Calculate and plot SMAs
Daily price data is inherently messy and noisy. You want to analyze the Apple stock daily price data, and plan to add a simple moving average (SMA) indicator to smooth out the data. Specifically, you decide to use the 50-day SMA.
The stock data has been preloaded in aapl_data
, and matplotlib.pyplot
has been imported as plt
. Additional customizations to the plot such as a title and legend have already been provided for you.
This exercise is part of the course
Financial Trading in Python
Exercise instructions
- Calculate the 50-day SMA using the
Close
price, and save it in a new column namedsma_50
. - Plot a line chart using the data in the columns
sma_50
andClose
.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Calculate SMA
aapl_data['sma_50'] = aapl_data['____'].____.mean()
# Plot the SMA
____(aapl_data['____'], color='green', label='SMA_50')
# Plot the close price
____(aapl_data['____'], color='red', label='Close')
# Customize and show the plot
plt.title('Simple moving averages')
plt.legend()
plt.show()