Python pandas.PeriodDtype() Examples

The following are 2 code examples of pandas.PeriodDtype(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module pandas , or try the search function .
Example #1
Source File: filtering_fe_autotype.py    From dash-docs with MIT License 6 votes vote down vote up 
def table_type(df_column):
    # Note - this only works with Pandas >= 1.0.0

    if sys.version_info < (3, 0):  # Pandas 1.0.0 does not support Python 2
        return 'any'

    if isinstance(df_column.dtype, pd.DatetimeTZDtype):
        return 'datetime',
    elif (isinstance(df_column.dtype, pd.StringDtype) or
            isinstance(df_column.dtype, pd.BooleanDtype) or
            isinstance(df_column.dtype, pd.CategoricalDtype) or
            isinstance(df_column.dtype, pd.PeriodDtype)):
        return 'text'
    elif (isinstance(df_column.dtype, pd.SparseDtype) or
            isinstance(df_column.dtype, pd.IntervalDtype) or
            isinstance(df_column.dtype, pd.Int8Dtype) or
            isinstance(df_column.dtype, pd.Int16Dtype) or
            isinstance(df_column.dtype, pd.Int32Dtype) or
            isinstance(df_column.dtype, pd.Int64Dtype)):
        return 'numeric'
    else:
        return 'any'
Example #2
Source File: test_dtypes.py    From pandera with MIT License 4 votes vote down vote up 
def test_pandas_extension_types():
    """Test pandas extension data type happy path."""
    # pylint: disable=no-member
    test_params = [
        (
            pd.CategoricalDtype(),
            pd.Series(["a", "a", "b", "b", "c", "c"], dtype="category"),
            None
        ),
        (
            pd.DatetimeTZDtype(tz='UTC'),
            pd.Series(
                pd.date_range(start="20200101", end="20200301"),
                dtype="datetime64[ns, utc]"
            ),
            None
        ),
        (pd.Int64Dtype(), pd.Series(range(10), dtype="Int64"), None),
        (pd.StringDtype(), pd.Series(["foo", "bar", "baz"], dtype="string"), None),
        (
            pd.PeriodDtype(freq='D'),
            pd.Series(pd.period_range('1/1/2019', '1/1/2020', freq='D')),
            None
        ),
        (
            pd.SparseDtype("float"),
            pd.Series(range(100)).where(
                lambda s: s < 5, other=np.nan).astype("Sparse[float]"),
            {"nullable": True},
        ),
        (
            pd.BooleanDtype(),
            pd.Series([1, 0, 0, 1, 1], dtype="boolean"),
            None
        ),
        (
            pd.IntervalDtype(subtype="int64"),
            pd.Series(pd.IntervalIndex.from_breaks([0, 1, 2, 3, 4])),
            None,
        )
    ]
    for dtype, data, series_kwargs in test_params:
        series_kwargs = {} if series_kwargs is None else series_kwargs
        series_schema = SeriesSchema(pandas_dtype=dtype, **series_kwargs)
        assert isinstance(series_schema.validate(data), pd.Series)