## File: README.md [](https://technical-analysis-library-in-python.readthedocs.io/en/latest/?badge=latest) [](https://coveralls.io/github/bukosabino/ta) [](https://github.com/psf/black) [](http://prospector.landscape.io/en/master/) [](https://www.paypal.me/guau/3) # Technical Analysis Library in Python It is a Technical Analysis library useful to do feature engineering from financial time series datasets (Open, Close, High, Low, Volume). It is built on Pandas and Numpy. The library has implemented 43 indicators: ## Volume ID | Name | Class | defs -- |-- |-- |-- | 1 | Money Flow Index (MFI) | [MFIIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volume.MFIIndicator) | [money_flow_index](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volume.money_flow_index) 2 | Accumulation/Distribution Index (ADI) | [AccDistIndexIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volume.AccDistIndexIndicator) | [acc_dist_index](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volume.acc_dist_index) 3 | On-Balance Volume (OBV) | [OnBalanceVolumeIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volume.OnBalanceVolumeIndicator) | [on_balance_volume](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volume.on_balance_volume) 4 | Chaikin Money Flow (CMF) | [ChaikinMoneyFlowIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volume.ChaikinMoneyFlowIndicator) | [chaikin_money_flow](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volume.chaikin_money_flow) 5 | Force Index (FI) | [ForceIndexIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volume.ForceIndexIndicator) | [force_index](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volume.force_index) 6 | Ease of Movement (EoM, EMV) | [EaseOfMovementIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volume.EaseOfMovementIndicator) | [ease_of_movement](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volume.ease_of_movement)[sma_ease_of_movement](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volume.sma_ease_of_movement) 7 | Volume-price Trend (VPT) | [VolumePriceTrendIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volume.VolumePriceTrendIndicator)| [volume_price_trend](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volume.volume_price_trend) 8 | Negative Volume Index (NVI) | [NegativeVolumeIndexIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volume.NegativeVolumeIndexIndicator)| [negative_volume_index](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volume.negative_volume_index) 9 | Volume Weighted Average Price (VWAP) | [VolumeWeightedAveragePrice](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volume.VolumeWeightedAveragePrice) | [volume_weighted_average_price](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volume.volume_weighted_average_price) ## Volatility ID | Name | Class | defs -- |-- |-- |-- | 10 | Average True Range (ATR) | [AverageTrueRange](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volatility.AverageTrueRange) | [average_true_range](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volatility.average_true_range) 11 | Bollinger Bands (BB) | [BollingerBands](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volatility.BollingerBands) | [bollinger_hband](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volatility.bollinger_hband)[bollinger_hband_indicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volatility.bollinger_hband_indicator)[bollinger_lband](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volatility.bollinger_lband)[bollinger_lband_indicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volatility.bollinger_lband_indicator)[bollinger_mavg](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volatility.bollinger_mavg)[bollinger_pband](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volatility.bollinger_pband)[bollinger_wband](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volatility.bollinger_wband) 12 | Keltner Channel (KC) | [KeltnerChannel](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volatility.KeltnerChannel) | [keltner_channel_hband](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volatility.keltner_channel_hband)[keltner_channel_hband_indicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volatility.keltner_channel_hband_indicator)[keltner_channel_lband](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volatility.keltner_channel_lband)[keltner_channel_lband_indicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volatility.keltner_channel_lband_indicator)[keltner_channel_mband](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volatility.keltner_channel_mband)[keltner_channel_pband](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volatility.keltner_channel_pband)[keltner_channel_wband](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volatility.keltner_channel_wband) 13 | Donchian Channel (DC) | [DonchianChannel](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volatility.DonchianChannel)| [donchian_channel_hband](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volatility.donchian_channel_hband)[donchian_channel_lband](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volatility.donchian_channel_lband)[donchian_channel_mban](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volatility.donchian_channel_mband)[donchian_channel_pband](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volatility.donchian_channel_pband)[donchian_channel_wband](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volatility.donchian_channel_wband) 14 | Ulcer Index (UI) | [UlcerIndex](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volatility.UlcerIndex)| [ulcer_index](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.volatility.ulcer_index) ## Trend ID | Name | Class | defs -- |-- |-- |-- | 15 | Simple Moving Average (SMA) | [SMAIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.SMAIndicator) | [sma_indicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.sma_indicator) 16 | Exponential Moving Average (EMA) | [EMAIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.EMAIndicator) | [ema_indicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.ema_indicator) | Trend 17 | Weighted Moving Average (WMA) | [WMAIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.WMAIndicator) | [wma_indicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.wma_indicator) 18 | Moving Average Convergence Divergence (MACD) | [MACD](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.MACD) | [macd](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.macd) [macd_diff](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.macd_diff)[macd_signal](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.macd_signal) 19 | Average Directional Movement Index (ADX) | [ADXIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.ADXIndicator) | [adx](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.adx)[adx_neg](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.adx_neg)[adx_pos](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.adx_pos) 20 | Vortex Indicator (VI) | [VortexIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.VortexIndicator) | [vortex_indicator_neg](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.vortex_indicator_neg) [vortex_indicator_pos](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.vortex_indicator_pos) 21 | Trix (TRIX) | [TRIXIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.TRIXIndicator) | [trix](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.trix) 22 | Mass Index (MI) | [MassIndex](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.MassIndex) | [mass_index](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.mass_index) 23 | Commodity Channel Index (CCI) | [CCIIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.CCIIndicator)| [cci](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.cci) 24 | Detrended Price Oscillator (DPO) | [DPOIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.DPOIndicator) | [dpo](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.dpo) 25 | KST Oscillator (KST) | [KSTIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.KSTIndicator) | [kst](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.kst)[kst_sig](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.kst_sig) 26 | Ichimoku Kinkō Hyō (Ichimoku) | [IchimokuIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.IchimokuIndicator) | [ichimoku_a](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.ichimoku_a)[ichimoku_b](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.ichimoku_b)[ichimoku_base_line](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.ichimoku_base_line)[ichimoku_conversion_line](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.ichimoku_conversion_line) 27 | Parabolic Stop And Reverse (Parabolic SAR) | [PSARIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.PSARIndicator) | [psar_down](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.psar_down) [psar_down_indicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.psar_down_indicator)[psar_up](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.psar_up)[psar_up_indicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.psar_up_indicator) 28 | Schaff Trend Cycle (STC) | [STCIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.STCIndicator) | [stc](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.stc) 29 | Aroon Indicator | [AroonIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.AroonIndicator) | [aroon_down](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.aroon_down)[aroon_up](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.aroon_up) ## Momentum ID | Name | Class | defs -- |-- |-- |-- | 30 | Relative Strength Index (RSI) | [RSIIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.momentum.RSIIndicator) | [rsi](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.momentum.rsi) 31 | Stochastic RSI (SRSI) | [StochRSIIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.momentum.StochRSIIndicator) | [stochrsi](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.momentum.stochrsi)[stochrsi_d](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.momentum.stochrsi_d)[stochrsi_k](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.momentum.stochrsi_k) 