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koorukuroo/finance_data.py

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pandas get_data_yahoo
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finance_data.py
import pandas as pd
import pandas.io.data
import datetime
#text = """A, AAPL, AMCC, AMD, AMGN, AMKR, AMNT.OB, AMZN, APC, ASOG.PK, AULO.OB, BAC, BBD-A.TO, BBD-B.TO, BEEI.OB, BKSD.OB, BP.BA, BPMI.PK, C, CAJT.PK, CAT, CGFI.OB, CHINA, CHKP, CIEN, CL, CLEC, CLNE, CNLG, COKE, CPAH.OB, CPHD, CPRT, CRDN, CRGN, CSCO, CSRVE.OB, CTS, CTXS, CVM, CVX, DE, DELL, DLTR, DO, DOG, DSCM, DVNNF.OB, DYN, EGN, ELNK, ELX, EP, ERJ, ETFC, EVEH.OB, FARO, FDO, FILE, FLIR, FNLY.OB, FNPR.OB, FORC.OB, FPP, GAGO.PK, GBVS.OB, GCAP.PK, GDKI.PK, GDTI.OB, GE, GEPT.PK, GERN, GFCI.PK, GILD, GLW, GOOG, GRDB.OB, GRMN, GS, GTXO.OB, GWGI.PK, HAL, HAST, HCKT, HD, HK, HPQ, HRAL.PK, IBM, IMDS.OB, IMGM.OB, INFY, INTC, IOC, IRF, JAVA, JCP, JDSU, JNJ, JNPR, JYHW.OB, K, KDSM.OB, KKD, KLDO.OB, KO, LEG, LOW, LRCX, LU, medx, MINI, MKC, MLNK, MNLU.OB, MO, MON, MOT, MRK, MSFT, MVBY.PK, MYL, NGEN, NGLS, NOIZ, NOK, NOVL, NOVOE.OB, NTGR, NVDA, NVS, NXRA.PK, OMI, ORCL, OSTK, PDLI, PEGA, PEP, PFE, PG, PHLI.OB, PNM, PPBV.OB, PWER, PYTO.OB, PZE, PZZA, Q, QCOM, QPCIE.OB, RIG, RIO, S, SBR, SCMR, SCON, SGAL.OB, SGP, SHRPQ.PK, SIFY, SIRI, SLB, smd, SUN, SVA, T, TAMO.OB, TASR, TEF, TNEN.OB, TRXAQ.PK, TWX, TXN, UTVG.OB, VOD, VRTL.PK, VSCI, VTSS.PK, VZ, WAG, WCYO.OB, WFC, WLL, WMT"""
#text = text.replace(' ', '').split(',')
#temp = []
#for t in text:
# if '.' not in t:
# temp.append(t)
#corps = temp
corps = ['A',
'AAPL',
'AMCC',
'AMD',
'AMGN',
'AMKR',
'AMZN',
'APC',
'BAC',
'C',
'CAT',
'CHKP',
'CIEN',
'CL',
'CLNE',
'CNLG',
'COKE',
'CPHD',
'CPRT',
'CSCO',
'CTS',
'CTXS',
'CVM',
'CVX',
'DE',
'DLTR',
'DO',
'DOG',
'DYN',
'EGN',
'ELNK',
'ELX',
'ERJ',
'ETFC',
'FARO',
'FLIR',
'FPP',
'GE',
'GERN',
'GILD',
'GLW',
'GOOG',
'GRMN',
'GS',
'HAL',
'HCKT',
'HD',
'HK',
'HPQ',
'IBM',
'INFY',
'INTC',
'IOC',
'JCP',
'JDSU',
'JNJ',
'JNPR',
'K',
'KKD',
'KO',
'LEG',
'LOW',
'LRCX',
'MINI',
'MKC',
'MLNK',
'MO',
'MON',
'MRK',
'MSFT',
'MYL',
'NGLS',
'NOK',
'NTGR',
'NVDA',
'NVS',
'OMI',
'ORCL',
'OSTK',
'PDLI',
'PEGA',
'PEP',
'PFE',
'PG',
'PNM',
'PZE',
'PZZA',
'Q',
'QCOM',
'RIG',
'RIO',
'S',
'SBR',
'SCMR',
'SCON',
'SGP',
'SIFY',
'SIRI',
'SLB',
'smd',
'SUN',
'SVA',
'T',
'TASR',
'TEF',
'TWX',
'TXN',
'VOD',
'VZ',
'WFC',
'WLL',
'WMT']
start = datetime.datetime(2015, 1, 1)
end = datetime.datetime(2015, 8, 25)
df = pd.io.data.get_data_yahoo(corps, start=start, end=end)
df['Adj Close'].head()
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