class ShouldGetSkipped(DataSet):
"""
Dataset that's only used by PrepopulatedFactor. It should get pruned from
the execution when PrepopulatedFactor is prepopulated.
"""
column1 = Column(dtype=float)
column2 = Column(dtype=float)
class Fundamentals(DataSet):
locals().update({
name: Column(dtype=float) for name in sharadar_f1_top25
})
locals().update({
name: Column(dtype=object) for name in sharadar_tickers
})
class Parent(DataSetFamily):
extra_dims = [
('dim_0', {'a', 'b', 'c'}),
('dim_1', {'d', 'e', 'f'}),
]
column_0 = Column('f8')
column_1 = Column('?')
class MD(DataSetFamily):
extra_dims = dims_spec
f8 = Column('f8')
i8 = Column('i8', missing_value=0)
ob = Column('O')
M8 = Column('M8[ns]')
boolean = Column('?')
class MD(MultiDimensionalDataSet):
extra_dims = dims_spec
f8 = Column('f8')
i8 = Column('i8', missing_value=0)
ob = Column('O')
M8 = Column('M8[ns]')
boolean = Column('?')
class Parent(MultiDimensionalDataSet):
extra_dims = [
('dim_0', {'a', 'b', 'c'}),
('dim_1', {'d', 'e', 'f'}),
]
column_0 = Column('f8')
column_1 = Column('?')
class Parent(DataSetFamily):
extra_dims = [
("dim_0", {"a", "b", "c"}),
("dim_1", {"d", "e", "f"}),
]
column_0 = Column("f8")
column_1 = Column("?")
class MD(DataSetFamily):
extra_dims = dims_spec
f8 = Column("f8")
i8 = Column("i8", missing_value=0)
ob = Column("O")
M8 = Column("M8[ns]")
boolean = Column("?")
class ShortableShares(DataSetFamily):
"""
DataSetFamily representing IBKR shortable shares. In order to use
the data in a pipeline, it must first be sliced to generate a regular
pipeline DataSet.
ShortableShares can be sliced along one dimension:
- `time` : the time of day (in the bundle timezone) as of which shortable
shares should be returned, formatted as HH:MM:SS, for example 08:45:00.
Attributes
----------
shares : float
number of shortable shares
Examples
--------
Get shortable shares as of 8:45 AM:
>>> shares = ibkr.ShortableShares.slice(time="08:45:00").shares.latest # doctest: +SKIP
"""
extra_dims = [
('time',
set(
pd.date_range(
start=pd.Timestamp.today().normalize().replace(hour=0,
minute=0),
end=pd.Timestamp.today().normalize().replace(hour=23,
minute=59),
freq="1min").strftime("%H:%M:%S")))
]
shares = Column(float64_dtype)
class MyDataSet(DataSet):
"""
We need to create an attribute for each needed data point within MyDataSet, before __new__() runs...
This is so MyDataSet converts the Column types into BoundColumn types.
"""
for point in data_points:
locals()[point] = Column(dtype=float)
def initialize(context):
# Create, register and name a pipeline in initialize.
pipe = Pipeline()
context.attach_pipeline(pipe, 'AAPL')
# Construct a simple moving average factor and add it to the pipeline.
USEquityPricing需要本地自定义
if True:
sma_short = SimpleMovingAverage(inputs=[USEquityPricing.close], window_length=10)
else:#mid added
data = Column(float64)
dataset = DataSet()
close = data.bind(dataset, 'aapl')
sma_short = SimpleMovingAverage(inputs=[close], window_length=10)
pipe.add(sma_short, 'sma_short')
def initialize(context):
# Create, register and name a pipeline in initialize.
pipe = Pipeline()
context.attach_pipeline(pipe, 'AAPL')
