test_readers.py

from collections import OrderedDict
import contextlib
from datetime import datetime, time
from functools import partial
import os
from urllib.error import URLError
import warnings

import numpy as np
import pytest

import pandas.util._test_decorators as td

import pandas as pd
from pandas import DataFrame, Index, MultiIndex, Series
import pandas.util.testing as tm


@contextlib.contextmanager
def ignore_xlrd_time_clock_warning():
    """
    Context manager to ignore warnings raised by the xlrd library,
    regarding the deprecation of `time.clock` in Python 3.7.
    """
    with warnings.catch_warnings():
        warnings.filterwarnings(
            action="ignore",
            message="time.clock has been deprecated",
            category=DeprecationWarning,
        )
        yield


@pytest.fixture(
    params=[
        # Add any engines to test here
        # When defusedxml is installed it triggers deprecation warnings for
        # xlrd and openpyxl, so catch those here
        pytest.param(
            "xlrd",
            marks=[
                td.skip_if_no("xlrd"),
                pytest.mark.filterwarnings("ignore:.*(tree\\.iter|html argument)"),
            ],
        ),
        pytest.param(
            "openpyxl",
            marks=[
                td.skip_if_no("openpyxl"),
                pytest.mark.filterwarnings("ignore:.*html argument"),
            ],
        ),
        pytest.param("odf", marks=td.skip_if_no("odf")),
    ]
)
def engine(request):
    """
    A fixture for Excel reader engines.
    """
    return request.param


@pytest.mark.parametrize("kwargs", [dict(), dict(engine=None)])
def test_default_engine(datapath, monkeypatch, kwargs):
    """
    A test for default ExcelFile engine value (which is None)
    """
    monkeypatch.chdir(datapath("io", "data"))
    expected = "xlrd"

    result = pd.ExcelFile("blank.xls", **kwargs)
    assert result.engine == expected


def test_bad_engine_raises():
    bad_engine = "foo"
    with pytest.raises(ValueError, match="Unknown engine: foo"):
        pd.read_excel("", engine=bad_engine)


class TestReaders:
    @pytest.fixture(autouse=True)
    def cd_and_set_engine(self, engine, datapath, monkeypatch, read_ext):
        """
        Change directory and set engine for read_excel calls.
        """
        if engine == "openpyxl" and read_ext == ".xls":
            pytest.skip()
        if engine == "odf" and read_ext != ".ods":
            pytest.skip()
        if read_ext == ".ods" and engine != "odf":
            pytest.skip()

        func = partial(pd.read_excel, engine=engine)
        monkeypatch.chdir(datapath("io", "data"))
        monkeypatch.setattr(pd, "read_excel", func)

    def test_usecols_int(self, read_ext, df_ref):
        df_ref = df_ref.reindex(columns=["A", "B", "C"])

        # usecols as int
        with tm.assert_produces_warning(
            FutureWarning, check_stacklevel=False, raise_on_extra_warnings=False
        ):
            with ignore_xlrd_time_clock_warning():
                df1 = pd.read_excel(
                    "test1" + read_ext, "Sheet1", index_col=0, usecols=3
                )

        # usecols as int
        with tm.assert_produces_warning(
            FutureWarning, check_stacklevel=False, raise_on_extra_warnings=False
        ):
            with ignore_xlrd_time_clock_warning():
                df2 = pd.read_excel(
                    "test1" + read_ext, "Sheet2", skiprows=[1], index_col=0, usecols=3
                )

        # TODO add index to xls file)
        tm.assert_frame_equal(df1, df_ref, check_names=False)
        tm.assert_frame_equal(df2, df_ref, check_names=False)

    def test_usecols_list(self, read_ext, df_ref):

        df_ref = df_ref.reindex(columns=["B", "C"])
        df1 = pd.read_excel(
            "test1" + read_ext, "Sheet1", index_col=0, usecols=[0, 2, 3]
        )
        df2 = pd.read_excel(
            "test1" + read_ext, "Sheet2", skiprows=[1], index_col=0, usecols=[0, 2, 3]
        )

        # TODO add index to xls file)
        tm.assert_frame_equal(df1, df_ref, check_names=False)
        tm.assert_frame_equal(df2, df_ref, check_names=False)

    def test_usecols_str(self, read_ext, df_ref):

        df1 = df_ref.reindex(columns=["A", "B", "C"])
        df2 = pd.read_excel("test1" + read_ext, "Sheet1", index_col=0, usecols="A:D")
        df3 = pd.read_excel(
            "test1" + read_ext, "Sheet2", skiprows=[1], index_col=0, usecols="A:D"
        )

