The sum of all the 5 minute or 1 hour volume data does not add upto the daily volume data

[fsagir123]

I have been trying to get the volume traded from the begining of market hours until the current time on a trading day. To check if adding the 5 minute or 1 hour volumes add correctly to estimate the volume traded for a day I tested it for TSLA and AAPL for July 19th 2024. But the results show that they are highly divergent.

The daily volumes are more than twice the sum of the 5 minute or 1 hour for TSLA and more than thrice for AAPL. Is this an issue with robin_stocks or with the app itself? Is there another way to find the total volume traded up until the current time using any other method?

I have attached the below excel files which show the discrepency. The last line is the volume extracted from add the 5 minute or 1 hour data and the second last line is extracted from the get_historical_data for the previous day.

RF_past_year_AAPL_data_with_prediction.xlsx RF_past_year_TSLA_data_with_prediction.xlsx

I used the below code to extract that day's trading data if interval == "day":

    stock_data_shorter_interval = rs.get_stock_historicals(stock_ticker, interval=shorter_interval, span=interval, bounds="trading")
    stock_data_shorter_interval = pd.DataFrame.from_dict(stock_data_shorter_interval)
    stock_data_shorter_interval[['close_price', 'high_price','low_price','open_price','volume']] = stock_data_shorter_interval[['close_price', 
    'high_price','low_price','open_price','volume']].apply(pd.to_numeric, errors='coerce')

    todays_data = pd.DataFrame({'open_price':[stock_data_shorter_interval['open_price'].iloc[0]],
               'high_price':[stock_data_shorter_interval['high_price'].max()],
               'low_price':[stock_data_shorter_interval['low_price'].min()],
               'close_price':[stock_data_shorter_interval['close_price'].iloc[-1]],
               'volume':[stock_data_shorter_interval['volume'].sum()]})