Metadata-Version: 2.1
Name: pandas-ta-quant
Version: 0.2.4
Summary: Augment pandas DataFrame with methods for machine learning
Home-page: https://github.com/KIC/pandas-ml-quant/pandas-ta-quant
Author: KIC
Author-email: 
License: MIT
Description: # Pandas TA Quant
        
        Not only a pure python re-implementation of the famous [TA-Lib][e1]. Additional indicators are available like covariance 
        measures or arma, garch and sarimax models. The library fully builds on top of pandas and pandas_ml_common, therefore
        allows to deal with MultiIndex easily:
        
        | Date                |   ('spy', 'Open') |   ('spy', 'High') |   ('spy', 'Low') |   ('spy', 'Close') |   ('spy', 'Volume') |   ('spy', 'Dividends') |   ('spy', 'Stock Splits') |   ('gld', 'Open') |   ('gld', 'High') |   ('gld', 'Low') |   ('gld', 'Close') |   ('gld', 'Volume') |   ('gld', 'Dividends') |   ('gld', 'Stock Splits') |
        |:--------------------|------------------:|------------------:|-----------------:|-------------------:|--------------------:|-----------------------:|--------------------------:|------------------:|------------------:|-----------------:|-------------------:|--------------------:|-----------------------:|--------------------------:|
        | 2020-02-07 00:00:00 |            332.82 |            333.99 |           331.6  |             332.2  |         6.41394e+07 |                      0 |                         0 |            147.83 |            148.18 |           147.34 |             147.79 |         6.3793e+06  |                      0 |                         0 |
        | 2020-02-10 00:00:00 |            331.23 |            334.75 |           331.19 |             334.68 |         4.207e+07   |                      0 |                         0 |            148.21 |            148.45 |           147.91 |             148.17 |         5.7936e+06  |                      0 |                         0 |
        
        ```
        df = pd.read_pickle("../pandas_ta_quant_test/.data/spy_gld.pickle")
        df._[["Close", df._["Close"].ta.sma(200)]].plot(figsize=(20,10))
        ```
        
        ![Plot][ghi1]
        
