Python pandas._libs.hashtable.StringHashTable() Examples

The following are 4 code examples of pandas._libs.hashtable.StringHashTable(). 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._libs.hashtable , or try the search function .
Example #1
Source File: algorithms.py    From recruit with Apache License 2.0 6 votes vote down vote up 
def _get_data_algo(values, func_map):

    if is_categorical_dtype(values):
        values = values._values_for_rank()

    values, dtype, ndtype = _ensure_data(values)
    if ndtype == 'object':

        # it's cheaper to use a String Hash Table than Object; we infer
        # including nulls because that is the only difference between
        # StringHashTable and ObjectHashtable
        if lib.infer_dtype(values, skipna=False) in ['string']:
            ndtype = 'string'

    f = func_map.get(ndtype, func_map['object'])

    return f, values


# --------------- #
# top-level algos #
# --------------- #
Example #2
Source File: algorithms.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 6 votes vote down vote up 
def _get_data_algo(values, func_map):

    if is_categorical_dtype(values):
        values = values._values_for_rank()

    values, dtype, ndtype = _ensure_data(values)
    if ndtype == 'object':

        # it's cheaper to use a String Hash Table than Object; we infer
        # including nulls because that is the only difference between
        # StringHashTable and ObjectHashtable
        if lib.infer_dtype(values, skipna=False) in ['string']:
            ndtype = 'string'

    f = func_map.get(ndtype, func_map['object'])

    return f, values


# --------------- #
# top-level algos #
# --------------- #
Example #3
Source File: algorithms.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def _get_hashtable_algo(values):
    """
    Parameters
    ----------
    values : arraylike

    Returns
    -------
    tuples(hashtable class,
           vector class,
           values,
           dtype,
           ndtype)
    """
    values, dtype, ndtype = _ensure_data(values)

    if ndtype == 'object':

        # it's cheaper to use a String Hash Table than Object; we infer
        # including nulls because that is the only difference between
        # StringHashTable and ObjectHashtable
        if lib.infer_dtype(values, skipna=False) in ['string']:
            ndtype = 'string'
        else:
            ndtype = 'object'

    htable, table = _hashtables[ndtype]
    return (htable, table, values, dtype, ndtype)
Example #4
Source File: algorithms.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def _get_hashtable_algo(values):
    """
    Parameters
    ----------
    values : arraylike

    Returns
    -------
    tuples(hashtable class,
           vector class,
           values,
           dtype,
           ndtype)
    """
    values, dtype, ndtype = _ensure_data(values)

    if ndtype == 'object':

        # it's cheaper to use a String Hash Table than Object; we infer
        # including nulls because that is the only difference between
        # StringHashTable and ObjectHashtable
        if lib.infer_dtype(values, skipna=False) in ['string']:
            ndtype = 'string'
        else:
            ndtype = 'object'

    htable, table = _hashtables[ndtype]
    return (htable, table, values, dtype, ndtype)