(jC^dZddlmZddlZddlmZmZddlZddlm Z ddl m Z erddl m Z ddlmZdd lmZdd lmZGd d ZGd dZdddf ddZGddZeZ ddZdZe dddZdZe dddZdZe dddZy) z accessor.py contains base classes for implementing accessor properties that can be mixed into or pinned onto other pandas classes. ) annotationsN) TYPE_CHECKINGfinal) set_module)find_stack_level)Callable)TypeTIndex)NDFramecleZdZUeZded<eZded<eddZ ddZ d fd Z xZ S) DirNamesMixinset[str] _accessorszfrozenset[str] _hidden_attrsc4|j|jzS)z: Delete unwanted __dir__ for this object. )rr)selfs 6C:\FundamentalWorkbench\vendor\pandas\core\accessor.py_dir_deletionszDirNamesMixin._dir_deletions#s !3!333cZ|jDchc]}t||s|c}Scc}w)z9 Add additional __dir__ for this object. )rhasattr)raccessors r_dir_additionszDirNamesMixin._dir_additions*s)*.TXGD(/ 4 4 U  rrcZeZdZdZd dZd dZd dZedddf d dZy ) PandasDelegatez@ Abstract base class for delegating methods/properties. ctd|)NzYou cannot access the property  TypeErrorrnameargskwargss r_delegate_property_getz%PandasDelegate._delegate_property_getBs9$@AArc td|d)Nz The property z cannot be setr-)rr0valuer1r2s r_delegate_property_setz%PandasDelegate._delegate_property_setEs-v^<==rctd|)NzYou cannot call method r-r/s r_delegate_methodzPandasDelegate._delegate_methodHs1$899rFc|SNxs rzPandasDelegate.Rs1rTcdfd }dfd }|D]J} |st| d|dk(r || } n|| } |s t|| r>t|| | Ly)a Add accessors to cls from the delegate class. Parameters ---------- cls Class to add the methods/properties to. delegate Class to get methods/properties and docstrings. accessors : list of str List of accessors to add. typ : {'property', 'method'} overwrite : bool, default False Overwrite the method/property in the target class if it exists. accessor_mapping: Callable, default lambda x: x Callable to map the delegate's function to the cls' function. raise_on_missing: bool, default True Raise if an accessor does not exist on delegate. False skips the missing accessor. c fd}fd}|_|_t||tjS)Nc&|jSr:)r3)rr0s r_getterz[PandasDelegate._add_delegate_accessors.._create_delegator_property.._getterks22488rc(|j|Sr:)r6)r new_valuesr0s r_setterz[PandasDelegate._add_delegate_accessors.._create_delegator_property.._setterns224DDr)fgetfsetdoc)r$propertygetattr__doc__)r0rBrEaccessor_mappingdelegates` r_create_delegator_propertyzJPandasDelegate._add_delegate_accessors.._create_delegator_propertyjsI 9 E $G #G H&6t&<=EE rcht}tj|fd}|S)Nc0|jg|i|Sr:)r8)rr1r2r0s rfzSPandasDelegate._add_delegate_accessors.._create_delegator_method..f}s ,t,,TCDCFCCr)rJ functoolswraps)r0methodrQrLrMs` r_create_delegator_methodzHPandasDelegate._add_delegate_accessors.._create_delegator_methodzs9X'7'=>F __V $ D% DHrNrIr0str)rJrsetattr) clsrM accessorstyp overwriterLraise_on_missingrNrUr0rQs ` ` r_add_delegate_accessorsz&PandasDelegate._add_delegate_accessorsKsj>   D$H&6t&:  1r>sqrTc&fd}|S)a Add delegated names to a class using a class decorator. This provides an alternative usage to directly calling `_add_delegate_accessors` below a class definition. Parameters ---------- delegate : object The class to get methods/properties & docstrings. accessors : Sequence[str] List of accessor to add. typ : {'property', 'method'} overwrite : bool, default False Overwrite the method/property in the target class if it exists. accessor_mapping: Callable, default lambda x: x Callable to map the delegate's function to the cls' function. raise_on_missing: bool, default True Raise if an accessor does not exist on delegate. False skips the missing accessor. Returns ------- callable A class decorator. Examples -------- @delegate_names(Categorical, ["categories", "ordered"], "property") class CategoricalAccessor(PandasDelegate): [...] c6|j|S)N)r\rLr])r^)rYrLrZrMr\r]r[s radd_delegate_accessorsz.delegate_names..add_delegate_accessorss/ ##   -- $  rr;)rMrZr[r\rLr]rgs`````` rdelegate_namesrhsP   "!rceZdZdZddZdZy)Accessora Custom property-like object. A descriptor for accessors. Parameters ---------- name : str Namespace that will be accessed under, e.g. ``df.foo``. accessor : cls Class with the extension methods. Notes ----- For accessor, The class's __init__ method assumes that one of ``Series``, ``DataFrame`` or ``Index`` as the single argument ``data``. c ||_||_yr:)_name _accessor)rr0rs r__init__zAccessor.__init__s !rc@| |jS|j|Sr:)rm)robjrYs r__get__zAccessor.__get__s ;>> !