Python pandas._libs.hashtable.Factorizer() Examples
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code examples of pandas._libs.hashtable.Factorizer().
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Example #1
Source File: merge.py From vnpy_crypto with MIT License | 4 votes |
def _factorize_keys(lk, rk, sort=True): if is_datetime64tz_dtype(lk) and is_datetime64tz_dtype(rk): lk = lk.values rk = rk.values # if we exactly match in categories, allow us to factorize on codes if (is_categorical_dtype(lk) and is_categorical_dtype(rk) and lk.is_dtype_equal(rk)): klass = libhashtable.Int64Factorizer if lk.categories.equals(rk.categories): rk = rk.codes else: # Same categories in different orders -> recode rk = _recode_for_categories(rk.codes, rk.categories, lk.categories) lk = _ensure_int64(lk.codes) rk = _ensure_int64(rk) elif is_int_or_datetime_dtype(lk) and is_int_or_datetime_dtype(rk): klass = libhashtable.Int64Factorizer lk = _ensure_int64(com._values_from_object(lk)) rk = _ensure_int64(com._values_from_object(rk)) else: klass = libhashtable.Factorizer lk = _ensure_object(lk) rk = _ensure_object(rk) rizer = klass(max(len(lk), len(rk))) llab = rizer.factorize(lk) rlab = rizer.factorize(rk) count = rizer.get_count() if sort: uniques = rizer.uniques.to_array() llab, rlab = _sort_labels(uniques, llab, rlab) # NA group lmask = llab == -1 lany = lmask.any() rmask = rlab == -1 rany = rmask.any() if lany or rany: if lany: np.putmask(llab, lmask, count) if rany: np.putmask(rlab, rmask, count) count += 1 return llab, rlab, count
Example #2
Source File: merge.py From Splunking-Crime with GNU Affero General Public License v3.0 | 4 votes |
def _factorize_keys(lk, rk, sort=True): if is_datetime64tz_dtype(lk) and is_datetime64tz_dtype(rk): lk = lk.values rk = rk.values # if we exactly match in categories, allow us to factorize on codes if (is_categorical_dtype(lk) and is_categorical_dtype(rk) and lk.is_dtype_equal(rk)): klass = libhashtable.Int64Factorizer lk = _ensure_int64(lk.codes) rk = _ensure_int64(rk.codes) elif is_int_or_datetime_dtype(lk) and is_int_or_datetime_dtype(rk): klass = libhashtable.Int64Factorizer lk = _ensure_int64(com._values_from_object(lk)) rk = _ensure_int64(com._values_from_object(rk)) else: klass = libhashtable.Factorizer lk = _ensure_object(lk) rk = _ensure_object(rk) rizer = klass(max(len(lk), len(rk))) llab = rizer.factorize(lk) rlab = rizer.factorize(rk) count = rizer.get_count() if sort: uniques = rizer.uniques.to_array() llab, rlab = _sort_labels(uniques, llab, rlab) # NA group lmask = llab == -1 lany = lmask.any() rmask = rlab == -1 rany = rmask.any() if lany or rany: if lany: np.putmask(llab, lmask, count) if rany: np.putmask(rlab, rmask, count) count += 1 return llab, rlab, count
Example #3
Source File: merge.py From elasticintel with GNU General Public License v3.0 | 4 votes |
def _factorize_keys(lk, rk, sort=True): if is_datetime64tz_dtype(lk) and is_datetime64tz_dtype(rk): lk = lk.values rk = rk.values # if we exactly match in categories, allow us to factorize on codes if (is_categorical_dtype(lk) and is_categorical_dtype(rk) and lk.is_dtype_equal(rk)): klass = libhashtable.Int64Factorizer lk = _ensure_int64(lk.codes) rk = _ensure_int64(rk.codes) elif is_int_or_datetime_dtype(lk) and is_int_or_datetime_dtype(rk): klass = libhashtable.Int64Factorizer lk = _ensure_int64(com._values_from_object(lk)) rk = _ensure_int64(com._values_from_object(rk)) else: klass = libhashtable.Factorizer lk = _ensure_object(lk) rk = _ensure_object(rk) rizer = klass(max(len(lk), len(rk))) llab = rizer.factorize(lk) rlab = rizer.factorize(rk) count = rizer.get_count() if sort: uniques = rizer.uniques.to_array() llab, rlab = _sort_labels(uniques, llab, rlab) # NA group lmask = llab == -1 lany = lmask.any() rmask = rlab == -1 rany = rmask.any() if lany or rany: if lany: np.putmask(llab, lmask, count) if rany: np.putmask(rlab, rmask, count) count += 1 return llab, rlab, count