Interating For a Month of 1Min Data

I am trying to iterate over a month of Alpaca data at “1Min” intervals to build a parameter search tool and backtest. However, I cannot figure out why I am not getting the right data. I am putting in start and end dates to get get a bracket of time. However, it spits out the completely wrong dates.

Any ideas on what I may be doing wrong?

Hey @Cloblak!

If you modify the date parameters to check only for 6-22 to 6-23, just as an example, do you get additional data or no?

Yea! I had to build a loop that changed the end date to the last date on the current data pull, going back until it matched the data I need.

def days_of_data_single_stock(ticker, interval, days_to_collect):
    ticker_data_dict = None
    ticker_data_dict = {}
    monthly_data_dict = None
    monthly_data_dict = {}
    interval_loop_data = None
    interval_loop_data = pd.DataFrame()
    stock_data = None
    TZ = 'America/New_York'
    start_str = ( - timedelta(days=days_to_collect)).strftime("%m-%d-%Y %H:%M")
    start=pd.Timestamp(start_str, tz=TZ).isoformat()

    end_str ="%m-%d-%Y %H:%M")
    end = pd.Timestamp(end_str, tz=TZ).isoformat()
    stock_data = api_paper.get_barset(ticker, interval, end = end, limit=1000).df
    stock_data = stock_data.reset_index()
    interval_loop_data = interval_loop_data.append(stock_data)
    df_start_ref = interval_loop_data["time"][0]
    start_str_ref = pd.Timestamp(start)
    #print(start_str_ref.value < df_start_ref.value)

    while start_str_ref.value < (df_start_ref - pd.Timedelta(days=1)).value:
        end_new = pd.Timestamp(interval_loop_data["time"].iloc[0].strftime("%Y-%m-%d"), tz=TZ).isoformat()
        stock_data_new = None
        stock_data_new = api_paper.get_barset(ticker, interval, start = start, end = end_new, limit=1000).df
        stock_data_new = stock_data_new.reset_index()
        interval_loop_data = interval_loop_data.append(stock_data_new).sort_values(by=['time'], ascending=True)
        df_start_ref = interval_loop_data["time"].iloc[0]
        #print(start_str_ref.value < df_start_ref.value, start_str_ref, df_start_ref, (df_start_ref - pd.Timedelta(days=1)))
    return interval_loop_data.reset_index()