# Construct a simple moving average factor and add it to the pipeline.
USEquityPricing需要本地自定义
if True:
sma_short = SimpleMovingAverage(inputs=[USEquityPricing.close],
window_length=10)
else: #mid added
data = Column(float64)
dataset = DataSet()
close = data.bind(dataset, 'aapl')
sma_short = SimpleMovingAverage(inputs=[close], window_length=10)
pipe.add(sma_short, 'sma_short')
def test_failure_timing_on_bad_dtypes(self):
# Just constructing a bad column shouldn't fail.
Column(dtype=int64_dtype)
with self.assertRaises(NoDefaultMissingValue) as e:
class BadDataSet(DataSet):
bad_column = Column(dtype=int64_dtype)
float_column = Column(dtype=float64_dtype)
int_column = Column(dtype=int64_dtype, missing_value=3)
self.assertTrue(
str(e.exception.args[0]).startswith(
"Failed to create Column with name 'bad_column'"))
Column(dtype=complex128_dtype)
with self.assertRaises(UnsupportedDType):
class BadDataSetComplex(DataSet):
bad_column = Column(dtype=complex128_dtype)
float_column = Column(dtype=float64_dtype)
int_column = Column(dtype=int64_dtype, missing_value=3)
class ETB(DataSet):
"""
Dataset representing whether securities are easy-to-borrow
through Alpaca.
Attributes
----------
etb : bool
whether the security is easy-to-borrow
Examples
--------
>>> are_etb = alpaca.ETB.etb.latest # doctest: +SKIP
"""
domain = US_EQUITIES
etb = Column(bool_dtype)
class MyData(DataSet):
col1 = Column(dtype=float)
col2 = Column(dtype=int, missing_value=100)
col3 = Column(dtype=object, missing_value="")
class D(DataSet):
c1 = Column(float)
c2 = Column(bool)
c3 = Column(object)
class MyData(DataSet):
domain = domain_param
col1 = Column(dtype=float)
class Estimates(DataSet):
event_date = Column(dtype=datetime64ns_dtype)
fiscal_quarter = Column(dtype=float64_dtype)
fiscal_year = Column(dtype=float64_dtype)
estimate = Column(dtype=float64_dtype)
def set_dataset_columns(data_points, cls):
for point in data_points:
setattr(cls, point, Column(dtype=float))
return cls
class SomeDataSet(DataSet):
foo = Column(float64_dtype)
bar = Column(float64_dtype)
buzz = Column(float64_dtype)
class SubDataSetNewCol(SomeDataSet):
qux = Column(float64_dtype)
class Loader2DataSet(DataSet):
col1 = Column(float32)
col2 = Column(float32)
class Loader1DataSet2(DataSet):
col1 = Column(float32)
col2 = Column(float32)
class D(DataSet):
c = Column(float)
b = Column(bool)
class D(DataSet):
c = Column(float)
class D(DataSet):
c = Column(bool)
class BadDataSetComplex(DataSet):
bad_column = Column(dtype=complex128_dtype)
float_column = Column(dtype=float64_dtype)
int_column = Column(dtype=int64_dtype, missing_value=3)
class Child(Parent):
column_2 = Column('O')
column_3 = Column('i8', -1)
class MyDataSubclass(MyData):
col4 = Column(dtype=float)
class SecuritiesMaster(DataSet):
"""
Dataset representing the securities master file.
Attributes
----------
Sid : str
Symbol : str
Exchange : str
Currency : str
SecType : str
Etf : bool
Timezone : str
Name : str
PriceMagnifier : float
Multiplier : float
Delisted : bool
DateDelisted : datetime64D
LastTradeDate : datetime64D
RolloverDate : datetime64D
alpaca_AssetId : str
Asset ID
alpaca_AssetClass : str
"us_equity"
alpaca_Exchange : str
AMEX, ARCA, BATS, NYSE, NASDAQ or NYSEARCA
alpaca_Symbol : str
alpaca_Name : str
alpaca_Status : str
active or inactive
alpaca_Tradable : float
Asset is tradable on Alpaca or not.
alpaca_Marginable : float
Asset is marginable or not.
alpaca_Shortable : float
Asset is shortable or not.
alpaca_EasyToBorrow : float
Asset is easy-to-borrow or not (filtering for easy_to_borrow = True is
the best way to check whether the name is currently available to short
at Alpaca).
