def transform(obj: FrameOrSeries, func: AggFuncType, axis: Axis, *args,
**kwargs) -> FrameOrSeries:
"""
Transform a DataFrame or Series
Parameters
----------
obj : DataFrame or Series
Object to compute the transform on.
func : string, function, list, or dictionary
Function(s) to compute the transform with.
axis : {0 or 'index', 1 or 'columns'}
Axis along which the function is applied:
* 0 or 'index': apply function to each column.
* 1 or 'columns': apply function to each row.
Returns
-------
DataFrame or Series
Result of applying ``func`` along the given axis of the
Series or DataFrame.
Raises
------
ValueError
If the transform function fails or does not transform.
"""
is_series = obj.ndim == 1
if obj._get_axis_number(axis) == 1:
assert not is_series
return transform(obj.T, func, 0, *args, **kwargs).T
if isinstance(func, list):
if is_series:
func = {com.get_callable_name(v) or v: v for v in func}
else:
func = {col: func for col in obj}
if isinstance(func, dict):
return transform_dict_like(obj, func, *args, **kwargs)
# func is either str or callable
try:
result = transform_str_or_callable(obj, func, *args, **kwargs)
except Exception:
raise ValueError("Transform function failed")
# Functions that transform may return empty Series/DataFrame
# when the dtype is not appropriate
if isinstance(result, (ABCSeries, ABCDataFrame)) and result.empty:
raise ValueError("Transform function failed")
if not isinstance(result,
(ABCSeries, ABCDataFrame)) or not result.index.equals(
obj.index):
raise ValueError("Function did not transform")
return result
def transform(obj: FrameOrSeries, func: AggFuncType, axis: Axis, *args,
**kwargs) -> FrameOrSeries:
"""
Transform a DataFrame or Series
Parameters
----------
obj : DataFrame or Series
Object to compute the transform on.
func : string, function, list, or dictionary
Function(s) to compute the transform with.
axis : {0 or 'index', 1 or 'columns'}
Axis along which the function is applied:
* 0 or 'index': apply function to each column.
* 1 or 'columns': apply function to each row.
Returns
-------
DataFrame or Series
Result of applying ``func`` along the given axis of the
Series or DataFrame.
Raises
------
ValueError
If the transform function fails or does not transform.
"""
from pandas.core.reshape.concat import concat
is_series = obj.ndim == 1
if obj._get_axis_number(axis) == 1:
assert not is_series
return transform(obj.T, func, 0, *args, **kwargs).T
if isinstance(func, list):
if is_series:
func = {com.get_callable_name(v) or v: v for v in func}
else:
func = {col: func for col in obj}
if isinstance(func, dict):
if not is_series:
cols = sorted(set(func.keys()) - set(obj.columns))
if len(cols) > 0:
raise SpecificationError(f"Column(s) {cols} do not exist")
if any(isinstance(v, dict) for v in func.values()):
# GH 15931 - deprecation of renaming keys
raise SpecificationError("nested renamer is not supported")
results = {}
for name, how in func.items():
colg = obj._gotitem(name, ndim=1)
try:
results[name] = transform(colg, how, 0, *args, **kwargs)
except Exception as e:
if str(e) == "Function did not transform":
raise e
# combine results
if len(results) == 0:
raise ValueError("Transform function failed")
return concat(results, axis=1)
# func is either str or callable
try:
if isinstance(func, str):
result = obj._try_aggregate_string_function(func, *args, **kwargs)
else:
f = obj._get_cython_func(func)
if f and not args and not kwargs:
result = getattr(obj, f)()
else:
try:
result = obj.apply(func, args=args, **kwargs)
except Exception:
result = func(obj, *args, **kwargs)
except Exception:
raise ValueError("Transform function failed")
# Functions that transform may return empty Series/DataFrame
# when the dtype is not appropriate
if isinstance(result, (ABCSeries, ABCDataFrame)) and result.empty:
raise ValueError("Transform function failed")
if not isinstance(result,
(ABCSeries, ABCDataFrame)) or not result.index.equals(
obj.index):
raise ValueError("Function did not transform")
return result
