[PYTHON] Quantopian Tutorial LESSON 6

This is a continuation of Last time.

LESSON 6 The history() Function

The data.history () method [^ 1] gets historical data. The arguments to pass are as follows.

The return value will be of pandas DataFrame type. In the example below, we get the price for 10 days of AAPL and calculate the average.

# Get the 10-day trailing price history of AAPL in the form of a Series.
hist = data.history(sid(24), 'price', 10, '1d')

# Mean price over the last 10 days.
mean_price = hist.mean()

By specifying '1d' in the 4th argument, data is acquired at a frequency of every day. If you specify '1m', you will get the data every minute.

If you specify '1d', the price for the day is also included. I think that the average up to the previous day is often used for trades that use the moving average as a guide. To calculate the average for 10 days up to the previous day, write as follows.

data.history(sid(8554), 'volume', 11, '1d')[:-1].mean()

Similar to data.current () introduced in LESSON 5, if multiple issues are specified, the DataFrame type of pandas will be returned.

# Get the last 5 minutes of volume data for each security in our list.
hist = data.history([sid(24), sid(8554), sid(5061)], 'volume', 5, '1m')

# Calculate the mean volume for each security in our DataFrame.
mean_volumes = hist.mean(axis=0)

If there are multiple brands and multiple fields are specified, the pandas Panel type [^ 2] will be returned.

# Low and high minute bar history for each of our securities.
hist = data.history([sid(24), sid(8554), sid(5061)], ['low', 'high'], 5, '1m')

# Calculate the mean low and high over the last 5 minutes
means = hist.mean()
mean_lows = means['low']
mean_highs = means['high']

The code below outputs the average volume of AAPL, MSFT, and SPY for 10 minutes.

def initialize(context):
    # AAPL, MSFT, SPY
    context.security_list = [sid(24), sid(8554), sid(5061)]

def handle_data(context, data):
    hist = data.history(context.security_list, 'volume', 10, '1m').mean()
    print hist.mean()

LESSON 5<-->LESSON7

[^ 1]: Notated as a method as before. [^ 2]: I've heard that Panel is integrated into xray. If anyone knows the details, please let me know.