edi_SecId : float
Unique global level Security ID (can be used to link all multiple
listings together)
edi_Currency : str
edi_PrimaryMic : str
MIC code for the primary listing (empty if unknown)
edi_Mic : str
ISO standard Market Identification Code
edi_MicSegment : str
ISO standard Market Identification Code
edi_MicTimezone : str
edi_IsPrimaryListing : float
1 if PrimaryMic = Mic
edi_LocalSymbol : str
Local code unique at Market level - a ticker or number
edi_IssuerId : float
Unique global level Issuer ID (can be used to link all securities of a
company togther)
edi_IssuerName : str
edi_IsoCountryInc : str
ISO Country of Incorporation of Issuer
edi_CountryInc : str
edi_IsoCountryListed : str
Country of Exchange where listed
edi_CountryListed : str
edi_SicCode : int
Standard Industrial Classification Code
edi_Sic : str
edi_SicIndustryGroup : str
edi_SicMajorGroup : str
edi_SicDivision : str
edi_Cik : str
Central Index Key
edi_Industry : str
edi_SecTypeCode : str
Type of Equity Instrument
edi_SecTypeDesc : str
Type of Equity Instrument (lookup SECTYPE with SectyCD)
edi_SecurityDesc : str
edi_PreferredName : str
for ETFs, the SecurityDesc, else the IssuerName
edi_GlobalListingStatus : str
Inactive at the global level else security is active. Not to be
confused with delisted which is inactive at the exchange level (lookup
SECSTATUS)
edi_ExchangeListingStatus : str
Indicates whether a security is Listed on an Exchange or Unlisted
Indicates Exchange Listing Status (lookup LISTSTAT)
edi_DateDelisted : datetime64D
edi_StructureCode : str
edi_StructureDesc : str
edi_RecordModified : str
Date event updated, format is yyyy/mm/dd hh:mm:ss
edi_RecordCreated : str
Date event first entered
edi_FirstPriceDate : datetime64D
first date a price is available
edi_LastPriceDate : datetime64D
latest date a price is available
ibkr_ConId : float
ibkr_Symbol : str
ibkr_SecType : str
ibkr_Etf : bool
ibkr_PrimaryExchange : str
ibkr_Currency : str
ibkr_LocalSymbol : str
ibkr_TradingClass : str
ibkr_MarketName : str
ibkr_LongName : str
ibkr_Timezone : str
ibkr_ValidExchanges : str
ibkr_AggGroup : float
ibkr_Sector : str
ibkr_Industry : str
ibkr_Category : str
ibkr_MinTick : float
ibkr_PriceMagnifier : float
ibkr_MdSizeMultiplier : float
ibkr_LastTradeDate : datetime64D
ibkr_ContractMonth : float
ibkr_RealExpirationDate : datetime64D
ibkr_Multiplier : float
ibkr_UnderConId : float
ibkr_UnderSymbol : str
ibkr_UnderSecType : str
ibkr_MarketRuleIds : str
ibkr_Strike : float
ibkr_Right : str
ibkr_Isin : str
ibkr_Cusip : str
ibkr_EvRule : str
ibkr_EvMultiplier : float
ibkr_Delisted : bool
ibkr_DateDelisted : datetime64D
sharadar_Permaticker : float
Permanent Ticker Symbol - The permaticker is a unique and unchanging
identifier for an issuer in the dataset which is issued by Sharadar.
sharadar_Ticker : str
Ticker Symbol - The ticker is a unique identifer for an issuer in the
database. Where a ticker contains a "." or a "-" this is removed from
the ticker. For example BRK.B is BRKB. We include the BRK.B ticker in
the Related Tickers field. Where a company is delisted and the ticker
is recycled; we use that ticker for the currently active company and
append a number to the ticker of the delisted company. eg GM is the
current actively traded entity; & GM1 is the entity that filed for
bankruptcy in 2009.
sharadar_Name : str
Issuer Name - The name of the security issuer.
