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Technical Analysis Library Time-Series

Project description

— title: jhTAlib author: Joost Hoeks date: 2019-06-10 —

# jhTAlib Technical Analysis Library Time-Series

You can use and import it for your:

  • Technical Analysis Software
  • Charting Software
  • Backtest Software
  • Trading Robot Software
  • Trading Software in general

Work in progress…

## Depends only on

## Docs

## Install From [PyPI](https://pypi.org/project/jhTAlib/):

` $ [sudo] pip3 install jhtalib `

From [source](https://github.com/joosthoeks/jhTAlib):

` $ git clone https://github.com/joosthoeks/jhTAlib.git $ cd jhTAlib $ [sudo] pip3 install -e . `

## Update From [PyPI](https://pypi.org/project/jhTAlib/):

` $ [sudo] pip3 install --upgrade jhtalib `

From [source](https://github.com/joosthoeks/jhTAlib):

` $ cd jhTAlib $ git pull [upstream master] `

## Examples

` $ cd example/ `

### Example 1

` $ python3 example-1-plot.py `

or

[https://colab.research.google.com/github/joosthoeks/jhTAlib/blob/master/example/example-1-plot.ipynb](https://colab.research.google.com/github/joosthoeks/jhTAlib/blob/master/example/example-1-plot.ipynb)

### Example 2

` $ python3 example-2-plot.py `

or

[https://colab.research.google.com/github/joosthoeks/jhTAlib/blob/master/example/example-2-plot.ipynb](https://colab.research.google.com/github/joosthoeks/jhTAlib/blob/master/example/example-2-plot.ipynb)

### Example 3

` $ python3 example-3-plot.py `

or

[https://colab.research.google.com/github/joosthoeks/jhTAlib/blob/master/example/example-3-plot.ipynb](https://colab.research.google.com/github/joosthoeks/jhTAlib/blob/master/example/example-3-plot.ipynb)

### Example 4

` $ python3 example-4-plot-quandl.py `

or

[https://colab.research.google.com/github/joosthoeks/jhTAlib/blob/master/example/example-4-plot-quandl.ipynb](https://colab.research.google.com/github/joosthoeks/jhTAlib/blob/master/example/example-4-plot-quandl.ipynb)

### Example 5

` $ python3 example-5-plot-quandl.py `

or

[https://colab.research.google.com/github/joosthoeks/jhTAlib/blob/master/example/example-5-plot-quandl.ipynb](https://colab.research.google.com/github/joosthoeks/jhTAlib/blob/master/example/example-5-plot-quandl.ipynb)

### Example 6

` $ python3 example-6-plot-quandl.py `

or

[https://colab.research.google.com/github/joosthoeks/jhTAlib/blob/master/example/example-6-plot-quandl.ipynb](https://colab.research.google.com/github/joosthoeks/jhTAlib/blob/master/example/example-6-plot-quandl.ipynb)

### Example 7

` $ python3 example-7-quandl-2-df.py `

or

[https://colab.research.google.com/github/joosthoeks/jhTAlib/blob/master/example/example-7-quandl-2-df.ipynb](https://colab.research.google.com/github/joosthoeks/jhTAlib/blob/master/example/example-7-quandl-2-df.ipynb)

### Example 8

` $ python3 example-8-alphavantage-2-df.py `

or

[https://colab.research.google.com/github/joosthoeks/jhTAlib/blob/master/example/example-8-alphavantage-2-df.ipynb](https://colab.research.google.com/github/joosthoeks/jhTAlib/blob/master/example/example-8-alphavantage-2-df.ipynb)

### Example 9

` $ python3 example-9-cryptocompare-2-df.py `

or

[https://colab.research.google.com/github/joosthoeks/jhTAlib/blob/master/example/example-9-cryptocompare-2-df.ipynb](https://colab.research.google.com/github/joosthoeks/jhTAlib/blob/master/example/example-9-cryptocompare-2-df.ipynb)

