Python pandas.core.dtypes.cast.infer_dtype_from_scalar() Examples

The following are 5 code examples of pandas.core.dtypes.cast.infer_dtype_from_scalar(). 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.core.dtypes.cast , or try the search function .
Example #1
Source File: hashing.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def _hash_scalar(val, encoding='utf8', hash_key=None):
    """
    Hash scalar value

    Returns
    -------
    1d uint64 numpy array of hash value, of length 1
    """

    if isna(val):
        # this is to be consistent with the _hash_categorical implementation
        return np.array([np.iinfo(np.uint64).max], dtype='u8')

    if getattr(val, 'tzinfo', None) is not None:
        # for tz-aware datetimes, we need the underlying naive UTC value and
        # not the tz aware object or pd extension type (as
        # infer_dtype_from_scalar would do)
        if not isinstance(val, tslibs.Timestamp):
            val = tslibs.Timestamp(val)
        val = val.tz_convert(None)

    dtype, val = infer_dtype_from_scalar(val)
    vals = np.array([val], dtype=dtype)

    return hash_array(vals, hash_key=hash_key, encoding=encoding,
                      categorize=False)
Example #2
Source File: hashing.py    From vnpy_crypto with MIT License 5 votes vote down vote up 
def _hash_scalar(val, encoding='utf8', hash_key=None):
    """
    Hash scalar value

    Returns
    -------
    1d uint64 numpy array of hash value, of length 1
    """

    if isna(val):
        # this is to be consistent with the _hash_categorical implementation
        return np.array([np.iinfo(np.uint64).max], dtype='u8')

    if getattr(val, 'tzinfo', None) is not None:
        # for tz-aware datetimes, we need the underlying naive UTC value and
        # not the tz aware object or pd extension type (as
        # infer_dtype_from_scalar would do)
        if not isinstance(val, tslib.Timestamp):
            val = tslib.Timestamp(val)
        val = val.tz_convert(None)

    dtype, val = infer_dtype_from_scalar(val)
    vals = np.array([val], dtype=dtype)

    return hash_array(vals, hash_key=hash_key, encoding=encoding,
                      categorize=False)
Example #3
Source File: hashing.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def _hash_scalar(val, encoding='utf8', hash_key=None):
    """
    Hash scalar value

    Returns
    -------
    1d uint64 numpy array of hash value, of length 1
    """

    if isna(val):
        # this is to be consistent with the _hash_categorical implementation
        return np.array([np.iinfo(np.uint64).max], dtype='u8')

    if getattr(val, 'tzinfo', None) is not None:
        # for tz-aware datetimes, we need the underlying naive UTC value and
        # not the tz aware object or pd extension type (as
        # infer_dtype_from_scalar would do)
        if not isinstance(val, tslibs.Timestamp):
            val = tslibs.Timestamp(val)
        val = val.tz_convert(None)

    dtype, val = infer_dtype_from_scalar(val)
    vals = np.array([val], dtype=dtype)

    return hash_array(vals, hash_key=hash_key, encoding=encoding,
                      categorize=False)
Example #4
Source File: hashing.py    From Splunking-Crime with GNU Affero General Public License v3.0 5 votes vote down vote up 
def _hash_scalar(val, encoding='utf8', hash_key=None):
    """
    Hash scalar value

    Returns
    -------
    1d uint64 numpy array of hash value, of length 1
    """

    if isna(val):
        # this is to be consistent with the _hash_categorical implementation
        return np.array([np.iinfo(np.uint64).max], dtype='u8')

    if getattr(val, 'tzinfo', None) is not None:
        # for tz-aware datetimes, we need the underlying naive UTC value and
        # not the tz aware object or pd extension type (as
        # infer_dtype_from_scalar would do)
        if not isinstance(val, tslib.Timestamp):
            val = tslib.Timestamp(val)
        val = val.tz_convert(None)

    dtype, val = infer_dtype_from_scalar(val)
    vals = np.array([val], dtype=dtype)

    return hash_array(vals, hash_key=hash_key, encoding=encoding,
                      categorize=False)
Example #5
Source File: hashing.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up 
def _hash_scalar(val, encoding='utf8', hash_key=None):
    """
    Hash scalar value

    Returns
    -------
    1d uint64 numpy array of hash value, of length 1
    """

    if isna(val):
        # this is to be consistent with the _hash_categorical implementation
        return np.array([np.iinfo(np.uint64).max], dtype='u8')

    if getattr(val, 'tzinfo', None) is not None:
        # for tz-aware datetimes, we need the underlying naive UTC value and
        # not the tz aware object or pd extension type (as
        # infer_dtype_from_scalar would do)
        if not isinstance(val, tslib.Timestamp):
            val = tslib.Timestamp(val)
        val = val.tz_convert(None)

    dtype, val = infer_dtype_from_scalar(val)
    vals = np.array([val], dtype=dtype)

    return hash_array(vals, hash_key=hash_key, encoding=encoding,
                      categorize=False)