Efficient way to get interval HiLo price for a list of stocks with different date time interval

thomas.ng

Given the exmaple dataframe below (real dataframe is more than few thousand rows), what is the most efficient way to obtain the maximum high price and minimum low price given the ricCode and startDate and endDate of each row of the dataframe ?

{'ricCode': {0: '0.0700.HK', 2: '0700.HK', 3: '9988.HK, 6: '2388.HK', 7: 'NVDA.O, 8: 'AMD.O'}, 'startDate': {0: '2023-03-13', 2: '2023-03-16', 3: '2023-05-03', 6: '2024-01-29', 7: '2025-01-06', 8: '2024-11-19'}, 'endDate': {0: '2023-03-13', 2: '2023-03-16', 3: '2023-05-03', 6: '2024-01-29', 7: '2025-01-06', 8: '2024-11-19'}}

Currently, I am using a for loop to iterate through each row of data frame. This is not only slow and it sometimes doesn't even return any output and just got stuck at times, Would appreciate a more efficient and error-prone way to do this, given the the start date and end date are different each row.

def get_rd_data(row):

try:

rd_out = rd.get_data(universe=row['ricCode'],fields=['MAX(TR.HIGHPRICE)','MIN(TR.LOWPRICE)'], parameters={'SDate':row[‘startDate'], 'EDate':row['endDate'], 'Frq':'D','Adjusted':1}) # adjusted already

except:

out = get_rd_data(row)

return out

output = pd.DataFrame()

for idx, row in data.iterrows():

output = pd.concat([output,get_rd_data(row)], axis=0)

Jirapongse

@thomas.ng

Thank you for reaching out to us.

It looks like that the application retrieves data at different dates for each RIC. For example:

If this is correct, you need to call the get_data method for each row at a time.

Moreover, you need to add the retry logic in the try/except block. You can refer to the following discussions.

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