sharadar_Exchange : str
Stock Exchange - The exchange on which the security trades. Examples
are: "NASDAQ";"NYSE";"NYSEARCA";"BATS";"OTC" and "NYSEMKT" (previously
the American Stock exchange).
sharadar_Delisted : bool
Is Delisted? - Is the security delisted?
sharadar_DateDelisted : datetime64D
sharadar_Category : str
Issuer Category - The category of the issuer: "Domestic"; "Canadian"
or "ADR".
sharadar_Cusips : str
CUSIPs - A security identifier. Space delimited in the event of
multiple identifiers.
sharadar_SicCode : int
Standard Industrial Classification (SIC) Code - The Standard
Industrial Classification (SIC) is a system for classifying industries
by a four-digit code; as sourced from SEC filings. More on the SIC
system here:
https://en.wikipedia.org/wiki/Standard_Industrial_Classification
sharadar_SicSector : str
SIC Sector - The SIC sector is based on the SIC code and the division
tabled here:
https://en.wikipedia.org/wiki/Standard_Industrial_Classification
sharadar_SicIndustry : str
SIC Industry - The SIC industry is based on the SIC code and the
industry tabled here: https://www.sec.gov/info/edgar/siccodes.htm
sharadar_FamaSector : str
Fama Sector - Not currently active - coming in a future update.
sharadar_FamaIndustry : str
Fama Industry - Industry classifications based on the SIC code and
classifications by Fama and French here: http://mba.tuck.dartmouth.edu
/pages/faculty/ken.french/Data_Library/det_48_ind_port.html
sharadar_Sector : str
Sector - Sharadar's sector classification based on SIC codes in a
format which approximates to GICS.
sharadar_Industry : str
Industry - Sharadar's industry classification based on SIC codes in a
format which approximates to GICS.
sharadar_ScaleMarketCap : str
Company Scale - Market Cap - This field is experimental and subject to
change. It categorises the company according to it's maximum observed
market cap as follows: 1 - Nano <$50m; 2 - Micro < $300m; 3 - Small <
$2bn; 4 - Mid <$10bn; 5 - Large < $200bn; 6 - Mega >= $200bn
sharadar_ScaleRevenue : str
Company Scale - Revenue - This field is experimental and subject to
change. It categorises the company according to it's maximum observed
annual revenue as follows: 1 - Nano <$50m; 2 - Micro < $300m; 3 -
Small < $2bn; 4 - Mid <$10bn; 5 - Large < $200bn; 6 - Mega >= $200bn
sharadar_RelatedTickers : str
Related Tickers - Where related tickers have been identified this
field is populated. Related tickers can include the prior ticker
before a ticker change; and it tickers for alternative share classes.
sharadar_Currency : str
Currency - The company functional reporting currency for the SF1
Fundamentals table or the currency for EOD prices in SEP and SFP.
sharadar_Location : str
Location - The company location as registered with the Securities and
Exchange Commission.
sharadar_CountryListed : str
ISO country code where security is listed
sharadar_LastUpdated : datetime64D
Last Updated Date - Last Updated represents the last date that this
database entry was updated; which is useful to users when updating
their local records.
sharadar_FirstAdded : datetime64D
First Added Date - The date that the ticker was first added to
coverage in the dataset.
sharadar_FirstPriceDate : datetime64D
First Price Date - The date of the first price observation for a given
ticker. Can be used as a proxy for IPO date. Minimum value of
1986-01-01 for IPO's that occurred prior to this date. Note: this does
not necessarily represent the first price date available in our
datasets since our end of day price history currently starts in
December 1998.
sharadar_LastPriceDate : datetime64D
Last Price Date - The most recent price observation available.
sharadar_FirstQuarter : datetime64D
First Quarter - The first financial quarter available in the dataset.
sharadar_LastQuarter : datetime64D
Last Quarter - The last financial quarter available in the dataset.
sharadar_SecFilings : str
SEC Filings URL - The URL pointing to the SEC filings which also
contains the Central Index Key (CIK).
sharadar_CompanySite : str
Company Website URL - The URL pointing to the company website.
usstock_Mic : str
usstock_Symbol : str
usstock_Name : str
usstock_Sector : str
sector in which company operates. There are 11 possible sectors.
usstock_Industry : str
industry in which company operates. There are 58 possible industries.
usstock_SicCode : str
Standard Industrial Classification Code, used in SEC filings
usstock_Sic : str
SIC code description, bottom tier in SIC hierarchy, e.g.