        # TODO add index to xls, read xls ignores index name ?
        tm.assert_frame_equal(df2, df1, check_names=False)
        tm.assert_frame_equal(df3, df1, check_names=False)

        df1 = df_ref.reindex(columns=["B", "C"])
        df2 = pd.read_excel("test1" + read_ext, "Sheet1", index_col=0, usecols="A,C,D")
        df3 = pd.read_excel(
            "test1" + read_ext, "Sheet2", skiprows=[1], index_col=0, usecols="A,C,D"
        )
        # TODO add index to xls file
        tm.assert_frame_equal(df2, df1, check_names=False)
        tm.assert_frame_equal(df3, df1, check_names=False)

        df1 = df_ref.reindex(columns=["B", "C"])
        df2 = pd.read_excel("test1" + read_ext, "Sheet1", index_col=0, usecols="A,C:D")
        df3 = pd.read_excel(
            "test1" + read_ext, "Sheet2", skiprows=[1], index_col=0, usecols="A,C:D"
        )
        tm.assert_frame_equal(df2, df1, check_names=False)
        tm.assert_frame_equal(df3, df1, check_names=False)

    @pytest.mark.parametrize(
        "usecols", [[0, 1, 3], [0, 3, 1], [1, 0, 3], [1, 3, 0], [3, 0, 1], [3, 1, 0]]
    )
    def test_usecols_diff_positional_int_columns_order(self, read_ext, usecols, df_ref):
        expected = df_ref[["A", "C"]]
        result = pd.read_excel(
            "test1" + read_ext, "Sheet1", index_col=0, usecols=usecols
        )
        tm.assert_frame_equal(result, expected, check_names=False)

    @pytest.mark.parametrize("usecols", [["B", "D"], ["D", "B"]])
    def test_usecols_diff_positional_str_columns_order(self, read_ext, usecols, df_ref):
        expected = df_ref[["B", "D"]]
        expected.index = range(len(expected))

        result = pd.read_excel("test1" + read_ext, "Sheet1", usecols=usecols)
        tm.assert_frame_equal(result, expected, check_names=False)

    def test_read_excel_without_slicing(self, read_ext, df_ref):
        expected = df_ref
        result = pd.read_excel("test1" + read_ext, "Sheet1", index_col=0)
        tm.assert_frame_equal(result, expected, check_names=False)

    def test_usecols_excel_range_str(self, read_ext, df_ref):
        expected = df_ref[["C", "D"]]
        result = pd.read_excel(
            "test1" + read_ext, "Sheet1", index_col=0, usecols="A,D:E"
        )
        tm.assert_frame_equal(result, expected, check_names=False)

    def test_usecols_excel_range_str_invalid(self, read_ext):
        msg = "Invalid column name: E1"

        with pytest.raises(ValueError, match=msg):
            pd.read_excel("test1" + read_ext, "Sheet1", usecols="D:E1")

    def test_index_col_label_error(self, read_ext):
        msg = "list indices must be integers.*, not str"

        with pytest.raises(TypeError, match=msg):
            pd.read_excel(
                "test1" + read_ext, "Sheet1", index_col=["A"], usecols=["A", "C"]
            )

    def test_index_col_empty(self, read_ext):
        # see gh-9208
        result = pd.read_excel("test1" + read_ext, "Sheet3", index_col=["A", "B", "C"])
        expected = DataFrame(
            columns=["D", "E", "F"],
            index=MultiIndex(levels=[[]] * 3, codes=[[]] * 3, names=["A", "B", "C"]),
        )
        tm.assert_frame_equal(result, expected)

    @pytest.mark.parametrize("index_col", [None, 2])
    def test_index_col_with_unnamed(self, read_ext, index_col):
        # see gh-18792
        result = pd.read_excel("test1" + read_ext, "Sheet4", index_col=index_col)
        expected = DataFrame(
            [["i1", "a", "x"], ["i2", "b", "y"]], columns=["Unnamed: 0", "col1", "col2"]
        )
        if index_col:
            expected = expected.set_index(expected.columns[index_col])

        tm.assert_frame_equal(result, expected)

    def test_usecols_pass_non_existent_column(self, read_ext):
        msg = (
            "Usecols do not match columns, "
            "columns expected but not found: " + r"\['E'\]"
        )

        with pytest.raises(ValueError, match=msg):
            pd.read_excel("test1" + read_ext, usecols=["E"])

    def test_usecols_wrong_type(self, read_ext):
        msg = (
            "'usecols' must either be list-like of "
            "all strings, all unicode, all integers or a callable."
        )

        with pytest.raises(ValueError, match=msg):
            pd.read_excel("test1" + read_ext, usecols=["E1", 0])

    def test_excel_stop_iterator(self, read_ext):

        parsed = pd.read_excel("test2" + read_ext, "Sheet1")
        expected = DataFrame([["aaaa", "bbbbb"]], columns=["Test", "Test1"])
        tm.assert_frame_equal(parsed, expected)

