code: def _rankdata_no_ties(x):
      """rankdata without ties for 2-d array
  
      This is a simplified version for ranking data if there are no ties.
      Works vectorized across columns.
  
      See Also
      --------
      scipy.stats.rankdata
  
      """
      nobs, k_vars = x.shape
      ranks = np.ones((nobs, k_vars))
      sidx = np.argsort(x, axis=0)
      ranks[sidx, np.arange(k_vars)] = np.arange(1, nobs + 1)[:, None]
      return ranks
  
file_path: statsmodels/statsmodels/distributions/tools.py
imports: import warnings
  import numpy
  from scipy import interpolate, stats
label_desc: Use image node_id 5 for calling a global function with example usage: _rankdata_no_ties(x) and returns: ranks