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>>", )