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Module that contains many useful utilities
for validating data or function arguments
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Checks whether 'args' has length of at most 'compat_args'. Raises
a TypeError if that is not the case, similar to in Python when a
function is called with too many arguments.
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Check that the keys in `arg_val_dict` are mapped to their
default values as specified in `compat_args`.
Note that this function is to be called only when it has been
checked that arg_val_dict.keys() is a subset of compat_args
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Checks whether the length of the `*args` argument passed into a function
has at most `len(compat_args)` arguments and whether or not all of these
elements in `args` are set to their default values.
Parameters
----------
fname : str
The name of the function being passed the `*args` parameter
args : tuple
The `*args` parameter passed into a function
max_fname_arg_count : int
The maximum number of arguments that the function `fname`
can accept, excluding those in `args`. Used for displaying
appropriate error messages. Must be non-negative.
compat_args : dict
A dictionary of keys and their associated default values.
In order to accommodate buggy behaviour in some versions of `numpy`,
where a signature displayed keyword arguments but then passed those
arguments **positionally** internally when calling downstream
implementations, a dict ensures that the original
order of the keyword arguments is enforced.
Raises
------
TypeError
If `args` contains more values than there are `compat_args`
ValueError
If `args` contains values that do not correspond to those
of the default values specified in `compat_args`
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Checks whether 'kwargs' contains any keys that are not
in 'compat_args' and raises a TypeError if there is one.
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Checks whether parameters passed to the **kwargs argument in a
function `fname` are valid parameters as specified in `*compat_args`
and whether or not they are set to their default values.
Parameters
----------
fname : str
The name of the function being passed the `**kwargs` parameter
kwargs : dict
The `**kwargs` parameter passed into `fname`
compat_args: dict
A dictionary of keys that `kwargs` is allowed to have and their
associated default values
Raises
------
TypeError if `kwargs` contains keys not in `compat_args`
ValueError if `kwargs` contains keys in `compat_args` that do not
map to the default values specified in `compat_args`
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Checks whether parameters passed to the *args and **kwargs argument in a
function `fname` are valid parameters as specified in `*compat_args`
and whether or not they are set to their default values.
Parameters
----------
fname: str
The name of the function being passed the `**kwargs` parameter
args: tuple
The `*args` parameter passed into a function
kwargs: dict
The `**kwargs` parameter passed into `fname`
max_fname_arg_count: int
The minimum number of arguments that the function `fname`
requires, excluding those in `args`. Used for displaying
appropriate error messages. Must be non-negative.
compat_args: dict
A dictionary of keys that `kwargs` is allowed to
have and their associated default values.
Raises
------
TypeError if `args` contains more values than there are
`compat_args` OR `kwargs` contains keys not in `compat_args`
ValueError if `args` contains values not at the default value (`None`)
`kwargs` contains keys in `compat_args` that do not map to the default
value as specified in `compat_args`
See Also
--------
validate_args : Purely args validation.
validate_kwargs : Purely kwargs validation.
z-() got multiple values for keyword argument 'r+ N)r �tuple�valuesr& r' r �updater5 )r r r( r r � args_dictr s r �validate_args_and_kwargsr; � s� � �P �
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Ensure that argument passed in arg_name can be interpreted as boolean.
Parameters
----------
value : bool
Value to be validated.
arg_name : str
Name of the argument. To be reflected in the error message.
none_allowed : bool, default True
Whether to consider None to be a valid boolean.
int_allowed : bool, default False
Whether to consider integer value to be a valid boolean.
Returns
-------
value
The same value as input.
Raises
------
ValueError
If the value is not a valid boolean.
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Validate the keyword arguments to 'fillna'.
This checks that exactly one of 'value' and 'method' is specified.
If 'method' is specified, this validates that it's a valid method.
Parameters
----------
value, method : object
The 'value' and 'method' keyword arguments for 'fillna'.
validate_scalar_dict_value : bool, default True
Whether to validate that 'value' is a scalar or dict. Specifically,
validate that it is not a list or tuple.
Returns
-------
value, method : object
r )�clean_fill_methodz(Must specify a fill 'value' or 'method'.z>"value" parameter must be a scalar or dict, but you passed a "�"z)Cannot specify both 'value' and 'method'.) �pandas.core.missingrI r r> �listr7 r r@ rA )rB �method�validate_scalar_dict_valuerI s r �validate_fillna_kwargsrO s� � �& 6� �}�� ��C�D�D� �}��+�"�6�*�� �&�=��
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Validate percentiles (used by describe and quantile).
This function checks if the given float or iterable of floats is a valid percentile
otherwise raises a ValueError.
Parameters
----------
q: float or iterable of floats
A single percentile or an iterable of percentiles.
Returns
-------
ndarray
An ndarray of the percentiles if valid.
Raises
------
ValueError if percentiles are not in given interval([0, 1]).
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Check that the `closed` argument is among [None, "left", "right"]
Parameters
----------
closed : {None, "left", "right"}
Returns
-------
left_closed : bool
right_closed : bool
Raises
------
ValueError : if argument is not among valid values
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Check that the `inclusive` argument is among {"both", "neither", "left", "right"}.
Parameters
----------
inclusive : {"both", "neither", "left", "right"}
Returns
-------
left_right_inclusive : tuple[bool, bool]
Raises
------
ValueError : if argument is not among valid values
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