"Electronic Computers"
usstock_SicIndustryGroup : str
3rd-level tier in SIC hierarchy, e.g. "Computer And Office Equipment"
usstock_SicMajorGroup : str
2nd-level tier in SIC hierarchy, e.g. "Industrial And Commercial
Machinery And Computer Equipment"
usstock_SicDivision : str
Top-level tier in SIC hierarchy
usstock_SecurityType : str
security type (more detailed than usstock_SecurityType2)
usstock_SecurityType2 : str
security type (less detailed than usstock_SecurityType)
usstock_CIK : str
the Central Index Key is the unique company identifier in SEC filings
usstock_PrimaryShareSid : str
the sid of the primary share class, if not this security (for companies with
multiple share classes). Filtering to securities where usstock_PrimaryShareSid
is null is a way to deduplicate companies with multiple share classes.
usstock_DateDelisted : datetime64D
usstock_FirstPriceDate : datetime64D
date of first available price
usstock_LastPriceDate : datetime64D
date of last available price
figi_Figi : str
e.g. BBG000BBBRC7
figi_Name : str
e.g. AFLAC INC
figi_Ticker : str
e.g. AFL
figi_CompositeFigi : str
e.g. BBG000BBBNC6
figi_ExchCode : str
e.g. UN
figi_UniqueId : str
e.g. EQ0010001500001000
figi_SecurityType : str
e.g. Common Stock
figi_MarketSector : str
e.g. Equity
figi_ShareClassFigi : str
e.g. BBG001S5NGJ4
figi_UniqueIdFutOpt : str
figi_SecurityType2 : str
e.g. Common Stock
figi_SecurityDescription : str
e.g. AFL
figi_IsComposite : bool
whether the Figi column contains a composite FIGI
Examples
--------
Filter ETFs:
>>> are_etfs = SecuritiesMaster.Etf.latest # doctest: +SKIP
Filter NYSE stocks:
>>> are_nyse_stocks = SecuritiesMaster.Exchange.latest.eq("XNYS") # doctest: +SKIP
Filter to primary shares, which can be identified by a null
usstock_PrimaryShareSid field (i.e. they have no pointer to another
primary share):
>>> are_primary_shares = master.SecuritiesMaster.usstock_PrimaryShareSid.latest.isnull() # doctest: +SKIP
"""
Sid = Column(object_dtype)
Symbol = Column(object_dtype)
Exchange = Column(object_dtype)
Currency = Column(object_dtype)
SecType = Column(object_dtype)
Etf = Column(bool_dtype)
Timezone = Column(object_dtype)
Name = Column(object_dtype)
PriceMagnifier = Column(float64_dtype)
Multiplier = Column(float64_dtype)
Delisted = Column(bool_dtype)
DateDelisted = Column(datetime64ns_dtype, missing_value=NaTD)
LastTradeDate = Column(datetime64ns_dtype, missing_value=NaTD)
RolloverDate = Column(datetime64ns_dtype, missing_value=NaTD)
alpaca_AssetId = Column(object_dtype)
alpaca_AssetClass = Column(object_dtype)
alpaca_Exchange = Column(object_dtype)
alpaca_Symbol = Column(object_dtype)
alpaca_Name = Column(object_dtype)
alpaca_Status = Column(object_dtype)
alpaca_Tradable = Column(float64_dtype)
alpaca_Marginable = Column(float64_dtype)
alpaca_Shortable = Column(float64_dtype)
alpaca_EasyToBorrow = Column(float64_dtype)
edi_SecId = Column(float64_dtype)
edi_Currency = Column(object_dtype)
edi_PrimaryMic = Column(object_dtype)
edi_Mic = Column(object_dtype)
edi_MicSegment = Column(object_dtype)
