如何在单元测试中使用pandas数据帧

Question

我正在开发一组python脚本来预处理数据集,然后使用scikit-learn生成一系列机器学习模型.我想开发一组单元测试来检查数据预处理函数,并希望能够使用一个小的测试pandas数据帧,我可以为其确定答案并在断言语句中使用它.

我似乎无法加载数据帧并使用self将其传递给单元测试.我的代码看起来像这样;

def setUp(self):
    TEST_INPUT_DIR = 'data/'
    test_file_name =  'testdata.csv'
    try:
        data = pd.read_csv(INPUT_DIR + test_file_name,
            sep = ',',
            header = 0)
    except IOError:
        print 'cannot open file'
    self.fixture = data

def tearDown(self):
    del self.fixture

def test1(self):    
    self.assertEqual(somefunction(self.fixture), somevalue)

if __name__ == '__main__':
    unittest.main()

谢谢您的帮助.

Answer 1

熊猫有一些测试工具.

import unittest
import pandas as pd
from pandas.util.testing import assert_frame_equal # <-- for testing dataframes

class DFTests(unittest.TestCase):

    """ class for running unittests """

    def setUp(self):
        """ Your setUp """
        TEST_INPUT_DIR = 'data/'
        test_file_name =  'testdata.csv'
        try:
            data = pd.read_csv(INPUT_DIR + test_file_name,
                sep = ',',
                header = 0)
        except IOError:
            print 'cannot open file'
        self.fixture = data

    def test_dataFrame_constructedAsExpected(self):
        """ Test that the dataframe read in equals what you expect"""
        foo = pd.DataFrame()
        assert_frame_equal(self.fixture, foo)

Answer 2

如果您使用最新的熊猫,我认为以下方式更清洁:

import pandas as pd

pd.testing.assert_frame_equal(my_df, expected_df)
pd.testing.assert_series_equal(my_series, expected_series)
pd.testing.assert_index_equal(my_index, expected_index)

AssertionError如果它们不是"相等",则每个函数都会引发.

有关更多信息和选项:https://pandas.pydata.org/pandas-docs/stable/reference/general_utility_functions.html#testing-functions