class_docstr: Univariate empirical cumulative distribution estimator.
class_docstr_tok: ["Univariate","empirical","cumulative","distribution","estimator","."]
docstr: Initialize the class with its parameters
  
  Parameters
  ----------
  stat : {{"proportion", "percent", "count"}}
      Distribution statistic to compute.
  complementary : bool
      If True, use the complementary CDF (1 - CDF)
docstr_tok: ["Initialize","the","class","with","its","parameters","Parameters","--","--","--","--","--","stat",":","{","{","``","proportion","''",",","``","percent","''",",","``","count","''","}","}","Distribution","statistic","to","compute",".","complementary",":","bool","If","True",",","use","the","complementary","CDF","(","1","-","CDF",")"]
code: def __init__(self, stat="proportion", complementary=False):
      """Initialize the class with its parameters
  
      Parameters
      ----------
      stat : {{"proportion", "percent", "count"}}
          Distribution statistic to compute.
      complementary : bool
          If True, use the complementary CDF (1 - CDF)
  
      """
      _check_argument("stat", ["count", "percent", "proportion"], stat)
      self.stat = stat
      self.complementary = complementary
  
imports: from numbers import Number
  from statistics import NormalDist
  import numpy
  import pandas
  from .algorithms import bootstrap
  from .utils import _check_argument
label_desc: Use image node_id 1 to create a new ECDF object  with example: obj = ECDF(stat, complementary)