Plotting 5-Day and 20-Day Moving Averages of Stock Prices with Python

The article explains how to use Python to draw the 5‑day and 20‑day moving averages of a stock price, noting that the 5‑day average is a short‑term trading threshold while the 20‑day average marks a medium‑term trend line, enabling simple strategy design.

import pandas as pd
import numpy as np
from pandas_datareader import data
import datetime
import matplotlib.pyplot as plt

After importing the required libraries, the script retrieves the last 100 days of price data for the Shanghai‑listed stock '601127.ss' from Yahoo Finance using data.DataReader, and displays the first few rows with price.head().

The fetched data (starting from 2021‑10‑08) is shown in a screenshot, confirming successful acquisition.

Moving averages are then added to the DataFrame:

price['ma5'] = price['Adj Close'].rolling(5).mean()
price['ma20'] = price['Adj Close'].rolling(20).mean()
price.tail()

The resulting DataFrame now contains the 5‑day and 20‑day average columns, as illustrated by another screenshot.

Finally, the script creates a Matplotlib figure to plot the adjusted closing price together with the two moving‑average lines:

fig = plt.figure(figsize=(16,9))
ax1 = fig.add_subplot(111, ylabel='Price')
price['Adj Close'].plot(ax=ax1, color='g', lw=2., legend=True)
price.ma5.plot(ax=ax1, color='r', lw=2., legend=True)
price.ma20.plot(ax=ax1, color='b', lw=2., legend=True)
plt.grid()
plt.show()

The generated chart clearly displays the price series and the two moving averages, allowing readers to visually assess the relationship between different periods and to devise moving‑average‑based trading strategies.

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