code: def std_prop(prop, nobs):
      """
      Standard error for the estimate of a proportion
  
      This is just ``np.sqrt(p * (1. - p) / nobs)``
  
      Parameters
      ----------
      prop : array_like
          proportion
      nobs : int, array_like
          number of observations
  
      Returns
      -------
      std : array_like
          standard error for a proportion of nobs independent observations
      """
      return np.sqrt(prop * (1.0 - prop) / nobs)
  
imports: from statsmodels.compat.python import lzip
  from typing import Callable
  import numpy
  import pandas
  from scipy import optimize, stats
  from statsmodels.stats.base import AllPairsResults, HolderTuple
  from statsmodels.stats.weightstats import _zstat_generic2
  from statsmodels.tools.sm_exceptions import HypothesisTestWarning
  from statsmodels.tools.testing import Holder
  from statsmodels.tools.validation import array_like
label_desc: Use image node_id 7 for calling a global function with example usage: std_prop(prop, nobs) and returns: np