Notebook
In [1]:
from quantopian.research import prices
In [6]:
llex_prices = prices(
    symbols('LLEX'),
    '01-01-2014',
    '05-01-2017',
)
In [7]:
llex_prices.plot()
Out[7]:
<matplotlib.axes._subplots.AxesSubplot at 0x7f22aa77e190>
In [8]:
llex_prices
Out[8]:
2014-01-02 00:00:00+00:00    2.270
2014-01-03 00:00:00+00:00    2.190
2014-01-06 00:00:00+00:00    2.210
2014-01-07 00:00:00+00:00    2.220
2014-01-08 00:00:00+00:00    2.240
2014-01-09 00:00:00+00:00    2.389
2014-01-10 00:00:00+00:00    2.311
2014-01-13 00:00:00+00:00    2.320
2014-01-14 00:00:00+00:00    2.340
2014-01-15 00:00:00+00:00    2.320
2014-01-16 00:00:00+00:00    2.350
2014-01-17 00:00:00+00:00    2.329
2014-01-21 00:00:00+00:00    2.350
2014-01-22 00:00:00+00:00    2.160
2014-01-23 00:00:00+00:00    2.170
2014-01-24 00:00:00+00:00    2.310
2014-01-27 00:00:00+00:00    2.270
2014-01-28 00:00:00+00:00    2.210
2014-01-29 00:00:00+00:00    2.260
2014-01-30 00:00:00+00:00    2.350
2014-01-31 00:00:00+00:00    3.050
2014-02-03 00:00:00+00:00    3.260
2014-02-04 00:00:00+00:00    3.200
2014-02-05 00:00:00+00:00    3.240
2014-02-06 00:00:00+00:00    3.440
2014-02-07 00:00:00+00:00    3.350
2014-02-10 00:00:00+00:00    3.400
2014-02-11 00:00:00+00:00    3.250
2014-02-12 00:00:00+00:00    3.530
2014-02-13 00:00:00+00:00    3.200
                             ...  
2017-03-20 00:00:00+00:00    4.330
2017-03-21 00:00:00+00:00    4.280
2017-03-22 00:00:00+00:00    4.300
2017-03-23 00:00:00+00:00    3.980
2017-03-24 00:00:00+00:00    4.010
2017-03-27 00:00:00+00:00    3.890
2017-03-28 00:00:00+00:00    4.000
2017-03-29 00:00:00+00:00    3.980
2017-03-30 00:00:00+00:00    3.950
2017-03-31 00:00:00+00:00    3.957
2017-04-03 00:00:00+00:00    3.860
2017-04-04 00:00:00+00:00    3.710
2017-04-05 00:00:00+00:00    3.790
2017-04-06 00:00:00+00:00    3.550
2017-04-07 00:00:00+00:00    3.550
2017-04-10 00:00:00+00:00    3.630
2017-04-11 00:00:00+00:00    3.660
2017-04-12 00:00:00+00:00    3.700
2017-04-13 00:00:00+00:00    3.700
2017-04-17 00:00:00+00:00    3.600
2017-04-18 00:00:00+00:00    4.059
2017-04-19 00:00:00+00:00    4.110
2017-04-20 00:00:00+00:00    4.250
2017-04-21 00:00:00+00:00    4.180
2017-04-24 00:00:00+00:00    4.210
2017-04-25 00:00:00+00:00    4.260
2017-04-26 00:00:00+00:00    4.560
2017-04-27 00:00:00+00:00    4.610
2017-04-28 00:00:00+00:00    4.460
2017-05-01 00:00:00+00:00    4.450
Freq: C, Name: Equity(37624 [LLEX]), dtype: float64
In [9]:
from quantopian.pipeline import Pipeline
from quantopian.research import run_pipeline
from quantopian.pipeline.experimental import QTradableStocksUS
In [10]:
pipe = Pipeline(
    columns={'qtu': QTradableStocksUS()}
)
In [11]:
df = run_pipeline(pipe, '2014-01-01', '2017-05-01')
In [13]:
llex = df[df.index.get_level_values(1) == symbols('llex')]
In [16]:
llex.head()
Out[16]:
qtu
2014-01-02 00:00:00+00:00 Equity(37624 [LLEX]) False
2014-01-03 00:00:00+00:00 Equity(37624 [LLEX]) False
2014-01-06 00:00:00+00:00 Equity(37624 [LLEX]) False
2014-01-07 00:00:00+00:00 Equity(37624 [LLEX]) False
2014-01-08 00:00:00+00:00 Equity(37624 [LLEX]) False
In [14]:
llex[llex['qtu']]
Out[14]:
qtu