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Python common.is_datetime64tz_dtype方法代码示例

本文整理汇总了Python中pandas.core.dtypes.common.is_datetime64tz_dtype方法的典型用法代码示例。如果您正苦于以下问题:Python common.is_datetime64tz_dtype方法的具体用法?Python common.is_datetime64tz_dtype怎么用?Python common.is_datetime64tz_dtype使用的例子?那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在pandas.core.dtypes.common的用法示例。


在下文中一共展示了common.is_datetime64tz_dtype方法的3个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: test_is_datetime64tz_dtype

# 需要导入模块: from pandas.core.dtypes import common [as 别名]
# 或者: from pandas.core.dtypes.common import is_datetime64tz_dtype [as 别名]
def test_is_datetime64tz_dtype():
    assert not com.is_datetime64tz_dtype(object)
    assert not com.is_datetime64tz_dtype([1, 2, 3])
    assert not com.is_datetime64tz_dtype(pd.DatetimeIndex([1, 2, 3]))
    assert com.is_datetime64tz_dtype(pd.DatetimeIndex(['2000'],
                                                      tz="US/Eastern")) 
开发者ID:Frank-qlu,项目名称:recruit,代码行数:8,代码来源:test_common.py

示例2: _hash_categories

# 需要导入模块: from pandas.core.dtypes import common [as 别名]
# 或者: from pandas.core.dtypes.common import is_datetime64tz_dtype [as 别名]
def _hash_categories(categories, ordered=True):
        from pandas.core.util.hashing import (
            hash_array, _combine_hash_arrays, hash_tuples
        )
        from pandas.core.dtypes.common import is_datetime64tz_dtype, _NS_DTYPE

        if len(categories) and isinstance(categories[0], tuple):
            # assumes if any individual category is a tuple, then all our. ATM
            # I don't really want to support just some of the categories being
            # tuples.
            categories = list(categories)  # breaks if a np.array of categories
            cat_array = hash_tuples(categories)
        else:
            if categories.dtype == 'O':
                types = [type(x) for x in categories]
                if not len(set(types)) == 1:
                    # TODO: hash_array doesn't handle mixed types. It casts
                    # everything to a str first, which means we treat
                    # {'1', '2'} the same as {'1', 2}
                    # find a better solution
                    hashed = hash((tuple(categories), ordered))
                    return hashed

            if is_datetime64tz_dtype(categories.dtype):
                # Avoid future warning.
                categories = categories.astype(_NS_DTYPE)

            cat_array = hash_array(np.asarray(categories), categorize=False)
        if ordered:
            cat_array = np.vstack([
                cat_array, np.arange(len(cat_array), dtype=cat_array.dtype)
            ])
        else:
            cat_array = [cat_array]
        hashed = _combine_hash_arrays(iter(cat_array),
                                      num_items=len(cat_array))
        return np.bitwise_xor.reduce(hashed) 
开发者ID:Frank-qlu,项目名称:recruit,代码行数:39,代码来源:dtypes.py

示例3: test_is_datetime64tz_dtype

# 需要导入模块: from pandas.core.dtypes import common [as 别名]
# 或者: from pandas.core.dtypes.common import is_datetime64tz_dtype [as 别名]
def test_is_datetime64tz_dtype():
    assert not com.is_datetime64tz_dtype(object)
    assert not com.is_datetime64tz_dtype([1, 2, 3])
    assert not com.is_datetime64tz_dtype(pd.DatetimeIndex([1, 2, 3]))
    assert com.is_datetime64tz_dtype(pd.DatetimeIndex(
        [1, 2, 3], tz="US/Eastern")) 
开发者ID:birforce,项目名称:vnpy_crypto,代码行数:8,代码来源:test_common.py


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