Exemplo n.º 1
0
def test_decimal_roundtrip(tmpdir, precision):
    num_values = 10

    columns = {}

    for scale in range(0, precision + 1):
        with util.random_seed(0):
            random_decimal_values = [
                util.randdecimal(precision, scale) for _ in range(num_values)
            ]
        column_name = 'dec_precision_{:d}_scale_{:d}'.format(precision, scale)
        columns[column_name] = random_decimal_values

    expected = pd.DataFrame(columns)
    filename = tmpdir.join('decimals.parquet')
    string_filename = str(filename)
    t = pa.Table.from_pandas(expected)
    _write_table(t, string_filename)
    result_table = _read_table(string_filename)
    result = result_table.to_pandas()
    tm.assert_frame_equal(result, expected)
Exemplo n.º 2
0
def test_decimal_roundtrip(tempdir, use_legacy_dataset):
    num_values = 10

    columns = {}
    for precision in range(1, 39):
        for scale in range(0, precision + 1):
            with util.random_seed(0):
                random_decimal_values = [
                    util.randdecimal(precision, scale)
                    for _ in range(num_values)
                ]
            column_name = ('dec_precision_{:d}_scale_{:d}'.format(
                precision, scale))
            columns[column_name] = random_decimal_values

    expected = pd.DataFrame(columns)
    filename = tempdir / 'decimals.parquet'
    string_filename = str(filename)
    table = pa.Table.from_pandas(expected)
    _write_table(table, string_filename)
    result_table = _read_table(string_filename,
                               use_legacy_dataset=use_legacy_dataset)
    result = result_table.to_pandas()
    tm.assert_frame_equal(result, expected)
Exemplo n.º 3
0
def test_decimal_roundtrip(tmpdir):
    num_values = 10

    columns = {}

    for precision in range(1, 39):
        for scale in range(0, precision + 1):
            with util.random_seed(0):
                random_decimal_values = [
                    util.randdecimal(precision, scale)
                    for _ in range(num_values)
                ]
            column_name = ('dec_precision_{:d}_scale_{:d}'
                           .format(precision, scale))
            columns[column_name] = random_decimal_values

    expected = pd.DataFrame(columns)
    filename = tmpdir.join('decimals.parquet')
    string_filename = str(filename)
    t = pa.Table.from_pandas(expected)
    _write_table(t, string_filename)
    result_table = _read_table(string_filename)
    result = result_table.to_pandas()
    tm.assert_frame_equal(result, expected)