    def test_excel_cell_error_na(self, read_ext):

        parsed = pd.read_excel("test3" + read_ext, "Sheet1")
        expected = DataFrame([[np.nan]], columns=["Test"])
        tm.assert_frame_equal(parsed, expected)

    def test_excel_table(self, read_ext, df_ref):

        df1 = pd.read_excel("test1" + read_ext, "Sheet1", index_col=0)
        df2 = pd.read_excel("test1" + read_ext, "Sheet2", skiprows=[1], index_col=0)
        # TODO add index to file
        tm.assert_frame_equal(df1, df_ref, check_names=False)
        tm.assert_frame_equal(df2, df_ref, check_names=False)

        df3 = pd.read_excel("test1" + read_ext, "Sheet1", index_col=0, skipfooter=1)
        tm.assert_frame_equal(df3, df1.iloc[:-1])

    def test_reader_special_dtypes(self, read_ext):

        expected = DataFrame.from_dict(
            OrderedDict(
                [
                    ("IntCol", [1, 2, -3, 4, 0]),
                    ("FloatCol", [1.25, 2.25, 1.83, 1.92, 0.0000000005]),
                    ("BoolCol", [True, False, True, True, False]),
                    ("StrCol", [1, 2, 3, 4, 5]),
                    # GH5394 - this is why convert_float isn't vectorized
                    ("Str2Col", ["a", 3, "c", "d", "e"]),
                    (
                        "DateCol",
                        [
                            datetime(2013, 10, 30),
                            datetime(2013, 10, 31),
                            datetime(1905, 1, 1),
                            datetime(2013, 12, 14),
                            datetime(2015, 3, 14),
                        ],
                    ),
                ]
            )
        )
        basename = "test_types"

        # should read in correctly and infer types
        actual = pd.read_excel(basename + read_ext, "Sheet1")
        tm.assert_frame_equal(actual, expected)

        # if not coercing number, then int comes in as float
        float_expected = expected.copy()
        float_expected["IntCol"] = float_expected["IntCol"].astype(float)
        float_expected.loc[float_expected.index[1], "Str2Col"] = 3.0
        actual = pd.read_excel(basename + read_ext, "Sheet1", convert_float=False)
        tm.assert_frame_equal(actual, float_expected)

        # check setting Index (assuming xls and xlsx are the same here)
        for icol, name in enumerate(expected.columns):
            actual = pd.read_excel(basename + read_ext, "Sheet1", index_col=icol)
            exp = expected.set_index(name)
            tm.assert_frame_equal(actual, exp)

        # convert_float and converters should be different but both accepted
        expected["StrCol"] = expected["StrCol"].apply(str)
        actual = pd.read_excel(
            basename + read_ext, "Sheet1", converters={"StrCol": str}
        )
        tm.assert_frame_equal(actual, expected)

        no_convert_float = float_expected.copy()
        no_convert_float["StrCol"] = no_convert_float["StrCol"].apply(str)
        actual = pd.read_excel(
            basename + read_ext,
            "Sheet1",
            convert_float=False,
            converters={"StrCol": str},
        )
        tm.assert_frame_equal(actual, no_convert_float)

    # GH8212 - support for converters and missing values
    def test_reader_converters(self, read_ext):

        basename = "test_converters"

        expected = DataFrame.from_dict(
            OrderedDict(
                [
                    ("IntCol", [1, 2, -3, -1000, 0]),
                    ("FloatCol", [12.5, np.nan, 18.3, 19.2, 0.000000005]),
                    ("BoolCol", ["Found", "Found", "Found", "Not found", "Found"]),
                    ("StrCol", ["1", np.nan, "3", "4", "5"]),
                ]
            )
        )

        converters = {
            "IntCol": lambda x: int(x) if x != "" else -1000,
            "FloatCol": lambda x: 10 * x if x else np.nan,
            2: lambda x: "Found" if x != "" else "Not found",
            3: lambda x: str(x) if x else "",
        }

        # should read in correctly and set types of single cells (not array
        # dtypes)
        actual = pd.read_excel(basename + read_ext, "Sheet1", converters=converters)
        tm.assert_frame_equal(actual, expected)

    def test_reader_dtype(self, read_ext):
        # GH 8212
        basename = "testdtype"
        actual = pd.read_excel(basename + read_ext)

        expected = DataFrame(
            {
                "a": [1, 2, 3, 4],
                "b": [2.5, 3.5, 4.5, 5.5],
                "c": [1, 2, 3, 4],
                "d": [1.0, 2.0, np.nan, 4.0],
            }
        ).reindex(columns=["a", "b", "c", "d"])

        tm.assert_frame_equal(actual, expected)

        actual = pd.read_excel(
            basename + read_ext, dtype={"a": "float64", "b": "float32", "c": str}
        )

        expected["a"] = expected["a"].astype("float64")
        expected["b"] = expected["b"].astype("float32")
        expected["c"] = ["001", "002", "003", "004"]
        tm.assert_frame_equal(actual, expected)

        with pytest.raises(ValueError):
            pd.read_excel(basename + read_ext, dtype={"d": "int64"})

