code: def daily_txns_with_bar_data(transactions, market_data):
      
  
      transactions.index.name = 'date'
      txn_daily = pd.DataFrame(transactions.assign(
          amount=abs(transactions.amount)).groupby(
          ['symbol', pd.TimeGrouper('D')]).sum()['amount'])
      txn_daily['price'] = market_data['price'].unstack()
      txn_daily['volume'] = market_data['volume'].unstack()
  
      txn_daily = txn_daily.reset_index().set_index('date')
  
      return txn_daily
docs: Sums the absolute value of shares traded in each name on each day.
      Adds columns containing the closing price and total daily volume for
      each day-ticker combination.
  
      Parameters
      ----------
      transactions : pd.DataFrame
          Prices and amounts of executed trades. One row per trade.
          - See full explanation in tears.create_full_tear_sheet
      market_data : pd.Panel
          Contains "volume" and "price" DataFrames for the tickers
          in the passed positions DataFrames
  
      Returns
      -------
      txn_daily : pd.DataFrame
          Daily totals for transacted shares in each traded name.
          price and volume columns for close price and daily volume for
          the corresponding ticker, respectively.