code: def detect_intraday(positions, transactions, threshold=0.25):
      """
      Attempt to detect an intraday strategy. Get the number of
      positions held at the end of the day, and divide that by the
      number of unique stocks transacted every day. If the average quotient
      is below a threshold, then an intraday strategy is detected.
  
      Parameters
      ----------
      positions : pd.DataFrame
          Daily net position values.
           - See full explanation in create_full_tear_sheet.
      transactions : pd.DataFrame
          Prices and amounts of executed trades. One row per trade.
           - See full explanation in create_full_tear_sheet.
  
      Returns
      -------
      boolean
          True if an intraday strategy is detected.
      """
  
      daily_txn = transactions.copy()
      daily_txn.index = daily_txn.index.date
      txn_count = daily_txn.groupby(level=0).symbol.nunique().sum()
      daily_pos = positions.drop("cash", axis=1).replace(0, np.nan)
      return daily_pos.count(axis=1).sum() / txn_count < threshold
  
imports: from __future__ import division
  import warnings
  from itertools import cycle
  from matplotlib.pyplot import cm
  import numpy
  import pandas
  from IPython.display import display, HTML
  import empyrical.utils
  from .None import pos
  from .None import txn
label_desc: Use image node_id 9 for calling a global function with example usage: detect_intraday(positions, transactions, threshold) and returns: unknown