32 | True strength index (TSI) | [TSIIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.momentum.TSIIndicator) | [tsi](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.momentum.tsi) 33 | Ultimate Oscillator (UO) | [UltimateOscillator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.momentum.UltimateOscillator) | [ultimate_oscillator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.momentum.ultimate_oscillator) 34 | Stochastic Oscillator (SR) | [StochasticOscillator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.momentum.StochasticOscillator) | [stoch](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.momentum.stoch)[stoch_signal](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.momentum.stoch_signal) 35 | Williams %R (WR) | [WilliamsRIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.momentum.WilliamsRIndicator) | [williams_r](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.momentum.williams_r) 36 | Awesome Oscillator (AO) | [AwesomeOscillatorIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.momentum.AwesomeOscillatorIndicator) | [awesome_oscillator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.momentum.awesome_oscillator) 37 | Kaufman's Adaptive Moving Average (KAMA) | [KAMAIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.momentum.KAMAIndicator) | [kama](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.momentum.kama) 38 | Rate of Change (ROC) | [ROCIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.momentum.ROCIndicator) | [roc](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.momentum.roc) 39 | Percentage Price Oscillator (PPO) | [PercentagePriceOscillator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.momentum.PercentagePriceOscillator) | [ppo](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.momentum.ppo)[ppo_hist](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.momentum.ppo_hist)[ppo_signal](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.momentum.ppo_signal) 40 | Percentage Volume Oscillator (PVO) | [PercentageVolumeOscillator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.momentum.PercentageVolumeOscillator) | [pvo](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.momentum.pvo)[pvo_hist](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.momentum.pvo_hist)[pvo_signal](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.momentum.pvo_signal) ## Others ID | Name | Class | defs -- |-- |-- |-- | 41 | Daily Return (DR) | [DailyReturnIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.others.DailyReturnIndicator) | [daily_return](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.others.daily_return) 42 | Daily Log Return (DLR) | [DailyLogReturnIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.others.DailyLogReturnIndicator) | [daily_log_return](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.others.daily_log_return) 43 | Cumulative Return (CR) | [CumulativeReturnIndicator](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.others.CumulativeReturnIndicator) | [cumulative_return](https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.others.cumulative_return) # Documentation https://technical-analysis-library-in-python.readthedocs.io/en/latest/ # Motivation to use * [English](https://towardsdatascience.com/technical-analysis-library-to-financial-datasets-with-pandas-python-4b2b390d3543) * [Spanish](https://medium.com/datos-y-ciencia/biblioteca-de-an%C3%A1lisis-t%C3%A9cnico-sobre-series-temporales-financieras-para-machine-learning-con-cb28f9427d0) # How to use (Python 3) ```sh $ pip install --upgrade ta ``` To use this library you should have a financial time series dataset including `Timestamp`, `Open`, `High`, `Low`, `Close` and `Volume` columns. You should clean or fill NaN values in your dataset before add technical analysis features. You can get code examples in [examples_to_use](https://github.com/bukosabino/ta/tree/master/examples_to_use) folder. You can visualize the features in [this notebook](https://github.com/bukosabino/ta/blob/master/examples_to_use/visualize_features.ipynb). #### Example adding all features ```python import pandas as pd from ta import add_all_ta_features from ta.utils import dropna # Load datas df = pd.read_csv('ta/tests/data/datas.csv', sep=',') # Clean NaN values df = dropna(df) # Add all ta features df = add_all_ta_features( df, open="Open", high="High", low="Low", close="Close", volume="Volume_BTC") ``` #### Example adding particular feature ```python import pandas as pd from ta.utils import dropna from ta.volatility import BollingerBands # Load datas df = pd.read_csv('ta/tests/data/datas.csv', sep=',') # Clean NaN values df = dropna(df) # Initialize Bollinger Bands Indicator indicator_bb = BollingerBands(close=df["Close"], window=20, window_dev=2) # Add Bollinger Bands features df['bb_bbm'] = indicator_bb.bollinger_mavg() df['bb_bbh'] = indicator_bb.bollinger_hband() df['bb_bbl'] = indicator_bb.bollinger_lband() # Add