        ## Full List of indicators
        
        |                                | module                                                            |
        |:-------------------------------|:------------------------------------------------------------------|
        | ta_adx                         | pandas_ta_quant.technical_analysis.indicators.multi_object        |
        | ta_all                         | pandas_ta_quant.technical_analysis.indicators                     |
        | ta_apo                         | pandas_ta_quant.technical_analysis.indicators.single_object       |
        | ta_atr                         | pandas_ta_quant.technical_analysis.indicators.multi_object        |
        | ta_bbands                      | pandas_ta_quant.technical_analysis.bands                          |
        | ta_bbands_indicator            | pandas_ta_quant.technical_analysis.indicators.single_object       |
        | ta_bop                         | pandas_ta_quant.technical_analysis.indicators.multi_object        |
        | ta_candle_category             | pandas_ta_quant.technical_analysis.encoders.candles               |
        | ta_candles_as_culb             | pandas_ta_quant.technical_analysis.encoders.candles               |
        | ta_cci                         | pandas_ta_quant.technical_analysis.indicators.multi_object        |
        | ta_cross                       | pandas_ta_quant.technical_analysis.labels.discrete                |
        | ta_cross_over                  | pandas_ta_quant.technical_analysis.labels.discrete                |
        | ta_cross_under                 | pandas_ta_quant.technical_analysis.labels.discrete                |
        | ta_decimal_year                | pandas_ta_quant.technical_analysis.indicators.time                |
        | ta_delta_hedged_price          | pandas_ta_quant.technical_analysis.normalizer                     |
        | ta_div                         | pandas_ta_quant.technical_analysis.math                           |
        | ta_draw_down                   | pandas_ta_quant.technical_analysis.indicators.single_object       |
        | ta_edge_detect                 | pandas_ta_quant.technical_analysis.forecast.support               |
        | ta_ema                         | pandas_ta_quant.technical_analysis.filters                        |
        | ta_ewma_covariance             | pandas_ta_quant.technical_analysis.covariances                    |
        | ta_fibbonaci_retracement       | pandas_ta_quant.technical_analysis.forecast.support               |
        | ta_future_bband_quantile       | pandas_ta_quant.technical_analysis.labels.discrete                |
        | ta_future_crossings            | pandas_ta_quant.technical_analysis.labels.discrete                |
        | ta_future_multi_bband_quantile | pandas_ta_quant.technical_analysis.labels.discrete                |
        | ta_future_multi_ma_quantile    | pandas_ta_quant.technical_analysis.labels.discrete                |
        | ta_future_pct_to_current_mean  | pandas_ta_quant.technical_analysis.labels.continuous              |
        | ta_gaf                         | pandas_ta_quant.technical_analysis.encoders.gramian_angular_field |
        | ta_gap                         | pandas_ta_quant.technical_analysis.indicators.multi_object        |
        | ta_garch11                     | pandas_ta_quant.technical_analysis.forecast.volatility            |
        | ta_has_opening_gap             | pandas_ta_quant.technical_analysis.labels.discrete                |
        | ta_hmm                         | pandas_ta_quant.technical_analysis.forecast.predictive_indicator  |
        | ta_inverse                     | pandas_ta_quant.technical_analysis.encoders.resample              |
        | ta_inverse_gasf                | pandas_ta_quant.technical_analysis.encoders.gramian_angular_field |
        | ta_is_opening_gap_closed       | pandas_ta_quant.technical_analysis.labels.discrete                |
        | ta_log_returns                 | pandas_ta_quant.technical_analysis.normalizer                     |
        | ta_ma_decompose                | pandas_ta_quant.technical_analysis.indicators.single_object       |
        | ta_ma_ratio                    | pandas_ta_quant.technical_analysis.normalizer                     |
        | ta_macd                        | pandas_ta_quant.technical_analysis.indicators.single_object       |
        | ta_mean_returns                | pandas_ta_quant.technical_analysis.indicators.single_object       |
        | ta_mgarch_covariance           | pandas_ta_quant.technical_analysis.covariances                    |
        | ta_mom                         | pandas_ta_quant.technical_analysis.indicators.single_object       |
        | ta_moving_covariance           | pandas_ta_quant.technical_analysis.covariances                    |
        | ta_multi_bbands                | pandas_ta_quant.technical_analysis.filters                        |
        | ta_multi_ma                    | pandas_ta_quant.technical_analysis.filters                        |
        | ta_ncdf_compress               | pandas_ta_quant.technical_analysis.normalizer                     |
        | ta_normalize_row               | pandas_ta_quant.technical_analysis.normalizer                     |
        | ta_ohl_trend_lines             | pandas_ta_quant.technical_analysis.forecast.support               |
        | ta_one_hot                     | pandas_ta_quant.technical_analysis.encoders.one_hot               |
        | ta_one_hot_encode_discrete     | pandas_ta_quant.technical_analysis.encoders.one_hot               |
        | ta_performance                 | pandas_ta_quant.technical_analysis.normalizer                     |
        | ta_poly_coeff                  | pandas_ta_quant.technical_analysis.indicators.single_object       |
        | ta_ppo                         | pandas_ta_quant.technical_analysis.indicators.single_object       |
        | ta_realative_candles           | pandas_ta_quant.technical_analysis.encoders.candles               |
        | ta_rescale                     | pandas_ta_quant.technical_analysis.normalizer                     |
        | ta_returns                     | pandas_ta_quant.technical_analysis.normalizer                     |
        | ta_rnn                         | pandas_ta_quant.technical_analysis.encoders.auto_regression       |
        | ta_roc                         | pandas_ta_quant.technical_analysis.indicators.single_object       |
        | ta_rsi                         | pandas_ta_quant.technical_analysis.indicators.single_object       |
        | ta_sarimax                     | pandas_ta_quant.technical_analysis.forecast.predictive_indicator  |
        | ta_sharpe_ratio                | pandas_ta_quant.technical_analysis.indicators.single_object       |
        | ta_sinusoidal_week             | pandas_ta_quant.technical_analysis.indicators.time                |
        | ta_sinusoidal_week_day         | pandas_ta_quant.technical_analysis.indicators.time                |
        | ta_slope                       | pandas_ta_quant.technical_analysis.indicators.single_object       |
        | ta_sma                         | pandas_ta_quant.technical_analysis.filters                        |
        | ta_sma_price_ratio             | pandas_ta_quant.technical_analysis.normalizer                     |
        | ta_sortino_ratio               | pandas_ta_quant.technical_analysis.indicators.single_object       |
        | ta_sparse_covariance           | pandas_ta_quant.technical_analysis.covariances                    |
        | ta_std_ret_bands               | pandas_ta_quant.technical_analysis.bands                          |
        | ta_std_ret_bands_indicator     | pandas_ta_quant.technical_analysis.indicators.single_object       |
        | ta_stddev                      | pandas_ta_quant.technical_analysis.indicators.single_object       |
        | ta_tr                          | pandas_ta_quant.technical_analysis.indicators.multi_object        |
        | ta_trend_lines                 | pandas_ta_quant.technical_analysis.forecast.support               |
        | ta_trix                        | pandas_ta_quant.technical_analysis.indicators.single_object       |
        | ta_ultimate_osc                | pandas_ta_quant.technical_analysis.indicators.multi_object        |
        | ta_up_down_volatility_ratio    | pandas_ta_quant.technical_analysis.indicators.single_object       |
        | ta_volume_as_time              | pandas_ta_quant.technical_analysis.encoders.volume                |
        | ta_wilders                     | pandas_ta_quant.technical_analysis.filters                        |
        | ta_williams_R                  | pandas_ta_quant.technical_analysis.indicators.multi_object        |
        | ta_z_norm                      | pandas_ta_quant.technical_analysis.normalizer                     |
        | ta_zscore                      | pandas_ta_quant.technical_analysis.indicators.single_object       |                                                                       |
        
        [ghi1]: ../.readme/images/multi_index.png
        
        [e1]: http://mrjbq7.github.io/ta-lib/
Keywords: pandas,ml,util,quant
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Description-Content-Type: text/markdown
Provides-Extra: dev
