Pulling historical data for a specific ric in Python versus Excel.

Dada
Dada LSEG
edited 7:19AM in Refinitiv Data Platform Libraries

Der Team,

I have a client asking the following:

Good morning Charlotte,

I hope you are doing well.

I am reaching out as there appears to be an issue pulling historical data for a specific ric in Python versus Excel.

I am currently able to pull via python historical barge freight. When I try the same for CIF NOLA Corn, it returns no data (NA). However, for the same ric I am able to pull the data on excel without any issues.

Here is an example of the code snippet ……. I have attached the email. - Can you please help me with this client request?.

Thanks a lot

Daniela

import pandas as pdimport eikon as ekek.set_app_key('3c6a5c9b106142d88b53b2c0844cf2dcb22c37f1')  # TPW key# Get the last business day datedate = (pd.Timestamp.today() - pd.offsets.BDay(1)).strftime('%Y-%m-%d')date_start = '2019-01-01'  # Start date for historical datadate_end = pd.Timestamp.today().strftime('%Y-%m-%d')df = ek.get_timeseries('C-USNOLAC-C1',fields=['CLOSE'],start_date= date_start,end_date=date_end,interval='daily')
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Answers

  • Gurpreet
    Gurpreet admin
    edited June 24
    https://community.developers.refinitiv.com/discussion/132507/pulling-historical-data-for-a-specific-ric-in-python-versus-excel

    Please don't post user information or other privacy data on these public forums! I have removed the offending attachment.

  • Jirapongse
    Jirapongse ✭✭✭✭✭

    @Dada

    The client can remove the fields parameter so the API will return all available fields of the subscribed RIC.

    df = ek.get_timeseries('C-USNOLAC-C1',start_date= date_start,end_date=date_end,interval='daily')
df

    It looks like that the correct field for C-USNOLAC-C1 is VALUE.

    image.png

    The Eikon Data API is quite old. Please inform the client to use the LSEG Data Library for Python instead. The examples are available on GitHub. The client can use the get_history method to get historical data. 

    datedate = (pd.Timestamp.today() - pd.offsets.BDay(1)).strftime('%Y-%m-%d')
date_start = '2019-01-01'  # Start date for historical 
date_end = pd.Timestamp.today().strftime('%Y-%m-%d')
df = ld.get_history('C-USNOLAC-C1',start= date_start,end=date_end,interval='1D')
df

    The output is:

    image.png

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