edi_MicTimezone = Column(object_dtype)
edi_IsPrimaryListing = Column(float64_dtype)
edi_LocalSymbol = Column(object_dtype)
edi_IssuerId = Column(float64_dtype)
edi_IssuerName = Column(object_dtype)
edi_IsoCountryInc = Column(object_dtype)
edi_CountryInc = Column(object_dtype)
edi_IsoCountryListed = Column(object_dtype)
edi_CountryListed = Column(object_dtype)
edi_SicCode = Column(object_dtype)
edi_Sic = Column(object_dtype)
edi_SicIndustryGroup = Column(object_dtype)
edi_SicMajorGroup = Column(object_dtype)
edi_SicDivision = Column(object_dtype)
edi_Cik = Column(object_dtype)
edi_Industry = Column(object_dtype)
edi_SecTypeCode = Column(object_dtype)
edi_SecTypeDesc = Column(object_dtype)
edi_SecurityDesc = Column(object_dtype)
edi_PreferredName = Column(object_dtype)
edi_GlobalListingStatus = Column(object_dtype)
edi_ExchangeListingStatus = Column(object_dtype)
edi_DateDelisted = Column(datetime64ns_dtype, missing_value=NaTD)
edi_StructureCode = Column(object_dtype)
edi_StructureDesc = Column(object_dtype)
edi_RecordModified = Column(object_dtype)
edi_RecordCreated = Column(object_dtype)
edi_FirstPriceDate = Column(datetime64ns_dtype, missing_value=NaTD)
edi_LastPriceDate = Column(datetime64ns_dtype, missing_value=NaTD)
ibkr_ConId = Column(float64_dtype)
ibkr_Symbol = Column(object_dtype)
ibkr_SecType = Column(object_dtype)
ibkr_Etf = Column(bool_dtype)
ibkr_PrimaryExchange = Column(object_dtype)
ibkr_Currency = Column(object_dtype)
ibkr_LocalSymbol = Column(object_dtype)
ibkr_TradingClass = Column(object_dtype)
ibkr_MarketName = Column(object_dtype)
ibkr_LongName = Column(object_dtype)
ibkr_Timezone = Column(object_dtype)
ibkr_ValidExchanges = Column(object_dtype)
ibkr_AggGroup = Column(float64_dtype)
ibkr_Sector = Column(object_dtype)
ibkr_Industry = Column(object_dtype)
ibkr_Category = Column(object_dtype)
ibkr_MinTick = Column(float64_dtype)
ibkr_PriceMagnifier = Column(float64_dtype)
ibkr_MdSizeMultiplier = Column(float64_dtype)
ibkr_LastTradeDate = Column(datetime64ns_dtype, missing_value=NaTD)
ibkr_ContractMonth = Column(float64_dtype)
ibkr_RealExpirationDate = Column(datetime64ns_dtype, missing_value=NaTD)
ibkr_Multiplier = Column(float64_dtype)
ibkr_UnderConId = Column(float64_dtype)
ibkr_UnderSymbol = Column(object_dtype)
ibkr_UnderSecType = Column(object_dtype)
ibkr_MarketRuleIds = Column(object_dtype)
ibkr_Strike = Column(float64_dtype)
ibkr_Right = Column(object_dtype)
ibkr_Isin = Column(object_dtype)
ibkr_Cusip = Column(object_dtype)
ibkr_EvRule = Column(object_dtype)
ibkr_EvMultiplier = Column(float64_dtype)
ibkr_Delisted = Column(bool_dtype)
ibkr_DateDelisted = Column(datetime64ns_dtype, missing_value=NaTD)
sharadar_Permaticker = Column(float64_dtype)
sharadar_Ticker = Column(object_dtype)
sharadar_Name = Column(object_dtype)
sharadar_Exchange = Column(object_dtype)
sharadar_Delisted = Column(bool_dtype)
sharadar_DateDelisted = Column(datetime64ns_dtype, missing_value=NaTD)
sharadar_Category = Column(object_dtype)
sharadar_Cusips = Column(object_dtype)
sharadar_SicCode = Column(object_dtype)
