detailed explanation of the Heavy, Medium, Light segmentation methodology, a specific image replacement, and expanded example code. The sample code demonstrates data generation, applying the segmentation method, and visualizing results with a bar plot. Additionally, a new method Changes
Sequence Diagram(s)sequenceDiagram
participant User
participant Code
participant HMLSegmentation
participant Visualizer
User->>Code: Execute sample code
Code->>HMLSegmentation: Process transaction data
HMLSegmentation-->>Code: Return segmentation results
Code->>Visualizer: Generate bar plot
Visualizer-->>User: Display visualization
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Copilot reviewed 2 out of 2 changed files in this pull request and generated 1 comment.
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docs/analysis_modules.md:491
- [nitpick] The variable name 'rng' is ambiguous. It should be renamed to 'random_generator'.
rng = np.random.default_rng(42)
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🧹 Nitpick comments (2)
docs/analysis_modules.md (2)
464-478: Typo Correction and Terminology Consistency
The image’s alt text reads “HML Segementation Distribution,” which appears to contain a typo. Please correct “Segementation” to “Segmentation” to ensure consistency with the rest of the document.
484-513: Enhance Clarity in the HML Segmentation Example Code
The example clearly demonstrates generating sample transaction data, applyingHMLSegmentation, and visualizing the result. For added clarity, consider adding an inline comment that explains the purpose of thezero_value_customers="include_with_light"parameter. Also, please verify thatseg.dfincludes a column namedsegment_name(or the intended column) since it is used in the grouping operation for the bar plot.
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docs/analysis_modules.md(1 hunks)
Typo fix Co-authored-by: Copilot <[email protected]>
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🧹 Nitpick comments (2)
docs/analysis_modules.md (2)
464-475: Clarify HML Segmentation Explanation and Enhance Accessibility.
The new HML segmentation section provides a clear explanation of the thresholds (20% heavy, 30% medium, 50% light) and explains the handling of zero-spend customers. For additional clarity, consider briefly mentioning why these particular percentages are chosen or linking to supporting documentation. Also, verify that the image tag provides suitable alternative text for accessibility requirements.
483-511: Review the HML Segmentation Code Example.
The Python example effectively demonstrates how to generate sample transaction data, apply HML segmentation, and visualize the results. Two suggestions:
- Data Input Format: The call to
bar.plotpasses a grouped Series (viaseg.df.groupby("segment_name")["unit_spend"].sum()) along withvalue_col="unit_spend". To ensure compatibility with the plotting function (as seen in earlier examples that pass a DataFrame), consider converting the Series to a DataFrame using.reset_index(). For example:You would then likely need to specify the appropriate- seg.df.groupby("segment_name")["unit_spend"].sum(), + seg.df.groupby("segment_name")["unit_spend"].sum().reset_index(),x_col(e.g.,"segment_name") in the arguments, if required by the API.- Comment Improvement: It might help to add a brief comment clarifying that the segmentation thresholds (20/30/50) are derived from typical Pareto distribution observations.
PR Type
Documentation
Description
Added detailed explanation of HML segmentation.
Included an illustrative example with Python code.
Replaced placeholder text and image with relevant content.
Enhanced documentation with a new visualization example.
Changes walkthrough 📝
analysis_modules.md
Added HML segmentation details and exampledocs/analysis_modules.md
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