Candle

---

Doji

Attempts to identify a "Doji" candle which is shorter than 10% of the average of the 10 previous bars High-Low range.

Sources

• TA Lib

Parameters:

Name	Type	Description	Default
open_	Series	open Series	required
high	Series	high Series	required
low	Series	low Series	required
close	Series	close Series	required
length	int	The period. Default: 10	None
factor	float	Doji value. Default: 100	None
scalar	float	Scalar. Default: 100	None
asint	bool	Returns as Int. Default: True	None
offset	int	Post shift. Default: 0	None

Other Parameters:

Name	Type	Description
naive	bool	Prefills potential Doji; bodies that are less than a percentage, factor, of it's High-Low range. Default: False
fillna	value	Replaces na's with value.

Returns:

Type	Description
Series	1 column

Warning

TA-Lib Correlation: np.float64(0.9434563530497265)

Tip

Corrective contributions welcome!

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Inside Bar

Attempts to identify an "Inside" candle which is smaller than it's previous candle.

Sources

• TA Lib
• tradingview

Parameters:

Name	Type	Description	Default
open_	Series	open Series	required
high	Series	high Series	required
low	Series	low Series	required
close	Series	close Series	required
asbool	bool	Return booleans. Default: False	None
scalar	float	Scalar. Default: 100	None
offset	int	Post shift. Default: 0	None

Other Parameters:

Name	Type	Description
fillna	value	Replaces na's with value.

Returns:

Type	Description
Series	1 column

---

Candle Pattern

This function wraps TA Lib candle patterns.

Sources

• TA Lib

Parameters:

Name	Type	Description	Default
open_	Series	open Series	required
high	Series	high Series	required
low	Series	low Series	required
close	Series	close Series	required
name	Union[str, List[str]]	Pattern name or a list of pattern names. Default: "all"	'all'
scalar	float	Scalar. Default: 100	None
offset	int	Post shift. Default: 0	None

Other Parameters:

Name	Type	Description
fillna	value	Replaces na's with value.

Returns:

Type	Description
DataFrame	Pattern Column(s)

TA Lib

TA Lib must be installed

NOTICE

Thanks to all those that have sponsored and dontated to the library in the past! Your support has been greatly appreciated!

However, future releases are on definite hold until 100+ donations of $150+ have been received via Buy Me a Coffee.

Help keep this library and application the best in it's class!

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Z Candles

Creates candlesticks using a rolling Z Score.

Sources

• Kevin Johnson

Parameters:

Name	Type	Description	Default
open_	Series	open Series	required
high	Series	high Series	required
low	Series	low Series	required
close	Series	close Series	required
length	int	The period. Default: 10	None
full	bool	Apply length to whole DataFrame. Default: False	None
ddof	int	By default, uses Pandas ddof=1. For Numpy calculation, use 0. Default: 1	None
offset	int	Post shift. Default: 0	None

Other Parameters:

Name	Type	Description
naive	bool	If True, prefills potential Doji less than the length if it less than a percentage of it's High-Low range. Default: False
fillna	value	Replaces na's with value.

Returns:

Type	Description
DataFrame	4 columns

Note

• Numpy std() ddof explanation.

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Heikin Ashi Candles

Creates Japanese ohlc candlesticks that attempts to filter out market noise. Developed by Munehisa Homma in the 1700s, Heikin Ashi Candles share some characteristics with standard candlestick charts but creates a smoother candlestick appearance.

Sources

• Investopedia

Parameters:

Name	Type	Description	Default
open_	Series	open Series	required
high	Series	high Series	required
low	Series	low Series	required
close	Series	close Series	required
offset	int	Post shift. Default: 0	None

Other Parameters:

Name	Type	Description
fillna	value	Replaces na's with value.

Returns:

Type	Description
DataFrame	4 columns