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 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)])
def get_median(x):
mask = notnull(x)
if not skipna and not mask.all():
return np.nan
return lib.median(x[mask])
