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https://github.com/OpenBB-finance/OpenBB.git
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6dea3a931a
* Fixes * Added better handling * Adds more handling * Adds more handling * Added screener handling * Added fixes * Added fixes
110 lines
2.6 KiB
Python
110 lines
2.6 KiB
Python
"""Volume Technical Analysis"""
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__docformat__ = "numpy"
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import logging
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import pandas as pd
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import pandas_ta as ta
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from openbb_terminal.decorators import log_start_end
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from openbb_terminal.common.technical_analysis import ta_helpers
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from openbb_terminal.rich_config import console
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logger = logging.getLogger(__name__)
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@log_start_end(log=logger)
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def ad(data: pd.DataFrame, use_open: bool = False) -> pd.DataFrame:
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"""Calculate AD technical indicator
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Parameters
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----------
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data : pd.DataFrame
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Dataframe of prices with OHLC and Volume
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use_open : bool
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Whether to use open prices
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Returns
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-------
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pd.DataFrame
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Dataframe with technical indicator
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"""
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kwargs = {}
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if use_open:
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kwargs["Open"] = data["Open"]
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df_ta = ta.ad(
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high=data["High"],
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low=data["Low"],
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close=data["Close"],
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volume=data["Volume"],
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**kwargs
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).dropna()
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return pd.DataFrame(df_ta)
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@log_start_end(log=logger)
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def adosc(
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data: pd.DataFrame, use_open: bool = False, fast: int = 3, slow: int = 10
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) -> pd.DataFrame:
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"""Calculate AD oscillator technical indicator
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Parameters
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----------
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data : pd.DataFrame
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Dataframe of OHLC prices
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use_open : bool
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Whether to use open prices
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fast: int
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Fast value
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slow: int
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Slow value
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Returns
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-------
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pd.DataFrame
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Dataframe with technical indicator
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"""
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if use_open:
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df_ta = ta.adosc(
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high=data["High"],
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low=data["Low"],
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close=data["Close"],
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volume=data["Volume"],
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open_=data["Open"],
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fast=fast,
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slow=slow,
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).dropna()
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else:
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df_ta = ta.adosc(
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high=data["High"],
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low=data["Low"],
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close=data["Close"],
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volume=data["Volume"],
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fast=fast,
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slow=slow,
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).dropna()
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return pd.DataFrame(df_ta)
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@log_start_end(log=logger)
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def obv(data: pd.DataFrame) -> pd.DataFrame:
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"""On Balance Volume
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Parameters
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----------
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data: pd.DataFrame
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Dataframe of OHLC prices
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Returns
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-------
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pd.DataFrame
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Dataframe with technical indicator
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"""
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close_col = ta_helpers.check_columns(data, high=False, low=False)
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if close_col is None:
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return pd.DataFrame()
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if "Volume" not in data.columns:
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console.print("[red]Volume column not found[/red]\n")
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return pd.DataFrame()
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return pd.DataFrame(ta.obv(close=data[close_col], volume=data["Volume"]).dropna())
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