def na_op(x, y):
try:
result = expressions.evaluate(op,
str_rep,
x,
y,
raise_on_error=True,
**eval_kwargs)
except TypeError:
if isinstance(y, (pa.Array, pd.Series, pd.Index)):
dtype = np.find_common_type([x.dtype, y.dtype], [])
result = np.empty(x.size, dtype=dtype)
mask = notnull(x) & notnull(y)
result[mask] = op(x[mask], _values_from_object(y[mask]))
elif isinstance(x, pa.Array):
result = pa.empty(len(x), dtype=x.dtype)
mask = notnull(x)
result[mask] = op(x[mask], y)
else:
raise TypeError(
"{typ} cannot perform the operation {op}".format(
typ=type(x).__name__, op=str_rep))
result, changed = com._maybe_upcast_putmask(result, ~mask, pa.NA)
result = com._fill_zeros(result, x, y, name, fill_zeros)
return result
def na_op(x, y):
try:
result = expressions.evaluate(op, str_rep, x, y,
raise_on_error=True, **eval_kwargs)
except TypeError:
result = pa.empty(len(x), dtype=x.dtype)
mask = notnull(x)
result[mask] = op(x[mask], y)
result, changed = com._maybe_upcast_putmask(result, -mask, pa.NA)
result = com._fill_zeros(result, y, fill_zeros)
return result
def na_op(x, y):
try:
result = expressions.evaluate(op, str_rep, x, y,
raise_on_error=True, **eval_kwargs)
except TypeError:
# TODO: might need to find_common_type here?
result = pa.empty(len(x), dtype=x.dtype)
mask = notnull(x)
result[mask] = op(x[mask], y)
result, changed = com._maybe_upcast_putmask(result, ~mask, pa.NA)
result = com._fill_zeros(result, x, y, name, fill_zeros)
return result
def na_op(x, y):
try:
result = expressions.evaluate(op, str_rep, x, y, raise_on_error=True, **eval_kwargs)
except TypeError:
if isinstance(y, (pa.Array, pd.Series)):
dtype = np.find_common_type([x.dtype, y.dtype], [])
result = np.empty(x.size, dtype=dtype)
mask = notnull(x) & notnull(y)
result[mask] = op(x[mask], y[mask])
else:
result = pa.empty(len(x), dtype=x.dtype)
mask = notnull(x)
result[mask] = op(x[mask], y)
result, changed = com._maybe_upcast_putmask(result, -mask, pa.NA)
result = com._fill_zeros(result, y, fill_zeros)
return result
def na_op(x, y):
try:
result = expressions.evaluate(op, str_rep, x, y,
raise_on_error=True, **eval_kwargs)
except TypeError:
if isinstance(y, (pa.Array, pd.Series)):
dtype = np.find_common_type([x.dtype, y.dtype], [])
result = np.empty(x.size, dtype=dtype)
mask = notnull(x) & notnull(y)
result[mask] = op(x[mask], y[mask])
else:
result = pa.empty(len(x), dtype=x.dtype)
mask = notnull(x)
result[mask] = op(x[mask], y)
result, changed = com._maybe_upcast_putmask(result, ~mask, pa.NA)
result = com._fill_zeros(result, x, y, name, fill_zeros)
return result
def na_op(x, y):
try:
result = expressions.evaluate(op, str_rep, x, y,
raise_on_error=True, **eval_kwargs)
except TypeError:
if isinstance(y, (pa.Array, pd.Series, pd.Index)):
dtype = np.find_common_type([x.dtype, y.dtype], [])
result = np.empty(x.size, dtype=dtype)
mask = notnull(x) & notnull(y)
result[mask] = op(x[mask], _values_from_object(y[mask]))
elif isinstance(x, pa.Array):
result = pa.empty(len(x), dtype=x.dtype)
mask = notnull(x)
result[mask] = op(x[mask], y)
else:
raise TypeError("{typ} cannot perform the operation {op}".format(typ=type(x).__name__,op=str_rep))
result, changed = com._maybe_upcast_putmask(result, ~mask, pa.NA)
result = com._fill_zeros(result, x, y, name, fill_zeros)
return result