### Example 10

DF NumPy Pandas

[https://colab.research.google.com/github/joosthoeks/jhTAlib/blob/master/example/example-10-df-numpy-pandas.ipynb](https://colab.research.google.com/github/joosthoeks/jhTAlib/blob/master/example/example-10-df-numpy-pandas.ipynb)

### Example 11

Basic Usage

[https://colab.research.google.com/github/joosthoeks/jhTAlib/blob/master/example/example-11-basic-usage.ipynb](https://colab.research.google.com/github/joosthoeks/jhTAlib/blob/master/example/example-11-basic-usage.ipynb)

## Test

` $ cd test/ $ python3 test.py `

## Reference

` import jhtalib as jhta `

### [Behavioral Techniques](https://github.com/joosthoeks/jhTAlib/blob/master/jhtalib/behavioral_techniques/behavioral_techniques.py)

#### ATH | All Time High | DONE

  • `dict of lists of floats = jhta.ATH(df, price='High')`

#### LMC | Last Major Correction | DONE

  • `dict of lists of floats = jhta.LMC(df, price='Low')`

#### PP | Pivot Point | DONE

#### FIBOPR | Fibonacci Price Retracements | DONE

  • `dict of lists of floats = jhta.FIBOPR(df, price='Close')`

#### FIBTR | Fibonacci Time Retracements |

#### GANNPR | W. D. Gann Price Retracements | DONE

  • `dict of lists of floats = jhta.GANNPR(df, price='Close')`

#### GANNTR | W. D. Gann Time Retracements |

#### JDN | Julian Day Number | DONE

#### JD | Julian Date | DONE

#### SUNC | Sun Cycle |

#### MERCURYC | Mercury Cycle |

#### VENUSC | Venus Cycle |

#### EARTHC | Earth Cycle |

#### MARSC | Mars Cycle |

#### JUPITERC | Jupiter Cycle |

#### SATURNC | Saturn Cycle |

#### URANUSC | Uranus Cycle |

#### NEPTUNEC | Neptune Cycle |

#### PLUTOC | Pluto Cycle |

#### MOONC | Moon Cycle |

### [Candlestick](https://github.com/joosthoeks/jhTAlib/blob/master/jhtalib/candlestick/candlestick.py)

#### CDLBODYS | Candle Body Size | DONE

#### CDLWICKS | Candle Wick Size | DONE

#### CDLUPPSHAS | Candle Upper Shadow Size | DONE

#### CDLLOWSHAS | Candle Lower Shadow Size | DONE

#### CDLBODYP | Candle Body Percent | DONE

  • `list of floats = jhta.CDLBODYP(p)`

#### CDLBODYM | Candle Body Momentum | DONE

  • `list of floats = jhta.CDLBODYM(df, n)`
  • book: Trading Systems and Methods

#### QSTICK | Qstick | DONE

#### SHADOWT | Shadow Trends | DONE

  • `dict of lists of floats = jhta.SHADOWT(df, n)`
  • book: The New Technical Trader