sharadar_SicSector = Column(object_dtype)
sharadar_SicIndustry = Column(object_dtype)
sharadar_FamaSector = Column(object_dtype)
sharadar_FamaIndustry = Column(object_dtype)
sharadar_Sector = Column(object_dtype)
sharadar_Industry = Column(object_dtype)
sharadar_ScaleMarketCap = Column(object_dtype)
sharadar_ScaleRevenue = Column(object_dtype)
sharadar_RelatedTickers = Column(object_dtype)
sharadar_Currency = Column(object_dtype)
sharadar_Location = Column(object_dtype)
sharadar_CountryListed = Column(object_dtype)
sharadar_LastUpdated = Column(datetime64ns_dtype, missing_value=NaTD)
sharadar_FirstAdded = Column(datetime64ns_dtype, missing_value=NaTD)
sharadar_FirstPriceDate = Column(datetime64ns_dtype, missing_value=NaTD)
sharadar_LastPriceDate = Column(datetime64ns_dtype, missing_value=NaTD)
sharadar_FirstQuarter = Column(datetime64ns_dtype, missing_value=NaTD)
sharadar_LastQuarter = Column(datetime64ns_dtype, missing_value=NaTD)
sharadar_SecFilings = Column(object_dtype)
sharadar_CompanySite = Column(object_dtype)
usstock_Mic = Column(object_dtype)
usstock_Symbol = Column(object_dtype)
usstock_Name = Column(object_dtype)
usstock_Sector = Column(object_dtype)
usstock_Industry = Column(object_dtype)
usstock_SicCode = Column(object_dtype)
usstock_Sic = Column(object_dtype)
usstock_SicIndustryGroup = Column(object_dtype)
usstock_SicMajorGroup = Column(object_dtype)
usstock_SicDivision = Column(object_dtype)
usstock_SecurityType = Column(object_dtype)
usstock_SecurityType2 = Column(object_dtype)
usstock_CIK = Column(object_dtype)
usstock_PrimaryShareSid = Column(object_dtype)
usstock_DateDelisted = Column(datetime64ns_dtype, missing_value=NaTD)
usstock_FirstPriceDate = Column(datetime64ns_dtype, missing_value=NaTD)
usstock_LastPriceDate = Column(datetime64ns_dtype, missing_value=NaTD)
figi_Figi = Column(object_dtype)
figi_Name = Column(object_dtype)
figi_Ticker = Column(object_dtype)
figi_CompositeFigi = Column(object_dtype)
figi_ExchCode = Column(object_dtype)
figi_UniqueId = Column(object_dtype)
figi_SecurityType = Column(object_dtype)
figi_MarketSector = Column(object_dtype)
figi_ShareClassFigi = Column(object_dtype)
figi_UniqueIdFutOpt = Column(object_dtype)
figi_SecurityType2 = Column(object_dtype)
figi_SecurityDescription = Column(object_dtype)
figi_IsComposite = Column(bool_dtype)
class EventDataSet(DataSet):
previous_event_date = Column(dtype=datetime64ns_dtype)
next_event_date = Column(dtype=datetime64ns_dtype)
previous_float = Column(dtype=float64_dtype)
next_float = Column(dtype=float64_dtype)
previous_datetime = Column(dtype=datetime64ns_dtype)
next_datetime = Column(dtype=datetime64ns_dtype)
previous_int = Column(dtype=int64_dtype, missing_value=-1)
next_int = Column(dtype=int64_dtype, missing_value=-1)
previous_string = Column(dtype=categorical_dtype, missing_value=None)
next_string = Column(dtype=categorical_dtype, missing_value=None)
previous_string_custom_missing = Column(
dtype=categorical_dtype,
missing_value=u"<<NULL>>",
)
next_string_custom_missing = Column(
dtype=categorical_dtype,
missing_value=u"<<NULL>>",
)