~~c""rNr_)r$r%r&rKrnrqr;rrrjrjs&"#rrjcdfd }|S)a Register a custom accessor on objects. Parameters ---------- name : str Name under which the accessor should be registered. A warning is issued if this name conflicts with a preexisting attribute. Returns ------- callable A class decorator. See Also -------- register_dataframe_accessor : Register a custom accessor on DataFrame objects. register_series_accessor : Register a custom accessor on Series objects. register_index_accessor : Register a custom accessor on Index objects. Notes ----- This function allows you to register a custom-defined accessor class for pandas objects (DataFrame, Series, or Index). The requirements for the accessor class are as follows: * Must contain an init method that: * accepts a single object * raises an AttributeError if the object does not have correctly matching inputs for the accessor * Must contain a method for each access pattern. * The methods should be able to take any argument signature. * Accessible using the @property decorator if no additional arguments are needed. c tr.tjd|dddtt t t |jj|S)Nzregistration of accessor z under name z for type z: is overriding a preexisting attribute with the same name.) stacklevel) rwarningswarn UserWarningrrXrjradd)rrYr0s r decoratorz%_register_accessor..decoratorsn 3  MM+H<|(*SG,01+-   T8D(34 4 r)rr r"r r;)r0rYrys`` r_register_accessorrzsZ  ra An accessor that only accepts integers could have a class defined like this: >>> @pd.api.extensions.register_dataframe_accessor("int_accessor") ... class IntAccessor: ... def __init__(self, pandas_obj): ... if not all(pandas_obj[col].dtype == 'int64' for col in pandas_obj.columns): ... raise AttributeError("All columns must contain integer values only") ... self._obj = pandas_obj ... ... def sum(self): ... return self._obj.sum() ... >>> df = pd.DataFrame([[1, 2], ['x', 'y']]) >>> df.int_accessor Traceback (most recent call last): ... AttributeError: All columns must contain integer values only. >>> df = pd.DataFrame([[1, 2], [3, 4]]) >>> df.int_accessor.sum() 0 4 1 6 dtype: int64zpandas.api.extensionsc&ddlm}t||S)a Register a custom accessor on DataFrame objects. Parameters ---------- name : str Name under which the accessor should be registered. A warning is issued if this name conflicts with a preexisting attribute. Returns ------- callable A class decorator. See Also -------- register_dataframe_accessor : Register a custom accessor on DataFrame objects. register_series_accessor : Register a custom accessor on Series objects. register_index_accessor : Register a custom accessor on Index objects. Notes ----- This function allows you to register a custom-defined accessor class for DataFrame. The requirements for the accessor class are as follows: * Must contain an init method that: * accepts a single DataFrame object * raises an AttributeError if the DataFrame object does not have correctly matching inputs for the accessor * Must contain a method for each access pattern. * The methods should be able to take any argument signature. * Accessible using the @property decorator if no additional arguments are needed. Examples -------- An accessor that only accepts integers could have a class defined like this: >>> @pd.api.extensions.register_dataframe_accessor("int_accessor") ... class IntAccessor: ... def __init__(self, pandas_obj): ... if not all( ... pandas_obj[col].dtype == "int64" for col in pandas_obj.columns ... ): ... raise AttributeError("All columns must contain integer values only") ... self._obj = pandas_obj ... ... def sum(self): ... return self._obj.sum() >>> df = pd.DataFrame([[1, 2], ["x", "y"]]) >>> df.int_accessor Traceback (most recent call last): ... AttributeError: All columns must contain integer values only. >>> df = pd.DataFrame([[1, 2], [3, 4]]) >>> df.int_accessor.sum() 0 4 1 6 dtype: int64 r) DataFrame)pandasr|rz)r0r|s rregister_dataframe_accessorr~EsH! dI ..ra An accessor that only accepts integers could have a class defined like this: >>> @pd.api.extensions.register_series_accessor("int_accessor") ... class IntAccessor: ... def __init__(self, pandas_obj): ... if not pandas_obj.dtype == 'int64': ... raise AttributeError("The series must contain integer data only") ... self._obj = pandas_obj ... ... def sum(self): ... return self._obj.sum() ... >>> df = pd.Series([1, 2, 'x']) >>> df.int_accessor Traceback (most recent call last): ... AttributeError: The series must contain integer data only. >>> df = pd.Series([1, 2, 3]) >>> df.int_accessor.sum() 6c&ddlm}t||S)aj Register a custom accessor on Series objects. Parameters ---------- name : str Name under which the accessor should be registered. A warning is issued if this name conflicts with a preexisting