#### IMI | Intraday Momentum Index | DONE

### [Cycle Indicators](https://github.com/joosthoeks/jhTAlib/blob/master/jhtalib/cycle_indicators/cycle_indicators.py)

#### HT_DCPERIOD | Hilbert Transform - Dominant Cycle Period |

#### HT_DCPHASE | Hilbert Transform - Dominant Cycle Phase |

#### HT_PHASOR | Hilbert Transform - Phasor Components |

#### HT_SINE | Hilbert Transform - SineWave |

#### HT_TRENDLINE | Hilbert Transform - Instantaneous Trendline |

#### HT_TRENDMODE | Hilbert Transform - Trend vs Cycle Mode |

#### TS | Trend Score | DONE

### [Data](https://github.com/joosthoeks/jhTAlib/blob/master/jhtalib/data/data.py)

#### CSV2DF | CSV file 2 DataFeed | DONE

  • `dict of tuples of floats = jhta.CSV2DF(csv_file_path)`

#### CSVURL2DF | CSV file url 2 DataFeed | DONE

  • `dict of tuples of floats = jhta.CSVURL2DF(csv_file_url)`

#### DF2CSV | DataFeed 2 CSV file | DONE

  • `csv file = jhta.DF2CSV(df, csv_file_path)`

#### DF2DFREV | DataFeed 2 DataFeed Reversed | DONE

  • `dict of tuples of floats = jhta.DF2DFREV(df)`

#### DF2DFWIN | DataFeed 2 DataFeed Window | DONE

  • `dict of tuples of floats = jhta.DF2DFWIN(df, start=0, end=10)`

#### DF_HEAD | DataFeed HEAD | DONE

  • `dict of tuples of floats = jhta.DF_HEAD(df, n=5)`

#### DF_TAIL | DataFeed TAIL | DONE

  • `dict of tuples of floats = jhta.DF_TAIL(df, n=5)`

#### DF2HEIKIN_ASHI | DataFeed 2 Heikin-Ashi DataFeed | DONE

  • `dict of tuples of floats = jhta.DF2HEIKIN_ASHI(df)`

### [Event Driven](https://github.com/joosthoeks/jhTAlib/blob/master/jhtalib/event_driven/event_driven.py)

#### ASI | Accumulation Swing Index (J. Welles Wilder) | DONE

  • `list of floats = jhta.ASI(df, L)`
  • book: New Concepts in Technical Trading Systems

#### SI | Swing Index (J. Welles Wilder) | DONE

  • `list of floats = jhta.SI(df, L)`
  • book: New Concepts in Technical Trading Systems

### [Experimental](https://github.com/joosthoeks/jhTAlib/blob/master/jhtalib/experimental/experimental.py)

#### JH_SAVGP | Swing Average Price - previous Average Price | DONE

  • `list of floats = jhta.JH_SAVGP(df)`

#### JH_SAVGPS | Swing Average Price - previous Average Price Summation | DONE

  • `list of floats = jhta.JH_SAVGPS(df)`

#### JH_SCO | Swing Close - Open | DONE

  • `list of floats = jhta.JH_SCO(df)`

#### JH_SCOS | Swing Close - Open Summation | DONE

  • `list of floats = jhta.JH_SCOS(df)`

#### JH_SMEDP | Swing Median Price - previous Median Price | DONE

  • `list of floats = jhta.JH_SMEDP(df)`

#### jh_SMEDPS | Swing Median Price - previous Median Price Summation | DONE

  • `list of floats = jhta.JH_SMEDPS(df)`

#### JH_SPP | Swing Price - previous Price | DONE

  • `list of floats = jhta.JH_SPP(df, price='Close')`

#### JH_SPPS | Swing Price - previous Price Summation | DONE

  • `list of floats = jhta.JH_SPPS(df, price='Close')`

#### JH_STYPP | Swing Typical Price - previous Typical Price | DONE

  • `list of floats = jhta.JH_STYPP(df)`

#### JH_STYPPS | Swing Typical Price - previous Typical Price Summation | DONE

  • `list of floats = jhta.JH_STYPPS(df)`

#### JH_SWCLP | Swing Weighted Close Price - previous Weighted Close Price | DONE

  • `list of floats = jhta.JH_SWCLP(df)`

#### JH_SWCLPS | Swing Weighted Close Price - previous Weighted Close Price Summation | DONE

  • `list of floats = jhta.JH_SWCLPS(df)`

### [General](https://github.com/joosthoeks/jhTAlib/blob/master/jhtalib/general/general.py)

#### NORMALIZE | Normalize | DONE

#### STANDARDIZE | Standardize | DONE

#### SPREAD | Spread | DONE

  • `list of floats = jhta.SPREAD(df1, df2, price1='Close', price2='Close')`

#### CP | Comparative Performance | DONE

#### CRSI | Comparative Relative Strength Index | DONE

#### CS | Comparative Strength | DONE

#### HR | Hit Rate / Win Rate | DONE

#### PLR | Profit/Loss Ratio | DONE

#### EV | Expected Value | DONE

#### POR | Probability of Ruin (Table of Lucas and LeBeau) | DONE

  • `int = jhta.POR(hitrade_float, profit_loss_ratio_float)`
  • book: Computer Analysis of the Futures Markets

