xgboosted
821038e1e1
Update all stale indicator counts (193→224, 253→284) across README, index, docs/index.rst, quickstart.md, and indicators.rst. Remove unverifiable hardcoded numbers (59 core indicators, ~45 indicators, 89/98/66 counterparts) in favor of generic descriptions or links to the live matrix. Add tulipy to optional deps list. Pin ta-lib>=0.6.8 in pyproject.toml and document binary wheel availability in install docs — pre-0.6.5 lacks wheels and requires manual C library setup. Pin tulipy>=0.4.0. Remove duplicate Compatibility Matrix section. Replace stale Windows wheel workaround with single cross-platform install command.
81 lines
2.5 KiB
ReStructuredText
81 lines
2.5 KiB
ReStructuredText
Pandas TA Classic Documentation
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===============================
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**Pandas TA Classic** is an easy to use library that leverages the Pandas package with **224 indicators and utility functions** plus **62 native candlestick patterns** (**284 unique total**; ``cdl_doji`` and ``cdl_inside`` are counted in both sets). All CDL patterns are natively implemented — no TA-Lib required. This is the **community maintained version** of the popular pandas-ta library.
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.. note::
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The library features **dynamic configuration management**:
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- **Category Discovery**: Indicators are automatically detected from the package structure
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- **Version Management**: Python version support (the latest stable plus the prior 4 versions) is dynamically managed via CI/CD workflows
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- Both ensure the library metadata stays in sync with actual capabilities
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.. image:: https://img.shields.io/github/license/xgboosted/pandas-ta-classic
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:target: #license
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:alt: License
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.. image:: https://github.com/xgboosted/pandas-ta-classic/workflows/CI/badge.svg
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:target: https://github.com/xgboosted/pandas-ta-classic/actions
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:alt: Build Status
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.. image:: https://img.shields.io/pypi/v/pandas-ta-classic?style=flat
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:target: https://pypi.org/project/pandas-ta-classic/
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:alt: PyPI Version
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Quick Start
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-----------
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**Pandas TA Classic** is simple to use — import the library and start calculating indicators directly on your DataFrame:
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.. code-block:: python
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import pandas as pd
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import pandas_ta_classic as ta
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# Load your data
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df = pd.read_csv("path/to/symbol.csv")
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# Calculate indicators
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df.ta.sma(length=20, append=True)
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df.ta.rsi(append=True)
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df.ta.macd(append=True)
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.. note::
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**New to Pandas TA Classic?** Check out our :doc:`quickstart` guide for a comprehensive introduction, or explore the :doc:`dataframe_api` guide for detailed programming conventions.
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Table of Contents
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-----------------
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.. toctree::
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:maxdepth: 2
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:caption: Getting Started:
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installation
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quickstart
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tutorials
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.. toctree::
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:maxdepth: 2
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:caption: User Guide:
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strategies
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dataframe_api
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indicators
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performance
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.. toctree::
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:maxdepth: 2
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:caption: Additional Resources:
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testing
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GitHub Repository <https://github.com/xgboosted/pandas-ta-classic>
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Examples <https://github.com/xgboosted/pandas-ta-classic/tree/main/examples>
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Changelog <https://github.com/xgboosted/pandas-ta-classic/blob/main/CHANGELOG.md>
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Indices and tables
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==================
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* :ref:`genindex`
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* :ref:`modindex`
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* :ref:`search`
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