    @pytest.mark.parametrize(
        "dtype,expected",
        [
            (
                None,
                DataFrame(
                    {
                        "a": [1, 2, 3, 4],
                        "b": [2.5, 3.5, 4.5, 5.5],
                        "c": [1, 2, 3, 4],
                        "d": [1.0, 2.0, np.nan, 4.0],
                    }
                ),
            ),
            (
                {"a": "float64", "b": "float32", "c": str, "d": str},
                DataFrame(
                    {
                        "a": Series([1, 2, 3, 4], dtype="float64"),
                        "b": Series([2.5, 3.5, 4.5, 5.5], dtype="float32"),
                        "c": ["001", "002", "003", "004"],
                        "d": ["1", "2", np.nan, "4"],
                    }
                ),
            ),
        ],
    )
    def test_reader_dtype_str(self, read_ext, dtype, expected):
        # see gh-20377
        basename = "testdtype"

        actual = pd.read_excel(basename + read_ext, dtype=dtype)
        tm.assert_frame_equal(actual, expected)

    def test_reading_all_sheets(self, read_ext):
        # Test reading all sheetnames by setting sheetname to None,
        # Ensure a dict is returned.
        # See PR #9450
        basename = "test_multisheet"
        dfs = pd.read_excel(basename + read_ext, sheet_name=None)
        # ensure this is not alphabetical to test order preservation
        expected_keys = ["Charlie", "Alpha", "Beta"]
        tm.assert_contains_all(expected_keys, dfs.keys())
        # Issue 9930
        # Ensure sheet order is preserved
        assert expected_keys == list(dfs.keys())

    def test_reading_multiple_specific_sheets(self, read_ext):
        # Test reading specific sheetnames by specifying a mixed list
        # of integers and strings, and confirm that duplicated sheet
        # references (positions/names) are removed properly.
        # Ensure a dict is returned
        # See PR #9450
        basename = "test_multisheet"
        # Explicitly request duplicates. Only the set should be returned.
        expected_keys = [2, "Charlie", "Charlie"]
        dfs = pd.read_excel(basename + read_ext, sheet_name=expected_keys)
        expected_keys = list(set(expected_keys))
        tm.assert_contains_all(expected_keys, dfs.keys())
        assert len(expected_keys) == len(dfs.keys())

    def test_reading_all_sheets_with_blank(self, read_ext):
        # Test reading all sheetnames by setting sheetname to None,
        # In the case where some sheets are blank.
        # Issue #11711
        basename = "blank_with_header"
        dfs = pd.read_excel(basename + read_ext, sheet_name=None)
        expected_keys = ["Sheet1", "Sheet2", "Sheet3"]
        tm.assert_contains_all(expected_keys, dfs.keys())

    # GH6403
    def test_read_excel_blank(self, read_ext):
        actual = pd.read_excel("blank" + read_ext, "Sheet1")
        tm.assert_frame_equal(actual, DataFrame())

    def test_read_excel_blank_with_header(self, read_ext):
        expected = DataFrame(columns=["col_1", "col_2"])
        actual = pd.read_excel("blank_with_header" + read_ext, "Sheet1")
        tm.assert_frame_equal(actual, expected)

    def test_date_conversion_overflow(self, read_ext):
        # GH 10001 : pandas.ExcelFile ignore parse_dates=False
        expected = pd.DataFrame(
            [
                [pd.Timestamp("2016-03-12"), "Marc Johnson"],
                [pd.Timestamp("2016-03-16"), "Jack Black"],
                [1e20, "Timothy Brown"],
            ],
            columns=["DateColWithBigInt", "StringCol"],
        )

        if pd.read_excel.keywords["engine"] == "openpyxl":
            pytest.xfail("Maybe not supported by openpyxl")

        result = pd.read_excel("testdateoverflow" + read_ext)
        tm.assert_frame_equal(result, expected)

    def test_sheet_name(self, read_ext, df_ref):
        filename = "test1"
        sheet_name = "Sheet1"

        df1 = pd.read_excel(
            filename + read_ext, sheet_name=sheet_name, index_col=0
        )  # doc
        with ignore_xlrd_time_clock_warning():
            df2 = pd.read_excel(filename + read_ext, index_col=0, sheet_name=sheet_name)

        tm.assert_frame_equal(df1, df_ref, check_names=False)
        tm.assert_frame_equal(df2, df_ref, check_names=False)

    def test_excel_read_buffer(self, read_ext):

        pth = "test1" + read_ext
        expected = pd.read_excel(pth, "Sheet1", index_col=0)
        with open(pth, "rb") as f:
            actual = pd.read_excel(f, "Sheet1", index_col=0)
            tm.assert_frame_equal(expected, actual)

