Daily To Weekly Data Conversion Extra Line In Output

I'm looking to convert daily data into weekly data. Input data OUTPUT DATA AT PRESENT AFTER CONVERTING TO WEEKLY candle_date open high low close

Solution 1:

   def convert_dailydata_to_weeklydata(daily_data):
        # Print function name
        SupportMethods.print_func_name()

        # Loop over the rows until a row with Monday as date is present
        row_counter_start = 0
        while True:
            if datetime.weekday(daily_data['candle_date'][row_counter_start]) == 0:
                break
            row_counter_start += 1

        # # Loop over the rows until a row with Sunday as date is present
        # row_counter_end = len(daily_data.index) - 1
        # while True:
        #     if datetime.weekday(daily_data['candle_date'][row_counter_end]) == 6:
        #         break
        #     row_counter_end -= 1
        # print(daily_data)
        # print(row_counter_end)

        # Copy all rows after the first Monday row of data is reached
        daily_data_temp = daily_data[row_counter_start:]

        # Getting week number
        daily_data_temp['Week_Number'] = pd.to_datetime(daily_data_temp['candle_date']).dt.week

        # Getting year. Weeknum is common across years to we need to create unique index by using year and weeknum
        daily_data_temp['Year'] = pd.to_datetime(daily_data_temp['candle_date']).dt.year

        # Grouping based on required values
        df = daily_data_temp.groupby(['Year', 'Week_Number']).agg(
            {'open': 'first', 'high': 'max', 'low': 'min', 'close': 'last', 'volume': 'sum', 'market_cap': 'sum'})

        # Reset index
        df = df.reset_index()

        # Create week date (start of week)
        # The + "1" isfor the day of the week.Week numbers 0-6 with 0 being Sunday and 6 being Saturday.
        df['week_date'] = pd.to_datetime(df['Year'].astype(str) + df['Week_Number'].astype(str) + "1", format='%G%V%w')

        # Set indexes
        df = df.set_index(['Year', 'Week_Number'])

        # Re-order columns into a new dataframe
        weekly_data = df[["week_date", "open", "high", "low", "close", "volume", "market_cap"]]
        weekly_data = weekly_data.rename({'week_date': 'candle_date'}, axis=1)

        # Drop index columns
        weekly_data.reset_index(drop=True, inplace=True)

        # Return data by dropping curent week's data
        if datetime.weekday(weekly_data.head(-1)['candle_date']) != 0:
            return weekly_data.head(-1)
        else:
            return weekly_data