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Co-authored-by: jose-donato <zmcdonato@gmail.com>
Co-authored-by: jose-donato <43375532+jose-donato@users.noreply.github.com>
Co-authored-by: andrewkenreich <andrew.kenreich@gmail.com>
2023-10-30 21:01:29 +00:00

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title, description, keywords
title description keywords
acf This page provides a detailed description and source code of acf - an OpenBB function used to plot Auto and Partial Auto Correlation of returns and change in returns. One can understand how to use the function, its parameters, and view examples of its use.
auto correlation
quantitive analysis
quantitative_analysis.qa_view.py
plots
openbb.qa.acf
codes
parameters
returns
examples
stocks.load
GitHub source code

import HeadTitle from '@site/src/components/General/HeadTitle.tsx';

Plots Auto and Partial Auto Correlation of returns and change in returns

Source Code: [link]

openbb.qa.acf(data: pd.DataFrame, target: str, symbol: str = "", lags: int = 15, external_axes: Optional[List[matplotlib.axes._axes.Axes]] = None)

Parameters

Name Type Description Default Optional
data pd.DataFrame Dataframe to look at None False
target str Data column to look at None False
symbol str Name of dataset True
lags int Max number of lags to look at 15 True
external_axes Optional[List[plt.Axes]] External axes (4 axes are expected in the list), by default None None True

Returns

This function does not return anything


Examples

from openbb_terminal.sdk import openbb
df = openbb.stocks.load("AAPL")
openbb.qa.acf(data=df, target="Adj Close")