### [Information](https://github.com/joosthoeks/jhTAlib/blob/master/jhtalib/information/information.py)

#### INFO | Print df Information | DONE

  • `print = jhta.INFO(df, price='Close')`

#### INFO_TRADES | Print Trades Information | DONE

  • `print = jhta.INFO_TRADES(profit_trades_list, loss_trades_list)`

### [Math Functions](https://github.com/joosthoeks/jhTAlib/blob/master/jhtalib/math_functions/math_functions.py)

#### EXP | Exponential | DONE

  • `list of floats = jhta.EXP(df, price='Close')`

#### LOG | Logarithm | DONE

  • `list of floats = jhta.LOG(df, price='Close')`

#### LOG10 | Base-10 Logarithm | DONE

  • `list of floats = jhta.LOG10(df, price='Close')`

#### SQRT | Square Root | DONE

  • `list of floats = jhta.SQRT(df, price='Close')`

#### ACOS | Arc Cosine | DONE

  • `list of floats = jhta.ACOS(df, price='Close')`

#### ASIN | Arc Sine | DONE

  • `list of floats = jhta.ASIN(df, price='Close')`

#### ATAN | Arc Tangent | DONE

  • `list of floats = jhta.ATAN(df, price='Close')`

#### COS | Cosine | DONE

  • `list of floats = jhta.COS(df, price='Close')`

#### SIN | Sine | DONE

  • `list of floats = jhta.SIN(df, price='Close')`

#### TAN | Tangent | DONE

  • `list of floats = jhta.TAN(df, price='Close')`

#### ACOSH | Inverse Hyperbolic Cosine | DONE

  • `list of floats = jhta.ACOSH(df, price='Close')`

#### ASINH | Inverse Hyperbolic Sine | DONE

  • `list of floats = jhta.ASINH(df, price='Close')`

#### ATANH | Inverse Hyperbolic Tangent | DONE

  • `list of floats = jhta.ATANH(df, price='Close')`

#### COSH | Hyperbolic Cosine | DONE

  • `list of floats = jhta.COSH(df, price='Close')`

#### SINH | Hyperbolic Sine | DONE

  • `list of floats = jhta.SINH(df, price='Close')`

#### TANH | Hyperbolic Tangent | DONE

  • `list of floats = jhta.TANH(df, price='Close')`

#### PI | Mathematical constant PI | DONE

  • `float = jhta.PI()`

#### E | Mathematical constant E | DONE

  • `float = jhta.E()`

#### TAU | Mathematical constant TAU | DONE

  • `float = jhta.TAU()`

#### PHI | Mathematical constant PHI | DONE

  • `float = jhta.PHI()`

#### FIB | Fibonacci series up to n | DONE

  • `list of ints = jhta.FIB(n)`

#### CEIL | Ceiling | DONE

  • `list of floats = jhta.CEIL(df, price='Close')`

#### FLOOR | Floor | DONE

  • `list of floats = jhta.FLOOR(df, price='Close')`

#### DEGREES | Radians to Degrees | DONE

  • `list of floats = jhta.DEGREES(df, price='Close')`

#### RADIANS | Degrees to Radians | DONE

  • `list of floats = jhta.RADIANS(df, price='Close')`

#### ADD | Addition High + Low | DONE

  • `list of floats = jhta.ADD(df)`

#### DIV | Division High / Low | DONE

  • `list of floats = jhta.DIV(df)`

#### MAX | Highest value over a specified period | DONE

  • `list of floats = jhta.MAX(df, n, price='Close')`

#### MAXINDEX | Index of highest value over a specified period | DONE

  • `list of ints = jhta.MAXINDEX(df, n, price='Close')`

#### MIN | Lowest value over a specified period | DONE

  • `list of floats = jhta.MIN(df, n, price='Close')`

