Notebook
In [13]:
from quantopian.pipeline.factors import CustomFactor
from quantopian.pipeline.filters import StaticAssets
from quantopian.pipeline import Pipeline
from quantopian.research import run_pipeline
from quantopian.pipeline.data.quandl import fred_usdontd156n
In [19]:
class LIBOR(CustomFactor):
    inputs = [fred_usdontd156n.value]
    window_length = 1
    
    def compute(self, today, asset_ids, out, values): 
        out[:] = values
In [20]:
def make_pipeline():
    spy = symbols('SPY')
    spy_fltr = StaticAssets([spy,])

    return Pipeline(
        columns={
            'libor': LIBOR()
        },
    screen = spy_fltr
    )
In [23]:
result = run_pipeline(make_pipeline(), '2016-10-01', '2017-01-01')
In [24]:
result
Out[24]:
libor
2016-10-03 00:00:00+00:00 Equity(8554 [SPY]) 0.42322
2016-10-04 00:00:00+00:00 Equity(8554 [SPY]) 0.42433
2016-10-05 00:00:00+00:00 Equity(8554 [SPY]) 0.42544
2016-10-06 00:00:00+00:00 Equity(8554 [SPY]) 0.42063
2016-10-07 00:00:00+00:00 Equity(8554 [SPY]) 0.41989
2016-10-10 00:00:00+00:00 Equity(8554 [SPY]) 0.42378
2016-10-11 00:00:00+00:00 Equity(8554 [SPY]) 0.42267
2016-10-12 00:00:00+00:00 Equity(8554 [SPY]) 0.42433
2016-10-13 00:00:00+00:00 Equity(8554 [SPY]) 0.42822
2016-10-14 00:00:00+00:00 Equity(8554 [SPY]) 0.42878
2016-10-17 00:00:00+00:00 Equity(8554 [SPY]) 0.42656
2016-10-18 00:00:00+00:00 Equity(8554 [SPY]) 0.42656
2016-10-19 00:00:00+00:00 Equity(8554 [SPY]) 0.42767
2016-10-20 00:00:00+00:00 Equity(8554 [SPY]) 0.42878
2016-10-21 00:00:00+00:00 Equity(8554 [SPY]) 0.43100
2016-10-24 00:00:00+00:00 Equity(8554 [SPY]) 0.43044
2016-10-25 00:00:00+00:00 Equity(8554 [SPY]) 0.43322
2016-10-26 00:00:00+00:00 Equity(8554 [SPY]) 0.43322
2016-10-27 00:00:00+00:00 Equity(8554 [SPY]) 0.43378
2016-10-28 00:00:00+00:00 Equity(8554 [SPY]) 0.43322
2016-10-31 00:00:00+00:00 Equity(8554 [SPY]) 0.43322
2016-11-01 00:00:00+00:00 Equity(8554 [SPY]) 0.43211
2016-11-02 00:00:00+00:00 Equity(8554 [SPY]) 0.43433
2016-11-03 00:00:00+00:00 Equity(8554 [SPY]) 0.43433
2016-11-04 00:00:00+00:00 Equity(8554 [SPY]) 0.43489
2016-11-07 00:00:00+00:00 Equity(8554 [SPY]) 0.43544
2016-11-08 00:00:00+00:00 Equity(8554 [SPY]) 0.43344
2016-11-09 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2016-11-10 00:00:00+00:00 Equity(8554 [SPY]) 0.43733
2016-11-11 00:00:00+00:00 Equity(8554 [SPY]) 0.43678
... ... ...
2016-11-18 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2016-11-21 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2016-11-22 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2016-11-23 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2016-11-25 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2016-11-28 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2016-11-29 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2016-11-30 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2016-12-01 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2016-12-02 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2016-12-05 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2016-12-06 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2016-12-07 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2016-12-08 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2016-12-09 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2016-12-12 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2016-12-13 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2016-12-14 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2016-12-15 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2016-12-16 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2016-12-19 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2016-12-20 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2016-12-21 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2016-12-22 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2016-12-23 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2016-12-27 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2016-12-28 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2016-12-29 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2016-12-30 00:00:00+00:00 Equity(8554 [SPY]) 0.43456
2017-01-03 00:00:00+00:00 Equity(8554 [SPY]) 0.43456

64 rows × 1 columns