    @tm.network
    def test_read_from_http_url(self, read_ext):
        if read_ext == ".ods":  # TODO: remove once on master
            pytest.skip()

        url = (
            "https://raw.github.com/pandas-dev/pandas/master/"
            "pandas/tests/io/data/test1" + read_ext
        )
        url_table = pd.read_excel(url)
        local_table = pd.read_excel("test1" + read_ext)
        tm.assert_frame_equal(url_table, local_table)

    @td.skip_if_not_us_locale
    def test_read_from_s3_url(self, read_ext, s3_resource):
        # Bucket "pandas-test" created in tests/io/conftest.py
        with open("test1" + read_ext, "rb") as f:
            s3_resource.Bucket("pandas-test").put_object(Key="test1" + read_ext, Body=f)

        url = "s3://pandas-test/test1" + read_ext
        url_table = pd.read_excel(url)
        local_table = pd.read_excel("test1" + read_ext)
        tm.assert_frame_equal(url_table, local_table)

    @pytest.mark.slow
    # ignore warning from old xlrd
    @pytest.mark.filterwarnings("ignore:This metho:PendingDeprecationWarning")
    def test_read_from_file_url(self, read_ext, datapath):

        # FILE
        localtable = os.path.join(datapath("io", "data"), "test1" + read_ext)
        local_table = pd.read_excel(localtable)

        try:
            url_table = pd.read_excel("file://localhost/" + localtable)
        except URLError:
            # fails on some systems
            import platform

            pytest.skip("failing on {}".format(" ".join(platform.uname()).strip()))

        tm.assert_frame_equal(url_table, local_table)

    def test_read_from_pathlib_path(self, read_ext):

        # GH12655
        from pathlib import Path

        str_path = "test1" + read_ext
        expected = pd.read_excel(str_path, "Sheet1", index_col=0)

        path_obj = Path("test1" + read_ext)
        actual = pd.read_excel(path_obj, "Sheet1", index_col=0)

        tm.assert_frame_equal(expected, actual)

    @td.skip_if_no("py.path")
    def test_read_from_py_localpath(self, read_ext):

        # GH12655
        from py.path import local as LocalPath

        str_path = os.path.join("test1" + read_ext)
        expected = pd.read_excel(str_path, "Sheet1", index_col=0)

        path_obj = LocalPath().join("test1" + read_ext)
        actual = pd.read_excel(path_obj, "Sheet1", index_col=0)

        tm.assert_frame_equal(expected, actual)

    def test_reader_seconds(self, read_ext):

        # Test reading times with and without milliseconds. GH5945.
        expected = DataFrame.from_dict(
            {
                "Time": [
                    time(1, 2, 3),
                    time(2, 45, 56, 100000),
                    time(4, 29, 49, 200000),
                    time(6, 13, 42, 300000),
                    time(7, 57, 35, 400000),
                    time(9, 41, 28, 500000),
                    time(11, 25, 21, 600000),
                    time(13, 9, 14, 700000),
                    time(14, 53, 7, 800000),
                    time(16, 37, 0, 900000),
                    time(18, 20, 54),
                ]
            }
        )

        actual = pd.read_excel("times_1900" + read_ext, "Sheet1")
        tm.assert_frame_equal(actual, expected)

        actual = pd.read_excel("times_1904" + read_ext, "Sheet1")
        tm.assert_frame_equal(actual, expected)

    def test_read_excel_multiindex(self, read_ext):
        # see gh-4679
        mi = MultiIndex.from_product([["foo", "bar"], ["a", "b"]])
        mi_file = "testmultiindex" + read_ext

        # "mi_column" sheet
        expected = DataFrame(
            [
                [1, 2.5, pd.Timestamp("2015-01-01"), True],
                [2, 3.5, pd.Timestamp("2015-01-02"), False],
                [3, 4.5, pd.Timestamp("2015-01-03"), False],
                [4, 5.5, pd.Timestamp("2015-01-04"), True],
            ],
            columns=mi,
        )

        actual = pd.read_excel(mi_file, "mi_column", header=[0, 1], index_col=0)
        tm.assert_frame_equal(actual, expected)

        # "mi_index" sheet
        expected.index = mi
        expected.columns = ["a", "b", "c", "d"]

        actual = pd.read_excel(mi_file, "mi_index", index_col=[0, 1])
        tm.assert_frame_equal(actual, expected, check_names=False)

