how download a data into csv file

Hello Guys, i´m trying to download a data with get_timeseries and when i get it i have a problem with my csv file.

I currently use:

import eikon as ek

ek.set_app_id('XXXXXXXXXXXXXXXXXXX')

df=ek.get_timeseries(['CARC.BA','CEL.BA','CAMb.BA','COL.BA','DYC.BA','ESM.BA','FER.BA','FIP.BA','GAR.BA',
'GBA.BA','CLA.BA','GRM.BA','CEC.BA','INR.BA','IRCP.BA','IRCP.BA','LON.BA','.MERV',
'.MAR','.MER25','ARBPLD3=BA','ARCUAP3=BA','ARDICA3=BA','ARDICP3=BA','ARDICY3=BA',
'ARNO203=BA','ARPARA3=BA','ARPARY3=BA','ARPR133=BA','ARTVPA3=BA','ARTVPP3=BA',
'ARTVPY3=BA','ARBP283=BA','ARBPMD3=BA','ARPARP3=BA','ARBARX13=BA','ARBPLE3=BA'],
interval="daily",
fields=['date','open','high','low','close'],
start_date='2000-01-01' , end_date='2008-01-01')

df.to_csv('ALFIN1.csv')

and then my data come

i have a problem with my date... run like the year is the day

2001-11-29

2002-02-27

2003-08-25

.........

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Accepted answers

your request causes too large result (too many instruments and too large range of date), then you meet the limit of 3000 datapoints. That's why a lot data has NaN value.

Note that 'date' field doesn't exists for timeseries, right name is 'timestamp' that is included by default in result.

If you reduce the number of instrument and the range of date, the result makes sense:

>>> df2=ek.get_timeseries(['CARC.BA','CEL.BA'], interval="daily", fields=['open','high','low','close'], start_date='2000-01-01' , end_date='2002-01-01')
>>> df2.head()
Security     CARC.BA                                  CEL.BA            \
Field           OPEN      HIGH       LOW     CLOSE      OPEN      HIGH
Date
2000-01-03  0.250202  0.250202  0.240194  0.240194  0.331061  0.331061
2000-01-04  0.225182  0.235190  0.225182  0.235190       NaN       NaN
2000-01-05  0.225182  0.225182  0.225182  0.225182  0.308489  0.308489
2000-01-06  0.220178  0.225182  0.220178  0.225182       NaN       NaN
2000-01-07  0.225182  0.225182  0.225182  0.225182       NaN       NaN

Security
Field            LOW     CLOSE
Date
2000-01-03  0.331061  0.331061
2000-01-04       NaN       NaN
2000-01-05  0.308489  0.308489
2000-01-06       NaN       NaN
2000-01-07       NaN       NaN
>>>

All comments

your request causes too large result (too many instruments and too large range of date), then you meet the limit of 3000 datapoints. That's why a lot data has NaN value.

Note that 'date' field doesn't exists for timeseries, right name is 'timestamp' that is included by default in result.

If you reduce the number of instrument and the range of date, the result makes sense:

>>> df2=ek.get_timeseries(['CARC.BA','CEL.BA'], interval="daily", fields=['open','high','low','close'], start_date='2000-01-01' , end_date='2002-01-01')
>>> df2.head()
Security     CARC.BA                                  CEL.BA            \
Field           OPEN      HIGH       LOW     CLOSE      OPEN      HIGH
Date
2000-01-03  0.250202  0.250202  0.240194  0.240194  0.331061  0.331061
2000-01-04  0.225182  0.235190  0.225182  0.235190       NaN       NaN
2000-01-05  0.225182  0.225182  0.225182  0.225182  0.308489  0.308489
2000-01-06  0.220178  0.225182  0.220178  0.225182       NaN       NaN
2000-01-07  0.225182  0.225182  0.225182  0.225182       NaN       NaN

Security
Field            LOW     CLOSE
Date
2000-01-03  0.331061  0.331061
2000-01-04       NaN       NaN
2000-01-05  0.308489  0.308489
2000-01-06       NaN       NaN
2000-01-07       NaN       NaN
>>>

pablo

Thanks so mouch

pablo

Otherwise, within my RIC´S list 'AGR.BA','ALU.BA','APBR.BA','AUS.BA','BHI.BA'

,'BMA.BA','BOL.BA','BYMA.BA','cec.ba','CEPU.BA','COM.BA','CRE.BA','CON.BA','ECO.BA','EDN.BA','SID.BA',

'FRA.BA','GFG.BA','HARG.BA','MIR.BA','OEST.BA','PAM.BA','PGR.BA','SMI.BA','SUPV.BA','TEC2.BA','TGNC.BA',

'TGS2.BA','TRA.BA','TENA.BA','YPFD.BA','BPAT.BA','RIO.BA','CAO.BA','CAU.BA','CARC.BA','CEL.BA','CAMb.BA','COL.BA',

'CTGM.BA','CVH.BA','DYC.BA','EDLH.BA','EMDH.BA','ESM.BA','FER.BA','FIP.BA','GAR.BA','GBA.BA','CLA.BA','GRM.BA','HAVH.BA',

