SpiralDevelopment / Candlestick Patterns
Licence: mit
Candlestick patterns detector
Stars: ✭ 132
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python
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candlestick-patterns
Candlestick patterns detector
Available patterns
- Inverted Hammer
- Hammer
- Hanging man
- Bearish/Bullish Harami
- Dark cloud cover
- Doji
- Doji Star
- Dragonfly doji
- Gravestone doji
- Bearish engulfing
- Bullish engulfing
- Morning star
- Morning star doji
- Piercing pattern
- Rain drop
- Rain drop doji
- Star
- Shooting star
How to use
Dataframe requirements
- Dataframe must contain open, high, low and close prices
- Open, high, low and close prices must be in numeric type.
Dataframe Example:
| time | open | high | low | close |
|---|---|---|---|---|
| 2019-12-24 00:00:00 | 7317.3 | 7436.68 | 7157.04 | 7255.77 |
| 2019-12-25 00:00:00 | 7255.77 | 7271.77 | 7128.86 | 7204.63 |
| 2019-12-26 00:00:00 | 7205.01 | 7435 | 7157.12 | 7202 |
| 2019-12-27 00:00:00 | 7202 | 7275.86 | 7076.42 | 7254.74 |
| 2019-12-28 00:00:00 | 7254.77 | 7365.01 | 7238.67 | 7316.14 |
| 2019-12-29 00:00:00 | 7315.36 | 7528.45 | 7288 | 7388.24 |
Code
from candlestick import candlestick
df = candlestick.inverted_hammer(df, target='result')
Result
| T | result | open | high | low | close |
|---|---|---|---|---|---|
| 2019-12-24 00:00:00 | False | 7317.3 | 7436.68 | 7157.04 | 7255.77 |
| 2019-12-25 00:00:00 | False | 7255.77 | 7271.77 | 7128.86 | 7204.63 |
| 2019-12-26 00:00:00 | True | 7205.01 | 7435 | 7157.12 | 7202 |
| 2019-12-27 00:00:00 | False | 7202 | 7275.86 | 7076.42 | 7254.74 |
| 2019-12-28 00:00:00 | False | 7254.77 | 7365.01 | 7238.67 | 7316.14 |
| 2019-12-29 00:00:00 | False | 7315.36 | 7528.45 | 7288 | 7388.24 |
"True" indicates that pattern is detected at that candle
Parametrs
All pattern detection methods receive 3 parametrs:
- target (String) - Indicates the column to which the result of detection is saved as boolean.
- is_reversed (Bool) - Pass True if rows in dataframe are in time descending order, otherwise False. Deafult is False.
- ohlc (List) - Pass list of strings which indicates the column names of open/high/low/close prices in dataframe. Default: ["open", "high", "low", "close"].
Support
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