为列表中的每个值创建数据帧

Question

我正在编写一个代码，用于下载多只股票的历史数据。代码如下所示：

import pandas as pd
from nsepy import get_history
from datetime import date
stock = ['3MINDIA','ABB','POWERINDIA','ACC','AIAENG','APLAPOLLO','AUBANK','AARTIDRUGS','AARTIIND','AAVAS','ABBOTINDIA','ADANIENT','ADANIGAS','ADANIGREEN','ADANIPORTS','ADANITRANS','ABCAPITAL','ABFRL','ADVENZYMES','AEGISCHEM','AFFLE','AJANTPHARM','AKZOINDIA','ALEMBICLTD','APLLTD','ALKEM','ALKYLAMINE','ALOKINDS','AMARAJABAT','AMBER','AMBUJACEM','APOLLOHOSP','APOLLOTYRE','ASHOKLEY','ASHOKA','ASIANPAINT','ASTERDM','ASTRAZEN','ASTRAL','ATUL','AUROPHARMA','AVANTIFEED','DMART','AXISBANK','BASF','BEML','BSE','BAJAJ-AUTO','BAJAJCON','BAJAJELEC','BAJFINANCE','BAJAJFINSV','BAJAJHLDNG','BALKRISIND','BALMLAWRIE','BALRAMCHIN','BANDHANBNK','BANKBARODA','BANKINDIA','MAHABANK','BATAINDIA','BAYERCROP','BERGEPAINT','BDL','BEL','BHARATFORG','BHEL','BPCL','BHARATRAS','BHARTIARTL','INFRATEL','BIOCON','BIRLACORPN','BSOFT','BLISSGVS','BLUEDART','BLUESTARCO','BBTC','BOMDYEING','BOSCHLTD','BRIGADE','BRITANNIA','CARERATING','CCL','CESC','CRISIL','CSBBANK','CADILAHC','CANFINHOME','CANBK','CAPLIPOINT','CGCL','CARBORUNIV','CASTROLIND','CEATLTD','CENTRALBK','CDSL','CENTURYPLY','CENTURYTEX','CERA','CHALET','CHAMBLFERT','CHENNPETRO','CHOLAHLDNG','CHOLAFIN','CIPLA','CUB','COALINDIA','COCHINSHIP','COFORGE','COLPAL','CONCOR','COROMANDEL','CREDITACC','CROMPTON','CUMMINSIND','CYIENT','DBCORP','DCBBANK','DCMSHRIRAM','DLF','DABUR','DALBHARAT','DEEPAKNTR','DELTACORP','DHANI','DHANUKA','DBL','DISHTV','DCAL','DIVISLAB','DIXON','LALPATHLAB','DRREDDY','EIDPARRY','EIHOTEL','EPL','ESABINDIA','EDELWEISS','EICHERMOT','ELGIEQUIP','EMAMILTD','ENDURANCE','ENGINERSIN','EQUITAS','ERIS','ESCORTS','EXIDEIND','FDC','FEDERALBNK','FINEORG','FINCABLES','FINPIPE','FSL','FORTIS','FCONSUMER','FRETAIL','GAIL','GEPIL','GHCL','GMMPFAUDLR','GMRINFRA','GALAXYSURF','GRSE','GARFIBRES','GICRE','GILLETTE','GLAXO','GLENMARK','GODFRYPHLP','GODREJAGRO','GODREJCP','GODREJIND','GODREJPROP','GRANULES','GRAPHITE','GRASIM','GESHIP','GREAVESCOT','GRINDWELL','GUJALKALI','GAEL','FLUOROCHEM','GUJGASLTD','GMDCLTD','GNFC','GPPL','GSFC','GSPL','GULFOILLUB','HEG','HCLTECH','HDFCAMC','HDFCBANK','HDFCLIFE','HFCL','HATHWAY','HATSUN','HAVELLS','HEIDELBERG','HERITGFOOD','HEROMOTOCO','HSCL','HINDALCO','HAL','HINDCOPPER','HINDPETRO','HINDUNILVR','HINDZINC','HONAUT','HUDCO','HDFC','HUHTAMAKI','ICICIBANK','ICICIGI','ICICIPRULI','ISEC','ICRA','IDBI','IDFCFIRSTB','IDFC','IFBIND','IIFL','IIFLWAM','IOLCP','IRB','IRCON','ITC','ITI','INDIACEM','IBULHSGFIN','IBREALEST','INDIAMART','INDIANB','IEX','INDHOTEL','IOC','IOB','IRCTC','INDOCO','IGL','INDUSINDBK','NAUKRI','INFY','INGERRAND','INOXLEISUR','INDIGO','IPCALAB','JBCHEPHARM','JKCEMENT','JKLAKSHMI','JKPAPER','JKTYRE','JMFINANCIL','JSWENERGY','JSWSTEEL','JTEKTINDIA','JAGRAN','JAICORPLTD','J&KBANK','JAMNAAUTO','JINDALSAW','JSLHISAR','JSL','JINDALSTEL','JCHAC','JUBLFOOD','JUSTDIAL','JYOTHYLAB','KEI','KNRCON','KRBL','KSB','KAJARIACER','KALPATPOWR','KANSAINER','KTKBANK','KARURVYSYA','KSCL','KEC','KOLTEPATIL','KOTAKBANK','L&TFH','LTTS','LICHSGFIN','LAOPALA','LAXMIMACH','LTI','LT','LAURUSLABS','LEMONTREE','LINDEINDIA','LUPIN','LUXIND','MASFIN','MMTC','MOIL','MRF','MGL','MAHSCOOTER','MAHSEAMLES','M&MFIN','M&M','MAHINDCIE','MHRIL','MAHLOG','MANAPPURAM','MRPL','MARICO','MARUTI','MFSL','METROPOLIS','MINDTREE','MINDACORP','MINDAIND','MIDHANI','MOTHERSUMI','MOTILALOFS','MPHASIS','MCX','MUTHOOTFIN','NATCOPHARM','NBCC','NCC','NESCO','NHPC','NLCINDIA','NMDC','NOCIL','NTPC','NH','NATIONALUM','NFL','NAVINFLUOR','NAVNETEDUL','NESTLEIND','NETWORK18','NILKAMAL','NAM-INDIA','OBEROIRLTY','ONGC','OIL','OMAXE','OFSS','ORIENTCEM','ORIENTELEC','ORIENTREF','PIIND','PNBHOUSING','PNCINFRA','PSPPROJECT','PTC','PVR','PAGEIND','PERSISTENT','PETRONET','PFIZER','PHILIPCARB','PHOENIXLTD','PIDILITIND','PEL','POLYMED','POLYCAB','POLYPLEX','PFC','POWERGRID','PRAJIND','PRESTIGE','PRSMJOHNSN','PGHL','PGHH','PNB','QUESS','RBLBANK','RECLTD','RITES','RADICO','RVNL','RAIN','RAJESHEXPO','RALLIS','RCF','RATNAMANI','RAYMOND','REDINGTON','RELAXO','RELIANCE','SBICARD','SBILIFE','SJVN','SKFINDIA','SRF','SANOFI','SCHAEFFLER','SCHNEIDER','SIS','SEQUENT','SFL','SHILPAMED','SCI','SHOPERSTOP','SHREECEM','SHRIRAMCIT','SRTRANSFIN','SIEMENS','SOBHA','SOLARINDS','SOLARA','SONATSOFTW','SOUTHBANK','SPICEJET','STARCEMENT','SBIN','SAIL','SWSOLAR','STLTECH','STAR','SUDARSCHEM','SUMICHEM','SPARC','SUNPHARMA','SUNTV','SUNDARMFIN','SUNDRMFAST','SUNTECK','SUPRAJIT','SUPREMEIND','SUPPETRO','SUVENPHAR','SUZLON','SWANENERGY','SWARAJENG','SYMPHONY','SYNGENE','TCIEXP','TCNSBRANDS','TTKPRESTIG','TVTODAY','TV18BRDCST','TVSMOTOR','TASTYBITE','TATACHEM','TATACOFFEE','TATACOMM','TCS','TATACONSUM','TATAELXSI','TATAINVEST','TATAMTRDVR','TATAMOTORS','TATAPOWER','TATASTLBSL','TATASTEEL','TEAMLEASE','TECHM','NIACL','RAMCOCEM','THERMAX','THYROCARE','TIMKEN','TITAN','TORNTPHARM','TORNTPOWER','TRENT','TRIDENT','TIINDIA','UCOBANK','UFLEX','UPL','UJJIVAN','UJJIVANSFB','ULTRACEMCO','UNIONBANK','UBL','MCDOWELL-N','VGUARD','VMART','VIPIND','VRLLOG','VSTIND','VAIBHAVGBL','VAKRANGEE','VTL','VARROC','VBL','VENKEYS','VINATIORGA','IDEA','VOLTAS','WABCOINDIA','WELCORP','WELSPUNIND','WESTLIFE','WHIRLPOOL','WIPRO','WOCKPHARMA','YESBANK','ZEEL','ZENSARTECH','ZYDUSWELL','ECLERX']

start = date (2019, 12, 1)
end = date (2020, 12, 10)


for stock_name in stock:
      data = get_history(symbol=stock_name, start=start, end=end)

nsepy模块的get_history函数根据开始和结束日期获取给定符号的数据。生成的数据帧如图所示：

我的疑问是，由于我为每个符号的数据帧赋值，以前的数据会被覆盖

因此，是否有一种方法可以将每个符号的相似数据存储在同一数据帧中

Answer 1

你最好创建一个以股票为关键字的字典。见下文：

res={}

for stock_name in stock:
      data = get_history(symbol=stock_name, start=start, end=end)
      res[stock_name]=data

然后，您可以通过res[stock_name]调用每个数据帧，例如res['POWERINDIA']将提供此特定股票的数据