import random
dataSet = [[0], [1], [2], [3], [4], [5], [6], [7], [8], [9], [10]]
trainDataSet = random.sample(dataSet, 3)

import csv
import random
def getDataSet(proportion):
  """
    :exception
      獲取訓練集和測試集(將數(shù)據(jù)按比例隨機劃分)
    :parameter
      proportion - 測試集/數(shù)據(jù)集
    :return
      trainDataSet - 訓練集
      testDataSet - 測試集
    author
      肖政宇
    modify
      2019年5月10日
  """
  dataSet = open('數(shù)據(jù)集.csv')
  dataSetReader = csv.reader(dataSet)
  """
    :exception
      將數(shù)據(jù)保存到數(shù)組
  """
  dataSet = []
  next(dataSetReader, 'none') # 跳過表頭
  data = next(dataSetReader, 'none')
  while (data != 'none'):
    dataSet.append(data)
    data = next(dataSetReader, 'none')
  """
    :exception
      按照比例隨機劃分出訓練集和測試集
  """
  dataNumber = dataSet.__len__() # 數(shù)據(jù)集數(shù)據(jù)條數(shù)
  testNumber = int(dataNumber * proportion) # 測試集數(shù)據(jù)條數(shù)
  testDataSet = [] # 測試數(shù)據(jù)集
  trainDataSet = [] # 訓練數(shù)據(jù)集
 
  testDataSet = random.sample(dataSet, testNumber) # 測試集
  for testData in testDataSet: # 將已經選定的測試集數(shù)據(jù)從數(shù)據(jù)集中刪除
    dataSet.remove(testData)
  trainDataSet = dataSet # 訓練集
 
  return trainDataSet, testDataSet