        # "both" sheet
        expected.columns = mi

        actual = pd.read_excel(mi_file, "both", index_col=[0, 1], header=[0, 1])
        tm.assert_frame_equal(actual, expected, check_names=False)

        # "mi_index_name" sheet
        expected.columns = ["a", "b", "c", "d"]
        expected.index = mi.set_names(["ilvl1", "ilvl2"])

        actual = pd.read_excel(mi_file, "mi_index_name", index_col=[0, 1])
        tm.assert_frame_equal(actual, expected)

        # "mi_column_name" sheet
        expected.index = list(range(4))
        expected.columns = mi.set_names(["c1", "c2"])
        actual = pd.read_excel(mi_file, "mi_column_name", header=[0, 1], index_col=0)
        tm.assert_frame_equal(actual, expected)

        # see gh-11317
        # "name_with_int" sheet
        expected.columns = mi.set_levels([1, 2], level=1).set_names(["c1", "c2"])

        actual = pd.read_excel(mi_file, "name_with_int", index_col=0, header=[0, 1])
        tm.assert_frame_equal(actual, expected)

        # "both_name" sheet
        expected.columns = mi.set_names(["c1", "c2"])
        expected.index = mi.set_names(["ilvl1", "ilvl2"])

        actual = pd.read_excel(mi_file, "both_name", index_col=[0, 1], header=[0, 1])
        tm.assert_frame_equal(actual, expected)

        # "both_skiprows" sheet
        actual = pd.read_excel(
            mi_file, "both_name_skiprows", index_col=[0, 1], header=[0, 1], skiprows=2
        )
        tm.assert_frame_equal(actual, expected)

    def test_read_excel_multiindex_header_only(self, read_ext):
        # see gh-11733.
        #
        # Don't try to parse a header name if there isn't one.
        mi_file = "testmultiindex" + read_ext
        result = pd.read_excel(mi_file, "index_col_none", header=[0, 1])

        exp_columns = MultiIndex.from_product([("A", "B"), ("key", "val")])
        expected = DataFrame([[1, 2, 3, 4]] * 2, columns=exp_columns)
        tm.assert_frame_equal(result, expected)

    def test_excel_old_index_format(self, read_ext):
        # see gh-4679
        filename = "test_index_name_pre17" + read_ext

        # We detect headers to determine if index names exist, so
        # that "index" name in the "names" version of the data will
        # now be interpreted as rows that include null data.
        data = np.array(
            [
                [None, None, None, None, None],
                ["R0C0", "R0C1", "R0C2", "R0C3", "R0C4"],
                ["R1C0", "R1C1", "R1C2", "R1C3", "R1C4"],
                ["R2C0", "R2C1", "R2C2", "R2C3", "R2C4"],
                ["R3C0", "R3C1", "R3C2", "R3C3", "R3C4"],
                ["R4C0", "R4C1", "R4C2", "R4C3", "R4C4"],
            ]
        )
        columns = ["C_l0_g0", "C_l0_g1", "C_l0_g2", "C_l0_g3", "C_l0_g4"]
        mi = MultiIndex(
            levels=[
                ["R0", "R_l0_g0", "R_l0_g1", "R_l0_g2", "R_l0_g3", "R_l0_g4"],
                ["R1", "R_l1_g0", "R_l1_g1", "R_l1_g2", "R_l1_g3", "R_l1_g4"],
            ],
            codes=[[0, 1, 2, 3, 4, 5], [0, 1, 2, 3, 4, 5]],
            names=[None, None],
        )
        si = Index(
            ["R0", "R_l0_g0", "R_l0_g1", "R_l0_g2", "R_l0_g3", "R_l0_g4"], name=None
        )

        expected = pd.DataFrame(data, index=si, columns=columns)

        actual = pd.read_excel(filename, "single_names", index_col=0)
        tm.assert_frame_equal(actual, expected)

        expected.index = mi

        actual = pd.read_excel(filename, "multi_names", index_col=[0, 1])
        tm.assert_frame_equal(actual, expected)

        # The analogous versions of the "names" version data
        # where there are explicitly no names for the indices.
        data = np.array(
            [
                ["R0C0", "R0C1", "R0C2", "R0C3", "R0C4"],
                ["R1C0", "R1C1", "R1C2", "R1C3", "R1C4"],
                ["R2C0", "R2C1", "R2C2", "R2C3", "R2C4"],
                ["R3C0", "R3C1", "R3C2", "R3C3", "R3C4"],
                ["R4C0", "R4C1", "R4C2", "R4C3", "R4C4"],
            ]
        )
        columns = ["C_l0_g0", "C_l0_g1", "C_l0_g2", "C_l0_g3", "C_l0_g4"]
        mi = MultiIndex(
            levels=[
                ["R_l0_g0", "R_l0_g1", "R_l0_g2", "R_l0_g3", "R_l0_g4"],
                ["R_l1_g0", "R_l1_g1", "R_l1_g2", "R_l1_g3", "R_l1_g4"],
            ],
            codes=[[0, 1, 2, 3, 4], [0, 1, 2, 3, 4]],
            names=[None, None],
        )
        si = Index(["R_l0_g0", "R_l0_g1", "R_l0_g2", "R_l0_g3", "R_l0_g4"], name=None)