attribute. Returns ------- callable A class decorator. See Also -------- register_dataframe_accessor : Register a custom accessor on DataFrame objects. register_series_accessor : Register a custom accessor on Series objects. register_index_accessor : Register a custom accessor on Index objects. Notes ----- This function allows you to register a custom-defined accessor class for Series. The requirements for the accessor class are as follows: * Must contain an init method that: * accepts a single Series object * raises an AttributeError if the Series object does not have correctly matching inputs for the accessor * Must contain a method for each access pattern. * The methods should be able to take any argument signature. * Accessible using the @property decorator if no additional arguments are needed. Examples -------- An accessor that only accepts integers could have a class defined like this: >>> @pd.api.extensions.register_series_accessor("int_accessor") ... class IntAccessor: ... def __init__(self, pandas_obj): ... if not pandas_obj.dtype == "int64": ... raise AttributeError("The series must contain integer data only") ... self._obj = pandas_obj ... ... def sum(self): ... return self._obj.sum() >>> df = pd.Series([1, 2, "x"]) >>> df.int_accessor Traceback (most recent call last): ... AttributeError: The series must contain integer data only. >>> df = pd.Series([1, 2, 3]) >>> df.int_accessor.sum() 6 r)Series)r}rrz)r0rs rregister_series_accessorrs@ dF ++ra[ An accessor that only accepts integers could have a class defined like this: >>> @pd.api.extensions.register_index_accessor("int_accessor") ... class IntAccessor: ... def __init__(self, pandas_obj): ... if not all(isinstance(x, int) for x in pandas_obj): ... raise AttributeError("The index must only be an integer value") ... self._obj = pandas_obj ... ... def even(self): ... return [x for x in self._obj if x % 2 == 0] >>> df = pd.DataFrame.from_dict( ... {"row1": {"1": 1, "2": "a"}, "row2": {"1": 2, "2": "b"}}, orient="index" ... ) >>> df.index.int_accessor Traceback (most recent call last): ... AttributeError: The index must only be an integer value. >>> df = pd.DataFrame( ... {"col1": [1, 2, 3, 4], "col2": ["a", "b", "c", "d"]}, index=[1, 2, 5, 8] ... ) >>> df.index.int_accessor.even() [2, 8]c&ddlm}t||S)aQ Register a custom accessor on Index objects. Parameters ---------- name : str Name under which the accessor should be registered. A warning is issued if this name conflicts with a preexisting attribute. Returns ------- callable A class decorator. See Also -------- register_dataframe_accessor : Register a custom accessor on DataFrame objects. register_series_accessor : Register a custom accessor on Series objects. register_index_accessor : Register a custom accessor on Index objects. Notes ----- This function allows you to register a custom-defined accessor class for Index. The requirements for the accessor class are as follows: * Must contain an init method that: * accepts a single Index object * raises an AttributeError if the Index object does not have correctly matching inputs for the accessor * Must contain a method for each access pattern. * The methods should be able to take any argument signature. * Accessible using the @property decorator if no additional arguments are needed. Examples -------- An accessor that only accepts integers could have a class defined like this: >>> @pd.api.extensions.register_index_accessor("int_accessor") ... class IntAccessor: ... def __init__(self, pandas_obj): ... if not all(isinstance(x, int) for x in pandas_obj): ... raise AttributeError("The index must only be an integer value") ... self._obj = pandas_obj ... ... def even(self): ... return [x for x in self._obj if x % 2 == 0] >>> df = pd.DataFrame.from_dict( ... {"row1": {"1": 1, "2": "a"}, "row2": {"1": 2, "2": "b"}}, orient="index" ... ) >>> df.index.int_accessor Traceback (most recent call last): ... AttributeError: The index must only be an integer value. >>> df = pd.DataFrame( ... {"col1": [1, 2, 3, 4], "col2": ["a", "b", "c", "d"]}, index=[1, 2, 5, 8] ... ) >>> df.index.int_accessor.even() [2, 8] rr )r}r rz)r0r s rregister_index_accessorrsH dE **r) rZr#r[rWr\rarLrbr]ra)r0rWrYztype[NDFrame | Index]r"Callable[[TypeT], TypeT])r0rWr"r) rK __future__rrRtypingrrrupandas.util._decoratorsrpandas.util._exceptionsrcollections.abcrpandas._typingr r}r pandas.core.genericr rr+rhrjCachedAccessorrz_register_df_examplesr~_register_series_examplesr_register_index_examplesrr;rrrs+#5($+