def f(arr): mask = common.notnull(arr) if skipna: return _tseries.median(arr[mask]) else: if not mask.all(): return np.nan return _tseries.median(arr)
def median(self): """ Compute median value of non-null values """ arr = self.values if arr.dtype != np.float_: arr = arr.astype(float) arr = arr[notnull(arr)] return _tseries.median(arr)
def get_median(x): mask = notnull(x) if not skipna and not mask.all(): return np.nan return lib.median(x[mask])
def f(arr): return _tseries.median(arr[common.notnull(arr)])