text: """
  Inferring a binomial proportion via exact mathematical analysis.
  """
  import sys
  import numpy as np
  from scipy.stats import beta
  from scipy.special import beta as beta_func
  import matplotlib.pyplot as plt
  import matplotlib.patches as patches
  #from HDIofICDF import *
  from scipy.optimize import fmin
  #from scipy.stats import *
  import scipy
  from scipy.stats import beta
  from scipy import special
  from scipy import stats
  import random
  from scipy.special.basic import bernoulli
  import math
  from pylab import mlab
  import json
  from builtins import staticmethod
  import copy
  from sklearn.gaussian_process import GaussianProcessRegressor
  from sklearn.gaussian_process.kernels import RBF, ConstantKernel as C
  from scipy.stats import binom
  from sklearn.preprocessing import normalize as probNorm
  import timeit
  import pandas
  import matplotlib.pyplot as plt
  from pandas.plotting import parallel_coordinates
  import io
  import requests
  from matplotlib.pyplot import ylabel
  
  
  
  
  
  
  
  
  class ParallelCoordinates(object):
      pass
  
      def getIrisData(self):
          pass
          url = "/Users/halil/Yandex.Disk.localized/root/academic/myphd/phd/0091-mypapers/uv-in-pc/data/pc-data-sample.csv"
          data=pandas.read_csv(url)
          list= data.values.T.tolist()
          return list
      
          
      def start(self):
          pass
          #self.pcForFewData()
          #self.scatterPlot()
  