如何在单元测试中使用 Pandas 数据框

Question

I am developing a set of python scripts to pre-process a dataset then produce a series of machine learning models using scikit-learn. I would like to develop a set of unittests to check the data pre-processing functions, and would like to be able to use a small test pandas dataframe for which I can determine the answers for and use it in assert statements.

I cannot seem to get it to load the dataframe and to pass it to the unit tests using self. My code looks something like this;

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()

Thanks for the help.

Answer 1

Pandas has some utilities for testing.

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

If you are using latest pandas, I think the following way is a bit cleaner:

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)

Each of these functions will raise AssertionError if they are not "equal".

For more information and options: https://pandas.pydata.org/pandas-docs/stable/reference/general_utility_functions.html#testing-functions

Answer 3

You could do something like this as well with snapshottest .

https://stackoverflow.com/a/64070787/3384609