#### MININDEX | Index of lowest value over a specified period | DONE

  • `list of ints = jhta.MININDEX(df, n, price='Close')`

#### MINMAX | Lowest and Highest values over a specified period | DONE

  • `dict of lists of floats = jhta.MINMAX(df, n, price='Close')`

#### MINMAXINDEX | Indexes of lowest and highest values over a specified period | DONE

  • `dict of lists of ints = jhta.MINMAXINDEX(df, n, price='Close')`

#### MULT | Multiply High * Low | DONE

  • `list of floats = jhta.MULT(df)`

#### SUB | Subtraction High - Low | DONE

  • `list of floats = jhta.SUB(df)`

#### SUM | Summation | DONE

  • `list of floats = jhta.SUM(df, n, price='Close')`

### [Momentum Indicators](https://github.com/joosthoeks/jhTAlib/blob/master/jhtalib/momentum_indicators/momentum_indicators.py)

#### ADX | Average Directional Movement Index |

#### ADXR | Average Directional Movement Index Rating |

#### APO | Absolute Price Oscillator | DONE

#### AROON | Aroon |

#### AROONOSC | Aroon Oscillator |

#### BOP | Balance Of Power |

#### CCI | Commodity Channel Index |

#### CMO | Chande Momentum Oscillator |

#### DX | Directional Movement Index |

#### MACD | Moving Average Convergence/Divergence |

#### MACDEXT | MACD with controllable MA type |

#### MACDFIX | Moving Average Convergence/Divergence Fix 12/26 |

#### MFI | Money Flow Index |

#### MINUS_DI | Minus Directional Indicator |

#### MINUS_DM | Minus Directional Movement |

#### MOM | Momentum | DONE

#### PLUS_DI | Plus Directional Indicator |

#### PLUS_DM | Plus Directional Movement |

#### PPO | Percentage Price Oscillator |

#### RMI | Relative Momentum Index | DONE

#### ROC | Rate of Change | DONE

  • `list of floats = jhta.ROC(df, n, price='Close')`

#### ROCP | Rate of Change Percentage | DONE

  • `list of floats = jhta.ROCP(df, n, price='Close')`

#### ROCR | Rate of Change Ratio | DONE

  • `list of floats = jhta.ROCR(df, n, price='Close')`

#### ROCR100 | Rate of Change Ratio 100 scale | DONE

#### RSI | Relative Strength Index | DONE

#### STOCH | Stochastic | DONE

#### STOCHF | Stochastic Fast |

#### STOCHRSI | Stochastic Relative Strength Index |

#### TRIX | 1-day Rate-Of-Change (ROC) of a Triple Smooth EMA |

#### ULTOSC | Ultimate Oscillator |

#### WILLR | Williams’ %R | DONE

### [Overlap Studies](https://github.com/joosthoeks/jhTAlib/blob/master/jhtalib/overlap_studies/overlap_studies.py)

#### BBANDS | Bollinger Bands | DONE

#### BBANDW | Bollinger Band Width | DONE

#### DEMA | Double Exponential Moving Average |

#### EMA | Exponential Moving Average | DONE

#### ENVP | Envelope Percent | DONE

#### KAMA | Kaufman Adaptive Moving Average |

#### MA | Moving Average |

#### MAMA | MESA Adaptive Moving Average |

#### MAVP | Moving Average with Variable Period |

#### MIDPOINT | MidPoint over period | DONE

#### MIDPRICE | MidPoint Price over period | DONE

#### MMR | Mayer Multiple Ratio | DONE

#### SAR | Parabolic SAR | DONE

  • `list of floats = jhta.SAR(df, af_step=.02, af_max=.2)`
  • book: New Concepts in Technical Trading Systems