Bollinger Band high indicator df['bb_bbhi'] = indicator_bb.bollinger_hband_indicator() # Add Bollinger Band low indicator df['bb_bbli'] = indicator_bb.bollinger_lband_indicator() # Add Width Size Bollinger Bands df['bb_bbw'] = indicator_bb.bollinger_wband() # Add Percentage Bollinger Bands df['bb_bbp'] = indicator_bb.bollinger_pband() ``` # Deploy and develop (for developers) ```sh $ git clone https://github.com/bukosabino/ta.git $ cd ta $ pip install -r requirements-play.txt $ make test ``` # Sponsor Thank you to [OpenSistemas](https://opensistemas.com)! It is because of your contribution that I am able to continue the development of this open source library. # Based on * https://en.wikipedia.org/wiki/Technical_analysis * https://pandas.pydata.org * https://github.com/FreddieWitherden/ta * https://github.com/femtotrader/pandas_talib # In Progress * Automated tests for all the indicators. # TODO * Use [NumExpr](https://github.com/pydata/numexpr) to speed up the NumPy/Pandas operations? [Article Motivation](https://towardsdatascience.com/speed-up-your-numpy-and-pandas-with-numexpr-package-25bd1ab0836b) * Add [more technical analysis features](https://en.wikipedia.org/wiki/Technical_analysis). * Wrapper to get financial data. * Use of the Pandas multi-indexing techniques to calculate several indicators at the same time. * Use Plotly/Streamlit to visualize features # Changelog Check the [changelog](https://github.com/bukosabino/ta/blob/master/RELEASE.md) of project. # Donation If you think `ta` library help you, please consider [buying me a coffee](https://www.paypal.me/guau/3). # Credits Developed by Darío López Padial (aka Bukosabino) and [other contributors](https://github.com/bukosabino/ta/graphs/contributors). Please, let me know about any comment or feedback. Also, I am a software engineer freelance focused on Data Science using Python tools such as Pandas, Scikit-Learn, Backtrader, Zipline or Catalyst. Don't hesitate to contact me if you need to develop something related with this library, Python, Technical Analysis, AlgoTrading, Machine Learning, etc. --- ## File: docs/index.rst .. Technical Analysis Library in Python documentation master file, created by sphinx-quickstart on Tue Apr 10 15:47:09 2018. You can adapt this file completely to your liking, but it should at least contain the root `toctree` directive. Welcome to Technical Analysis Library in Python's documentation! ================================================================ It is a Technical Analysis library to financial time series datasets (open, close, high, low, volume). You can use it to do feature engineering from financial datasets. It is built on Python Pandas library. Installation (python >= v3.6) ================================================================ .. code-block:: bash > virtualenv -p python3 virtualenvironment > source virtualenvironment/bin/activate > pip install ta Examples ================== Example adding all features: .. code-block:: python import pandas as pd from ta import add_all_ta_features from ta.utils import dropna # Load datas df = pd.read_csv('ta/tests/data/datas.csv', sep=',') # Clean NaN values df = dropna(df) # Add ta features filling NaN values df = add_all_ta_features( df, open="Open", high="High", low="Low", close="Close", volume="Volume_BTC", fillna=True) Example adding a particular feature: .. code-block:: python import pandas as pd from ta.utils import dropna from ta.volatility import BollingerBands # Load datas df = pd.read_csv('ta/tests/data/datas.csv', sep=',') # Clean NaN values df = dropna(df) # Initialize Bollinger Bands Indicator indicator_bb = BollingerBands(close=df["Close"], window=20, window_dev=2) # Add Bollinger Bands features df['bb_bbm'] = indicator_bb.bollinger_mavg() df['bb_bbh'] = indicator_bb.bollinger_hband() df['bb_bbl'] = indicator_bb.bollinger_lband() # Add Bollinger Band high indicator df['bb_bbhi'] = indicator_bb.bollinger_hband_indicator() # Add Bollinger Band low indicator df['bb_bbli'] = indicator_bb.bollinger_lband_indicator() Motivation ================== * English: https://towardsdatascience.com/technical-analysis-library-to-financial-datasets-with-pandas-python-4b2b390d3543 * Spanish: https://medium.com/datos-y-ciencia/biblioteca-de-an%C3%A1lisis-t%C3%A9cnico-sobre-series-temporales-financieras-para-machine-learning-con-cb28f9427d0 Contents ================== .. toctree:: TA Indices and tables ================== * :ref:`genindex` * :ref:`modindex` * :ref:`search` --- ## File: docs/ta.rst Documentation ************************** .. automodule:: ta Momentum Indicators ========================= Momentum Indicators. .. automodule:: ta.momentum :members: Volume Indicators ========================= Volume Indicators. .. automodule:: ta.volume :members: Volatility Indicators ========================= Volatility Indicators. .. automodule:: ta.volatility :members: Trend Indicators ========================= Trend Indicators. .. automodule:: ta.trend :members: Others Indicators ========================= Others Indicators. .. automodule:: ta.others :members: