Is there an interval type 30 minutes for python api?

df1=ek.get_timeseries(s1,fields=["Open","High","Low","Close","Volume"],
start_date = "2017-11-13T01:00:00",end_date = "2017-11-13T07:04:05",interval='minute')

Do u have any high effect ways to handle this data into 5mins bar?

wyj

I hope there got 5mins, 30mins,hour.....

This a simple example to extract a 30 minute interval timeseries from a minute interval result:

import eikon as ek
from datetime import timedelta

interval = 30

def ohlcsum(df):
    return [df['OPEN'][0],df['HIGH'].max(),df['LOW'].min(),
           df['CLOSE'][-1],int(df['VOLUME'].sum())]

data_1min = ek.get_timeseries('PEUP.PA', interval='minute')
timestamps=[]
result=[]
start_slice = data_1min.index[0]
while True:
    end_slice = start_slice + timedelta(minutes=interval-1)
    interval_slice = data_1min.loc[start_slice : end_slice]
    try:
        data = ohlcsum(interval_slice)
    except IndexError:
        break
    timestamps.append(interval_slice.index[-1])
    result.append(data)
    start_slice = start_slice + timedelta(minutes=interval)
    if start_slice > data_1min.index[-1]:
        break

labels = ['OPEN','HIGH','LOW','CLOSE','VOLUME']
data_new_interval = pd.DataFrame.from_records(result, index=timestamps, columns=labels)

wyj

I don't think u got the right data for 5 min

for every 5 min data, it should be calculated by the following function

def ohlcsum(df):
    df = df.sort()
    return {
       'Open': df['Open'][0],
       'High': df['High'].max(),
       'Low': df['Low'].min(),
       'Close': df['Close'][-1],
       'Volume': df['Volume'].sum()
      }

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