        expected = pd.DataFrame(data, index=si, columns=columns)

        actual = pd.read_excel(filename, "single_no_names", index_col=0)
        tm.assert_frame_equal(actual, expected)

        expected.index = mi

        actual = pd.read_excel(filename, "multi_no_names", index_col=[0, 1])
        tm.assert_frame_equal(actual, expected, check_names=False)

    def test_read_excel_bool_header_arg(self, read_ext):
        # GH 6114
        for arg in [True, False]:
            with pytest.raises(TypeError):
                pd.read_excel("test1" + read_ext, header=arg)

    def test_read_excel_chunksize(self, read_ext):
        # GH 8011
        with pytest.raises(NotImplementedError):
            pd.read_excel("test1" + read_ext, chunksize=100)

    def test_read_excel_skiprows_list(self, read_ext):
        # GH 4903
        actual = pd.read_excel(
            "testskiprows" + read_ext, "skiprows_list", skiprows=[0, 2]
        )
        expected = DataFrame(
            [
                [1, 2.5, pd.Timestamp("2015-01-01"), True],
                [2, 3.5, pd.Timestamp("2015-01-02"), False],
                [3, 4.5, pd.Timestamp("2015-01-03"), False],
                [4, 5.5, pd.Timestamp("2015-01-04"), True],
            ],
            columns=["a", "b", "c", "d"],
        )
        tm.assert_frame_equal(actual, expected)

        actual = pd.read_excel(
            "testskiprows" + read_ext, "skiprows_list", skiprows=np.array([0, 2])
        )
        tm.assert_frame_equal(actual, expected)

    def test_read_excel_nrows(self, read_ext):
        # GH 16645
        num_rows_to_pull = 5
        actual = pd.read_excel("test1" + read_ext, nrows=num_rows_to_pull)
        expected = pd.read_excel("test1" + read_ext)
        expected = expected[:num_rows_to_pull]
        tm.assert_frame_equal(actual, expected)

    def test_read_excel_nrows_greater_than_nrows_in_file(self, read_ext):
        # GH 16645
        expected = pd.read_excel("test1" + read_ext)
        num_records_in_file = len(expected)
        num_rows_to_pull = num_records_in_file + 10
        actual = pd.read_excel("test1" + read_ext, nrows=num_rows_to_pull)
        tm.assert_frame_equal(actual, expected)

    def test_read_excel_nrows_non_integer_parameter(self, read_ext):
        # GH 16645
        msg = "'nrows' must be an integer >=0"
        with pytest.raises(ValueError, match=msg):
            pd.read_excel("test1" + read_ext, nrows="5")

    def test_read_excel_squeeze(self, read_ext):
        # GH 12157
        f = "test_squeeze" + read_ext

        actual = pd.read_excel(f, "two_columns", index_col=0, squeeze=True)
        expected = pd.Series([2, 3, 4], [4, 5, 6], name="b")
        expected.index.name = "a"
        tm.assert_series_equal(actual, expected)

        actual = pd.read_excel(f, "two_columns", squeeze=True)
        expected = pd.DataFrame({"a": [4, 5, 6], "b": [2, 3, 4]})
        tm.assert_frame_equal(actual, expected)

        actual = pd.read_excel(f, "one_column", squeeze=True)
        expected = pd.Series([1, 2, 3], name="a")
        tm.assert_series_equal(actual, expected)


class TestExcelFileRead:
    @pytest.fixture(autouse=True)
    def cd_and_set_engine(self, engine, datapath, monkeypatch, read_ext):
        """
        Change directory and set engine for ExcelFile objects.
        """
        if engine == "odf" and read_ext != ".ods":
            pytest.skip()
        if read_ext == ".ods" and engine != "odf":
            pytest.skip()
        if engine == "openpyxl" and read_ext == ".xls":
            pytest.skip()

        func = partial(pd.ExcelFile, engine=engine)
        monkeypatch.chdir(datapath("io", "data"))
        monkeypatch.setattr(pd, "ExcelFile", func)

    def test_excel_passes_na(self, read_ext):

        with pd.ExcelFile("test4" + read_ext) as excel:
            parsed = pd.read_excel(
                excel, "Sheet1", keep_default_na=False, na_values=["apple"]
            )
        expected = DataFrame(
            [["NA"], [1], ["NA"], [np.nan], ["rabbit"]], columns=["Test"]
        )
        tm.assert_frame_equal(parsed, expected)

        with pd.ExcelFile("test4" + read_ext) as excel:
            parsed = pd.read_excel(
                excel, "Sheet1", keep_default_na=True, na_values=["apple"]
            )
        expected = DataFrame(
            [[np.nan], [1], [np.nan], [np.nan], ["rabbit"]], columns=["Test"]
        )
        tm.assert_frame_equal(parsed, expected)

