How do I add a trendline to stock price data in Python?

Question

I am attempting to make (i.e. calculate and plot) a trendline for stock price data in python. So far, I have tried using numpy's polyfit function. However, it doesn't work for me, because I can't seem to define the y-axis... At this point, I imagine it is helpful to show the data that I'm dealing with:

import yfinance as yf
import matplotlib.pyplot as plt

#get the price data for the stock
data = yf.download("AAPL","1990-01-01","2021-01-01")

#plot the data
plt.plot(data["Adj Close"])
plt.show()

Any ideas that could help me would be much appreciated!

Answer 1

1- Using ployfit to fit a polynomial line (for example with degree 2 , a degree of 1 will be linear line)

import numpy as np 
import seaborn as sns

# create numpy array to fint regression line
x = np.arange(data["Adj Close"].size)
fit = np.polyfit(x, data["Adj Close"], deg=2)
fit_function = np.poly1d(fit)

sns.lineplot(data=data["Adj Close"]);
#Linear regression plot
sns.lineplot(x=data["Adj Close"].index ,y=fit_function(x))

Or you can get the trend of time series via STL decomposition

!pip install stldecompose

from stldecompose import decompose

decomp = decompose(data["Adj Close"].values)
trend = decomp.trend

sns.lineplot(data=data["Adj Close"]);
sns.lineplot(x=data["Adj Close"].index ,y=trend)