How to use is_subdtype method in pandera

Best Python code snippet using pandera_python

dtypes.py

Source:dtypes.py

...293        return "timedelta"294###############################################################################295# Utilities296###############################################################################297def is_subdtype(298    arg1: Union[DataType, Type[DataType]],299    arg2: Union[DataType, Type[DataType]],300) -> bool:301    """Returns True if first argument is lower/equal in DataType hierarchy."""302    arg1_cls = arg1 if inspect.isclass(arg1) else arg1.__class__303    arg2_cls = arg2 if inspect.isclass(arg2) else arg2.__class__304    return issubclass(arg1_cls, arg2_cls)  # type: ignore305def is_int(pandera_dtype: Union[DataType, Type[DataType]]) -> bool:306    """Return True if :class:`pandera.dtypes.DataType` is an integer."""307    return is_subdtype(pandera_dtype, Int)308def is_uint(pandera_dtype: Union[DataType, Type[DataType]]) -> bool:309    """Return True if :class:`pandera.dtypes.DataType` is310    an unsigned integer."""311    return is_subdtype(pandera_dtype, UInt)312def is_float(pandera_dtype: Union[DataType, Type[DataType]]) -> bool:313    """Return True if :class:`pandera.dtypes.DataType` is a float."""314    return is_subdtype(pandera_dtype, Float)315def is_complex(pandera_dtype: Union[DataType, Type[DataType]]) -> bool:316    """Return True if :class:`pandera.dtypes.DataType` is a complex number."""317    return is_subdtype(pandera_dtype, Complex)318def is_numeric(pandera_dtype: Union[DataType, Type[DataType]]) -> bool:319    """Return True if :class:`pandera.dtypes.DataType` is a complex number."""320    return is_subdtype(pandera_dtype, _Number)321def is_bool(pandera_dtype: Union[DataType, Type[DataType]]) -> bool:322    """Return True if :class:`pandera.dtypes.DataType` is a boolean."""323    return is_subdtype(pandera_dtype, Bool)324def is_string(pandera_dtype: Union[DataType, Type[DataType]]) -> bool:325    """Return True if :class:`pandera.dtypes.DataType` is a string."""326    return is_subdtype(pandera_dtype, String)327def is_category(pandera_dtype: Union[DataType, Type[DataType]]) -> bool:328    """Return True if :class:`pandera.dtypes.DataType` is a category."""329    return is_subdtype(pandera_dtype, Category)330def is_datetime(pandera_dtype: Union[DataType, Type[DataType]]) -> bool:331    """Return True if :class:`pandera.dtypes.DataType` is a datetime."""332    return is_subdtype(pandera_dtype, DateTime)333def is_timedelta(pandera_dtype: Union[DataType, Type[DataType]]) -> bool:334    """Return True if :class:`pandera.dtypes.DataType` is a timedelta."""...

utils.py

Source:utils.py

...14    dtype_groups = column_series.groupby(dataframe.dtypes).groups15    if dtype_filter is None:16        dtype_filter = null_filter17    return {k.name: v for k, v in dtype_groups.items() if dtype_filter(k.name)}18def is_subdtype(dtype1, dtype2):19    if isinstance(dtype1, six.string_types):20        try:21            dtype1 = np.dtype(dtype1)22        except TypeError:23            return False24    return np.issubdtype(dtype1, dtype2)25def is_ordinal(dtype):26    return is_subdtype(dtype, np.integer)27def is_continous(dtype):28    return is_subdtype(dtype, np.number) and not is_ordinal(dtype)29def is_numeric(dtype):30    return is_subdtype(dtype, np.number)31def is_categorical(dtype):32    return not is_numeric(dtype)33def ordinal_columns(dataframe):34    return unflatten_list(dtype_dict(dataframe, is_ordinal).values())35def continous_columns(dataframe):36    return unflatten_list(dtype_dict(dataframe, is_continous).values())37def numeric_columns(dataframe):38    return unflatten_list(dtype_dict(dataframe, is_numeric).values())39def categorical_columns(dataframe):40    return unflatten_list(dtype_dict(dataframe, is_categorical).values())41def mean_impute_numerics(dataframe):42    numerics = dataframe.values43    # impute with mean44    imputer = Imputer(strategy='mean', missing_values='NaN')...

test_validators.py

Source:test_validators.py

...56    v = in_bounds((0, 5), closed=closed)57    expected = f"<in_bounds validator with bounds {interval_str}>"58    assert repr(v) == expected59def test_is_subdtype_success(simple_attr):60    v = is_subdtype(np.number)61    # nothing happends62    v(None, simple_attr, np.array([1, 2, 3]))63    v(None, simple_attr, np.array([1.0, 2.0, 3.0]))64def test_is_subdtype_fail(simple_attr):65    v = is_subdtype(np.number)66    with pytest.raises(TypeError, match=r".*not a sub-dtype of.*"):67        v(None, simple_attr, np.array(["1", "2", "3"]))68def test_is_subdtype_repr():69    v = is_subdtype(np.number)...

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