f2f419b89221602dc31c69de32df1cba281db481,upsetplot/tests/test_data.py,,test_from_contents,#,90

Before Change


@pytest.mark.parametrize("typ", [set, list, tuple, iter])
@pytest.mark.parametrize("id_column", ["id", "blah"])
def test_from_contents(typ, id_column):
    contents = {"cat1": typ(["aa", "bb", "cc"]),
                "cat2": typ(["cc", "dd"]),
                "cat3": typ(["ee"]),
                }
    empty_data = pd.DataFrame(index=["aa", "bb", "cc", "dd", "ee", "ff"])
    out = from_contents(OrderedDict(contents), data=empty_data,
                        id_column=id_column)
    out2 = from_memberships(memberships=[{"cat1"},

After Change




def test_from_contents(typ=set, id_column="id"):
    contents = {"cat1": {"aa", "bb", "cc"},
                "cat2": {"cc", "dd"},
                "cat3": {"ee"},
                }
    empty_data = pd.DataFrame(index=["aa", "bb", "cc", "dd", "ee"])
    baseline = from_contents(OrderedDict(contents), data=empty_data,
                             id_column=id_column)
    // data=None
    out = from_contents(OrderedDict(contents), id_column=id_column)
    assert_frame_equal(out.sort_values(id_column), baseline)

    // unordered contents dict
    out = from_contents({"cat3": contents["cat3"],
                         "cat2": contents["cat2"],
                         "cat1": contents["cat1"]},
                        data=empty_data, id_column=id_column)
    assert_frame_equal(out.reorder_levels(["cat1", "cat2", "cat3"]),
                       baseline)

    // empty category
    out = from_contents({"cat1": contents["cat1"],
                         "cat2": contents["cat2"],
                         "cat3": contents["cat3"],
                         "cat4": []},
                        data=empty_data,
                        id_column=id_column)
    assert not out.index.to_frame()["cat4"].any()  // cat4 should be all-false
    assert len(out.index.names) == 4
    out.index = out.index.to_frame().set_index(["cat1", "cat2", "cat3"]).index
    assert_frame_equal(out, baseline)
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 8

Instances


Project Name: jnothman/UpSetPlot
Commit Name: f2f419b89221602dc31c69de32df1cba281db481
Time: 2019-05-30
Author: joel.nothman@gmail.com
File Name: upsetplot/tests/test_data.py
Class Name:
Method Name: test_from_contents


Project Name: nilmtk/nilmtk
Commit Name: 571ac6df8cbd237abf09b85da7c99e2fad3ed280
Time: 2014-01-09
Author: jack-list@xlk.org.uk
File Name: nilmtk/dataset/dataset.py
Class Name: DataSet
Method Name: describe


Project Name: GoogleCloudPlatform/python-docs-samples
Commit Name: 63ea9b2637ce8e478c854b68d8af7ca42e19abcf
Time: 2020-09-22
Author: 35782177+melaniedejong@users.noreply.github.com
File Name: iam/api-client/quickstart.py
Class Name:
Method Name: quickstart