'CEC.BA','INR.BA','INVJ.BA','IRCP.BA','IRCP.BA','LEDh.BA','LOMA.BA','LON.BA','metr.BA','.MERV','.MAR','.MER25','ARA2E23=BA',

'ARA2E2D3=BA','ARA2E73=BA','ARA2E7D3=BA','ARA2E83=BA','ARA2E8D3=BA','ARA2M23=BA','ARAA21D3=BA','ARAA22X3=BA',

'ARAA22Z3=BA','ARAA253=BA','ARAA25D3=BA','ARAA263=BA','ARAA373=BA','ARAA37D3=BA','ARAA46D3=BA','ARAC173=BA',

'ARAC17D3=BA','ARAE483=BA','ARAE48D3=BA','ARAF193=BA','ARAM203=BA','ARAMX93=BA','ARAN183=BA','ARAN18D3=BA',

'ARAO203=BA','ARAO20D3=BA','ARAY243=BA','ARAY24D3=BA','ARBCIUA3=BA','ARBD2C93=BA','ARBDC193=BA','ARBDC223=BA',

'ARBPLD3=BA','ARBPLDD3=BA','ARCEDI3=BA','ARCH24D3=BA','ARCO24D3=BA','ARCO263=BA','ARCO26D3=BA','ARCUAP3=BA',

'ARDIA03=BA','ARDICA3=BA','ARDICAD3=BA','ARDICP3=BA','ARDICPD3=BA','ARDICY3=BA','ARDICYD3=BA','ARDIY03=BA',

'ARNO203=BA','ARPAA03=BA','ARPAA0D3=BA','ARPAP03=BA','ARPARA3=BA','ARPARAD3=BA','ARPARY3=BA','ARPARYD3=BA',

'ARPAY03=BA','ARPB21D3=BA','ARPBF233=BA','ARPBM243=BA','ARPF23D3=BA','ARPMG183=BA','ARPMJ213=BA','ARPMN183=BA',

'ARPMO183=BA','ARPR133=BA','ARPR153=BA','ARPUM213=BA','ARPUO193=BA','ARRNG233=BA','ARSA24D3=BA','ARTC213=BA','ARTC233=BA',

'ARTJ203=BA','ARTO263=BA','ARTVPA3=BA','ARTVPAD3=BA','ARTVPE3=BA','ARTVPP3=BA','ARTVPY3=BA','ARTVPYD3=BA','ARPSUR3=BA',

'ARSTD3=BA','ARKO3=BA','ARLMT3=BA','ARA2E33=BA','ARA2E3D3=BA','ARAA223=BA','ARAA463=BA','ARBDC203=BA','ARBDC283=BA','ARBP283=BA',

'ARBPMD3=BA','ARCCO263=BA','ARDIA0D3=BA','ARPARP3=BA','ARPMD183=BA','ARRI25D3=BA','ARTC203=BA','ARTFU273=BA','ARTS183=BA',

'ARINAG3=BA','ARBRIO63=BA','ARDOME3=BA','AREDSH3=BA','ARMTBA3=BA','ARMSFT3=BA','ARAA193=BA','ARAA19D3=BA','ARAA213=BA',

'ARBARX13=BA','ARBDC243=BA','ARBOC6O3=BA','ARBP18D3=BA','ARBP213=BA','ARBP28D3=BA','ARBPLE3=BA','ARBPLED3=BA','ARDICE3=BA',

'ARDIP03=BA','ARNDG213=BA','ARPAY0D3=BA','ARPB24D3=BA','ARPB27D3=BA','ARPBY223=BA','ARPMY243=BA','ARS24DD3=BA','ARTO213=BA',

'ARTU27D3=BA','ARTVY03=BA','ARABT3=BA','ARHMY3=BA','ARMON3=BA','ARPFE3=BA','ARQCOM3=BA','ARXOM3=BA','ARA2M2Z3=BA','ARAA26D3=BA',

'ARERF253=BA','ARPARE3=BA','ARPBD193=BA','ARPBJ273=BA','ARABX3=BA','ARBSBR3=BA','ARCAT3=BA','ARPU23D3=BA','ARTXAR3=BA','ARBA.C3=BA',

'ARJPM3=BA','ARRIO3=BA','ARCHSG13=BA','ARLEID3=BA','ARDIY0D3=BA','ARMERA3=BA','ARHULI3=BA','ARIBM3=BA','ARRNG223=BA','ARSLB3=BA',

'ARPBA253=BA','ARPBJ9D3=BA','ARPU26D3=BA','ARRIF253=BA','ARTO233=BA'

AT LEAST THE 70% OF THEM HAVE AN ERROR LIKE

INVALID RIC

Alex Putkov.1

@pablo
Did you mean to ask a question here? If yes, I'm not sure what you're asking. A bunch of RICs on your list are indeed invalid, e.g. SID.BA, EMDH.BA, ARAA22X3=BA, ARAA22Z3=BA etc. If you meant to ask something, would you mind elaborating on your question?

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