Jupyter Indicators

Sure, David, it's not a silly question at all. In the QuantConnect documentation, there are several examples of how to plot indicators like Variance. Here are a few examples in Python:

1. Variance Algorithm This example shows how to create a Variance indicator and plot it. The Variance indicator computes the n-period population variance. The Plot method is used to plot the current value of the Variance indicator when it's ready.

class VarianceAlgorithm(QCAlgorithm):
 def Initialize(self) -> None:
 self.symbol = self.AddEquity("SPY", Resolution.Daily).Symbol
 self.var = Variance(20)

 def OnData(self, slice: Slice) -> None:
 bar = slice.Bars.get(self.symbol)
 if bar:
 self.var.Update(bar.EndTime, bar.Close)

 if self.var.IsReady:
 # The current value of self.var is represented by self.var.Current.Value
 self.Plot("Variance", "var", self.var.Current.Value)

Source

1. Plotting Indicators This example shows how to plot the indicator values using Python. The plot method is used to plot the indicator values and plt.show() is used to display the plots.

sma_of_rsi_plot = sma_of_rsi_dataframe[["SMA Of RSI"]]
sma_of_rsi_plot.plot(title="SPY SMA(10) of RSI(10)", figsize=(15, 10))
plt.show()

Source

1. Bar Indicators This example shows how to plot bar indicators using Python. The plot method is used to plot the indicator values and plt.show() is used to display the plots.

atr_indicator.plot(title="SPY ATR(20)", figsize=(15, 10))
plt.show()

Source

I hope this helps! Let me know if you have any other questions.

import matplotlib.pyplot as plt
import mplfinance
import numpy as np
from pandas.plotting import register_matplotlib_converters
register_matplotlib_converters()

qb = QuantBook()
tickers = ["SPY", 
           "QQQ"]   
symbols = [qb.AddEquity(ticker, Resolution.Daily).Symbol for ticker in tickers]
history = qb.History(symbols, datetime(1999, 1, 1), datetime(2023, 1, 1))

symbol = symbols[0]
data = history.loc[symbol]['close']
data.plot(title=f"{symbol} Close Price", figsize=(15, 10))

Thanks Mia, but I'm still unsure of how to get the names for other indicators.

For example in the above Jupyter code, how could I change the variable ‘close’ in the second to last line:

data = history.loc[symbol]['close']

to get a line plot for an indicator variable not listed in the documentation like ‘variance’ or ‘standard deviation’? I just don't know what names they're referenced to and can't seem to find them on the quantconnect website.

To plot indicators like Variance or Standard Deviation, you first need to create these indicators and update them with the historical data. The historical data itself does not contain these indicators, they need to be calculated. Here's an example of how you can do this for Variance and Standard Deviation:

from QuantConnect.Indicators import Variance, StandardDeviation

qb = QuantBook()
symbol = qb.AddEquity("SPY", Resolution.Daily).Symbol
history = qb.History(symbol, datetime(1999, 1, 1), datetime(2023, 1, 1))

# Create the indicators
variance = Variance(20)
stddev = StandardDeviation(20)

# Update the indicators with historical data
for idx, row in history.loc[symbol].iterrows():
    variance.Update(idx, row["close"])
    stddev.Update(idx, row["close"])

# Plot the indicators
plt.figure(figsize=(15,10))
plt.plot(variance.Samples, label='Variance')
plt.plot(stddev.Samples, label='Standard Deviation')
plt.legend()
plt.show()

In this code, we first create the Variance and Standard Deviation indicators with a period of 20. Then we update these indicators with the close prices from the historical data. Finally, we plot the indicators.

Please note that the Variance and Standard Deviation indicators are not automatically included in the historical data, they need to be calculated separately as shown above.

For more information on how to use indicators in QuantConnect, you can refer to the Indicators documentation.

Thank you!

You're welcome, David! If you have any more questions in the future, don't hesitate to ask. Happy coding!