#### SAREXT | Parabolic SAR - Extended |

#### SMA | Simple Moving Average | DONE

#### T3 | Triple Exponential Moving Average (T3) |

#### TEMA | Triple Exponential Moving Average |

#### TRIMA | Triangular Moving Average | DONE

#### WMA | Weighted Moving Average

### [Pattern Recognition](https://github.com/joosthoeks/jhTAlib/blob/master/jhtalib/pattern_recognition/pattern_recognition.py)

#### CDL2CROWS | Two Crows |

#### CDL3BLACKCROWS | Three Black Crows |

#### CDL3INSIDE | Three Inside Up/Down |

#### CDL3LINESTRIKE | Three-Line Strike |

#### CDL3OUTSIDE | Three Outside Up/Down |

#### CDL3STARSINSOUTH | Three Stars In The South |

#### CDL3WHITESOLDIERS | Three Advancing White Soldiers |

#### CDLABANDONEDBABY | Abandoned Baby |

#### CDLADVANCEBLOCK | Advance Block |

#### CDLBELTHOLD | Belt-hold |

#### CDLBREAKAWAY | Breakaway |

#### CDLCLOSINGMARUBOZU | Closing Marubozu |

#### CDLCONSEALBABYSWALL | Concealing Baby Swallow |

#### CDLCOUNTERATTACK | Counterattack |

#### CDLDARKCLOUDCOVER | Dark Cloud Cover |

#### CDLDOJI | Doji |

#### CDLDOJISTAR | Doji Star |

#### CDLDRAGONFLYDOJI | Dragonfly Doji |

#### CDLENGULFING | Engulfing Pattern |

#### CDLEVENINGDOJISTAR | Evening Doji Star |

#### CDLEVENINGSTAR | Evening Star |

#### CDLGAPSIDESIDEWHITE | Up/Down-gap side-by-side white lines |

#### CDLGRAVESTONEDOJI | Gravestone Doji |

#### CDLHAMMER | Hammer |

#### CDLHANGINGMAN | Hanging Man |

#### CDLHARAMI | Harami Pattern |

#### CDLHARAMICROSS | Harami Cross Pattern |

#### CDLHIGHWAVE | High-Wave Candle |

#### CDLHIKKAKE | Hikkake Pattern |

#### CDLHIKKAKEMOD | Modified Hikkake Pattern |

#### CDLHOMINGPIGEON | Homing Pigeon |

#### CDLIDENTICAL3CROWS | Identical Three Crows |

#### CDLINNECK | In-Neck Pattern |

#### CDLINVERTEDHAMMER | Inverted Hammer |

#### CDLKICKING | Kicking |

#### CDLKICKINGBYLENGTH | Kicking - bull/bear determined by the longer marubozu |

#### CDLLADDERBOTTOM | Ladder Bottom |

#### CDLLONGLEGGEDDOJI | Long Legged Doji |

#### CDLLONGLINE | Long Line Candle |

#### CDLMARUBOZU | Marubozu |

#### CDLMATCHINGLOW | Matching Low |

#### CDLMATHOLD | Mat Hold |

#### CDLMORNINGDOJISTAR | Morning Doji Star |

#### CDLMORNINGSTAR | Morning Star |

#### CDLONNECK | On-Neck Pattern |

#### CDLPIERCING | Piercing Pattern |

#### CDLRICKSHAWMAN | Rickshaw Man |

#### CDLRISEFALL3METHODS | Rising/Falling Three Methods |

#### CDLSEPARATINGLINES | Separating Lines |

#### CDLSHOOTINGSTAR | Shooting Star |

#### CDLSHORTLINE | Short Line Candle |

#### CDLSPINNINGTOP | Spinning Top |

#### CDLSTALLEDPATTERN | Stalled Pattern |

#### CDLSTICKSANDWICH | Stick Sandwich |

#### CDLTAKURI | Takuri (Dragonfly Doji with very long lower shadow) |

#### CDLTASUKIGAP | Tasuki Gap |

#### CDLTHRUSTING | Thrusting Pattern |

#### CDLTRISTAR | Tristar Pattern |

#### CDLUNIQUE3RIVER | Unique 3 River |

#### CDLUPSIDEGAP2CROWS | Upside Gap Two Crows |

#### CDLXSIDEGAP3METHODS | Upside/Downside Gap Three Methods |

### [Price