Add Plotly-based feature visualization examples and docs links

[chandraveshchaudhari]

This PR addresses the visualization TODO by adding Plotly-based examples for technical indicator exploration.

What changed

• Added category-based notebooks to visualize indicator outputs using Plotly.
• Updated README guidance to point users to the new category notebooks.
• Improved discoverability of feature-visualization workflows across Volume, Volatility, Trend, Momentum, and Others indicators.

Why this change

• Makes technical indicators easier to inspect and compare interactively.
• Improves the feature-engineering experience for users working with financial time series.
• Helps new users quickly understand indicator behavior through visual exploration.

Scope

• Non-breaking change.
• Focused on examples and documentation updates.
• No API behavior changes.

Validation

• Confirmed notebooks render Plotly visualizations correctly.
• Verified README links and navigation to the new examples.

[review-notebook-app]

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[atharvajoshi01]

Nice visualizations, the Plotly charts look good. A few things I noticed:

1. The committed notebook outputs add ~116k lines to the diff. Stripping outputs before commit (via nbstripout or clearing cells manually) would keep the repo lean and let users generate the charts themselves.

2. The helper functions (COLUMN_ALIASES, _find_column, load_nse_history, etc.) are duplicated across all 5 notebooks. A shared utility module in the same folder would cut the boilerplate.

3. The column headers in the CSV have trailing spaces which is why you need the alias matching logic. Stripping the headers in the CSV itself would simplify things.

4. The README TODO removal mentions Streamlit as addressed but only Plotly is covered here.

The charting code itself is clean and correct.

[chandraveshchaudhari]

Thanks, I have addressed all points. Please see the summary of changes:

• Notebook outputs: Stripped outputs and cleared execution counts for all five notebooks to shrink diffs.

  • 01_volume_indicators.ipynb
  • 02_volatility_indicators.ipynb
  • 03_trend_indicators.ipynb
  • 04_momentum_indicators.ipynb
  • 05_others_indicators.ipynb

• Shared utilities: Moved duplicated helpers into a single module: category_utils.py. Notebooks now call prepare_category() and only contain plotting code.

• CSV header trimming: Normalization added to load_nse_history() (headers are stripped) so trailing spaces are handled centrally; this removes the need for per-notebook alias duplication.

• README: Kept TODO for Streamlit app in README.md.

[chandraveshchaudhari]

Please review and merge my pull request