def isin(comps, values): """ Compute the isin boolean array Parameters ---------- comps: array-like values: array-like Returns ------- boolean array same length as comps """ if not com.is_list_like(comps): raise TypeError( "only list-like objects are allowed to be passed" " to isin(), you passed a " "[{0}]".format(type(comps).__name__) ) comps = np.asarray(comps) if not com.is_list_like(values): raise TypeError( "only list-like objects are allowed to be passed" " to isin(), you passed a " "[{0}]".format(type(values).__name__) ) # GH11232 # work-around for numpy < 1.8 and comparisions on py3 # faster for larger cases to use np.in1d if (_np_version_under1p8 and compat.PY3) or len(comps) > 1000000: f = lambda x, y: np.in1d(x, np.asarray(list(y))) else: f = lambda x, y: lib.ismember_int64(x, set(y)) # may need i8 conversion for proper membership testing if com.is_datetime64_dtype(comps): from pandas.tseries.tools import to_datetime values = to_datetime(values)._values.view("i8") comps = comps.view("i8") elif com.is_timedelta64_dtype(comps): from pandas.tseries.timedeltas import to_timedelta values = to_timedelta(values)._values.view("i8") comps = comps.view("i8") elif com.is_int64_dtype(comps): pass else: f = lambda x, y: lib.ismember(x, set(values)) return f(comps, values)
def isin(comps, values): """ Compute the isin boolean array Parameters ---------- comps: array-like values: array-like Returns ------- boolean array same length as comps """ if not com.is_list_like(comps): raise TypeError("only list-like objects are allowed to be passed" " to isin(), you passed a " "[{0}]".format(type(comps).__name__)) comps = np.asarray(comps) if not com.is_list_like(values): raise TypeError("only list-like objects are allowed to be passed" " to isin(), you passed a " "[{0}]".format(type(values).__name__)) if not isinstance(values, np.ndarray): values = list(values) # GH11232 # work-around for numpy < 1.8 and comparisions on py3 # faster for larger cases to use np.in1d if (_np_version_under1p8 and compat.PY3) or len(comps) > 1000000: f = lambda x, y: np.in1d(x, np.asarray(list(y))) else: f = lambda x, y: lib.ismember_int64(x, set(y)) # may need i8 conversion for proper membership testing if com.is_datetime64_dtype(comps): from pandas.tseries.tools import to_datetime values = to_datetime(values)._values.view('i8') comps = comps.view('i8') elif com.is_timedelta64_dtype(comps): from pandas.tseries.timedeltas import to_timedelta values = to_timedelta(values)._values.view('i8') comps = comps.view('i8') elif com.is_int64_dtype(comps): pass else: f = lambda x, y: lib.ismember(x, set(values)) return f(comps, values)
def _validate_dtype(dtype): """ require dtype to be None or int64 """ if not (dtype is None or com.is_int64_dtype(dtype)): raise TypeError('Invalid to pass a non-int64 dtype to RangeIndex')