Transform](https://github.com/joosthoeks/jhTAlib/blob/master/jhtalib/price_transform/price_transform.py)

#### AVGPRICE | Average Price | DONE

#### MEDPRICE | Median Price | DONE

#### TYPPRICE | Typical Price | DONE

#### WCLPRICE | Weighted Close Price | DONE

### [Statistic Functions](https://github.com/joosthoeks/jhTAlib/blob/master/jhtalib/statistic_functions/statistic_functions.py)

#### MEAN | Arithmetic mean (average) of data | DONE

  • `list of floats = jhta.MEAN(df, n, price='Close')`

#### HARMONIC_MEAN | Harmonic mean of data | DONE

  • `list of floats = jhta.HARMONIC_MEAN(df, n, price='Close')`

#### MEDIAN | Median (middle value) of data | DONE

  • `list of floats = jhta.MEDIAN(df, n, price='Close')`

#### MEDIAN_LOW | Low median of data | DONE

  • `list of floats = jhta.MEDIAN_LOW(df, n, price='Close')`

#### MEDIAN_HIGH | High median of data | DONE

  • `list of floats = jhta.MEDIAN_HIGH(df, n, price='Close')`

#### MEDIAN_GROUPED | Median, or 50th percentile, of grouped data | DONE

  • `list of floats = jhta.MEDIAN_GROUPED(df, n, price='Close', interval=1)`

#### MODE | Mode (most common value) of discrete data | DONE

  • `list of floats = jhta.MODE(df, n, price='Close')`

#### PSTDEV | Population standard deviation of data | DONE

  • `list of floats = jhta.PSTDEV(df, n, price='Close', mu=None)`

#### PVARIANCE | Population variance of data | DONE

  • `list of floats = jhta.PVARIANCE(df, n, price='Close', mu=None)`

#### STDEV | Sample standard deviation of data | DONE

  • `list of floats = jhta.STDEV(df, n, price='Close', xbar=None)`

#### VARIANCE | Sample variance of data | DONE

  • `list of floats = jhta.VARIANCE(df, n, price='Close', xbar=None)`

#### COV | Covariance | DONE

#### COVARIANCE | Covariance | DONE

#### COR | Correlation | DONE

  • `float = jhta.COR(list1, list2)`

#### CORRELATION | Correlation | DONE

  • `list of floats = jhta.CORRELATION(df1, df2, n, price1='Close', price2='Close')`

#### PCOR | Population Correlation | DONE

  • `float = jhta.PCOR(list1, list2)`

#### PCORRELATION | Population Correlation | DONE

  • `list of floats = jhta.PCORRELATION(df1, df2, n, price1='Close', price2='Close')`

#### BETA | Beta | DONE

#### BETAS | Betas | DONE

#### LSR | Least Squares Regression | DONE

#### SLR | Simple Linear Regression | DONE

### [Uncategorised](https://github.com/joosthoeks/jhTAlib/blob/master/jhtalib/uncategorised/uncategorised.py)

### [Volatility Indicators](https://github.com/joosthoeks/jhTAlib/blob/master/jhtalib/volatility_indicators/volatility_indicators.py)

#### ATR | Average True Range | DONE

#### NATR | Normalized Average True Range |

#### RVI | Relative Volatility Index | DONE

#### INERTIA | Inertia |

#### TRANGE | True Range | DONE

### [Volume Indicators](https://github.com/joosthoeks/jhTAlib/blob/master/jhtalib/volume_indicators/volume_indicators.py)

#### AD | Chaikin A/D Line | DONE

#### ADOSC | Chaikin A/D Oscillator |

#### OBV | On Balance Volume | DONE

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