        # 13967
        with pd.ExcelFile("test5" + read_ext) as excel:
            parsed = pd.read_excel(
                excel, "Sheet1", keep_default_na=False, na_values=["apple"]
            )
        expected = DataFrame(
            [["1.#QNAN"], [1], ["nan"], [np.nan], ["rabbit"]], columns=["Test"]
        )
        tm.assert_frame_equal(parsed, expected)

        with pd.ExcelFile("test5" + read_ext) as excel:
            parsed = pd.read_excel(
                excel, "Sheet1", keep_default_na=True, na_values=["apple"]
            )
        expected = DataFrame(
            [[np.nan], [1], [np.nan], [np.nan], ["rabbit"]], columns=["Test"]
        )
        tm.assert_frame_equal(parsed, expected)

    @pytest.mark.parametrize("arg", ["sheet", "sheetname", "parse_cols"])
    def test_unexpected_kwargs_raises(self, read_ext, arg):
        # gh-17964
        kwarg = {arg: "Sheet1"}
        msg = "unexpected keyword argument `{}`".format(arg)

        with pd.ExcelFile("test1" + read_ext) as excel:
            with pytest.raises(TypeError, match=msg):
                pd.read_excel(excel, **kwarg)

    def test_excel_table_sheet_by_index(self, read_ext, df_ref):

        with pd.ExcelFile("test1" + read_ext) as excel:
            df1 = pd.read_excel(excel, 0, index_col=0)
            df2 = pd.read_excel(excel, 1, skiprows=[1], index_col=0)
        tm.assert_frame_equal(df1, df_ref, check_names=False)
        tm.assert_frame_equal(df2, df_ref, check_names=False)

        with pd.ExcelFile("test1" + read_ext) as excel:
            df1 = excel.parse(0, index_col=0)
            df2 = excel.parse(1, skiprows=[1], index_col=0)
        tm.assert_frame_equal(df1, df_ref, check_names=False)
        tm.assert_frame_equal(df2, df_ref, check_names=False)

        with pd.ExcelFile("test1" + read_ext) as excel:
            df3 = pd.read_excel(excel, 0, index_col=0, skipfooter=1)
        tm.assert_frame_equal(df3, df1.iloc[:-1])

        with tm.assert_produces_warning(
            FutureWarning, check_stacklevel=False, raise_on_extra_warnings=False
        ):
            with pd.ExcelFile("test1" + read_ext) as excel:
                df4 = pd.read_excel(excel, 0, index_col=0, skip_footer=1)

            tm.assert_frame_equal(df3, df4)

        with pd.ExcelFile("test1" + read_ext) as excel:
            df3 = excel.parse(0, index_col=0, skipfooter=1)

        tm.assert_frame_equal(df3, df1.iloc[:-1])

    def test_sheet_name(self, read_ext, df_ref):
        filename = "test1"
        sheet_name = "Sheet1"

        with pd.ExcelFile(filename + read_ext) as excel:
            df1_parse = excel.parse(sheet_name=sheet_name, index_col=0)  # doc

        with pd.ExcelFile(filename + read_ext) as excel:
            df2_parse = excel.parse(index_col=0, sheet_name=sheet_name)

        tm.assert_frame_equal(df1_parse, df_ref, check_names=False)
        tm.assert_frame_equal(df2_parse, df_ref, check_names=False)

    def test_excel_read_buffer(self, engine, read_ext):
        pth = "test1" + read_ext
        expected = pd.read_excel(pth, "Sheet1", index_col=0, engine=engine)

        with open(pth, "rb") as f:
            with pd.ExcelFile(f) as xls:
                actual = pd.read_excel(xls, "Sheet1", index_col=0)

        tm.assert_frame_equal(expected, actual)

    def test_reader_closes_file(self, engine, read_ext):
        f = open("test1" + read_ext, "rb")
        with pd.ExcelFile(f) as xlsx:
            # parses okay
            pd.read_excel(xlsx, "Sheet1", index_col=0, engine=engine)

        assert f.closed

    def test_conflicting_excel_engines(self, read_ext):
        # GH 26566
        msg = "Engine should not be specified when passing an ExcelFile"

        with pd.ExcelFile("test1" + read_ext) as xl:
            with pytest.raises(ValueError, match=msg):
                pd.read_excel(xl, engine="foo")