BoghdadyJR/codesearch_python · Datasets at Hugging Face

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def _generate_range_overflow_safe_signed(endpoint, periods, stride, side): """ A special case for _generate_range_overflow_safe where `periods * stride` can be calculated without overflowing int64 bounds. """ assert side in ['start', 'end'] if side == 'end': stride *= -1 with np.err...
def set_locale(new_locale, lc_var=locale.LC_ALL): """ Context manager for temporarily setting a locale. Parameters ---------- new_locale : str or tuple A string of the form <language_country>.<encoding>. For example to set the current locale to US English with a UTF8 encoding, you w...
def can_set_locale(lc, lc_var=locale.LC_ALL): """ Check to see if we can set a locale, and subsequently get the locale, without raising an Exception. Parameters ---------- lc : str The locale to attempt to set. lc_var : int, default `locale.LC_ALL` The category of the locale...
def _valid_locales(locales, normalize): """ Return a list of normalized locales that do not throw an ``Exception`` when set. Parameters ---------- locales : str A string where each locale is separated by a newline. normalize : bool Whether to call ``locale.normalize`` on eac...
def get_locales(prefix=None, normalize=True, locale_getter=_default_locale_getter): """ Get all the locales that are available on the system. Parameters ---------- prefix : str If not ``None`` then return only those locales with the prefix provided. For example to ge...
def ensure_float(arr): """ Ensure that an array object has a float dtype if possible. Parameters ---------- arr : array-like The array whose data type we want to enforce as float. Returns ------- float_arr : The original array cast to the float dtype if possible...
def ensure_categorical(arr): """ Ensure that an array-like object is a Categorical (if not already). Parameters ---------- arr : array-like The array that we want to convert into a Categorical. Returns ------- cat_arr : The original array cast as a Categorical. If it already ...
def ensure_int64_or_float64(arr, copy=False): """ Ensure that an dtype array of some integer dtype has an int64 dtype if possible If it's not possible, potentially because of overflow, convert the array to float64 instead. Parameters ---------- arr : array-like The array whose...
def classes_and_not_datetimelike(*klasses): """ evaluate if the tipo is a subclass of the klasses and not a datetimelike """ return lambda tipo: (issubclass(tipo, klasses) and not issubclass(tipo, (np.datetime64, np.timedelta64)))
def is_sparse(arr): """ Check whether an array-like is a 1-D pandas sparse array. Check that the one-dimensional array-like is a pandas sparse array. Returns True if it is a pandas sparse array, not another type of sparse array. Parameters ---------- arr : array-like Array-like...
def is_scipy_sparse(arr): """ Check whether an array-like is a scipy.sparse.spmatrix instance. Parameters ---------- arr : array-like The array-like to check. Returns ------- boolean Whether or not the array-like is a scipy.sparse.spmatrix instance. Notes -----...
def is_offsetlike(arr_or_obj): """ Check if obj or all elements of list-like is DateOffset Parameters ---------- arr_or_obj : object Returns ------- boolean Whether the object is a DateOffset or listlike of DatetOffsets Examples -------- >>> is_offsetlike(pd.DateOf...
def is_period(arr): """ Check whether an array-like is a periodical index. .. deprecated:: 0.24.0 Parameters ---------- arr : array-like The array-like to check. Returns ------- boolean Whether or not the array-like is a periodical index. Examples --------...
def is_string_dtype(arr_or_dtype): """ Check whether the provided array or dtype is of the string dtype. Parameters ---------- arr_or_dtype : array-like The array or dtype to check. Returns ------- boolean Whether or not the array or dtype is of the string dtype. E...
def is_period_arraylike(arr): """ Check whether an array-like is a periodical array-like or PeriodIndex. Parameters ---------- arr : array-like The array-like to check. Returns ------- boolean Whether or not the array-like is a periodical array-like or PeriodInd...
def is_datetime_arraylike(arr): """ Check whether an array-like is a datetime array-like or DatetimeIndex. Parameters ---------- arr : array-like The array-like to check. Returns ------- boolean Whether or not the array-like is a datetime array-like or DatetimeI...
def is_datetimelike(arr): """ Check whether an array-like is a datetime-like array-like. Acceptable datetime-like objects are (but not limited to) datetime indices, periodic indices, and timedelta indices. Parameters ---------- arr : array-like The array-like to check. Returns...
def is_dtype_equal(source, target): """ Check if two dtypes are equal. Parameters ---------- source : The first dtype to compare target : The second dtype to compare Returns ---------- boolean Whether or not the two dtypes are equal. Examples -------- >>> is_dt...
def is_dtype_union_equal(source, target): """ Check whether two arrays have compatible dtypes to do a union. numpy types are checked with ``is_dtype_equal``. Extension types are checked separately. Parameters ---------- source : The first dtype to compare target : The second dtype to co...
def is_datetime64_ns_dtype(arr_or_dtype): """ Check whether the provided array or dtype is of the datetime64[ns] dtype. Parameters ---------- arr_or_dtype : array-like The array or dtype to check. Returns ------- boolean Whether or not the array or dtype is of the datet...
def is_numeric_v_string_like(a, b): """ Check if we are comparing a string-like object to a numeric ndarray. NumPy doesn't like to compare such objects, especially numeric arrays and scalar string-likes. Parameters ---------- a : array-like, scalar The first object to check. b ...
def is_datetimelike_v_numeric(a, b): """ Check if we are comparing a datetime-like object to a numeric object. By "numeric," we mean an object that is either of an int or float dtype. Parameters ---------- a : array-like, scalar The first object to check. b : array-like, scalar ...
def is_datetimelike_v_object(a, b): """ Check if we are comparing a datetime-like object to an object instance. Parameters ---------- a : array-like, scalar The first object to check. b : array-like, scalar The second object to check. Returns ------- boolean ...
def needs_i8_conversion(arr_or_dtype): """ Check whether the array or dtype should be converted to int64. An array-like or dtype "needs" such a conversion if the array-like or dtype is of a datetime-like dtype Parameters ---------- arr_or_dtype : array-like The array or dtype to ch...
def is_bool_dtype(arr_or_dtype): """ Check whether the provided array or dtype is of a boolean dtype. Parameters ---------- arr_or_dtype : array-like The array or dtype to check. Returns ------- boolean Whether or not the array or dtype is of a boolean dtype. Notes...
def is_extension_type(arr): """ Check whether an array-like is of a pandas extension class instance. Extension classes include categoricals, pandas sparse objects (i.e. classes represented within the pandas library and not ones external to it like scipy sparse matrices), and datetime-like arrays. ...
def is_extension_array_dtype(arr_or_dtype): """ Check if an object is a pandas extension array type. See the :ref:`Use Guide <extending.extension-types>` for more. Parameters ---------- arr_or_dtype : object For array-like input, the ``.dtype`` attribute will be extracted. ...
def _is_dtype(arr_or_dtype, condition): """ Return a boolean if the condition is satisfied for the arr_or_dtype. Parameters ---------- arr_or_dtype : array-like, str, np.dtype, or ExtensionArrayType The array-like or dtype object whose dtype we want to extract. condition : callable[Unio...
def _get_dtype(arr_or_dtype): """ Get the dtype instance associated with an array or dtype object. Parameters ---------- arr_or_dtype : array-like The array-like or dtype object whose dtype we want to extract. Returns ------- obj_dtype : The extract dtype instance from the ...
def _is_dtype_type(arr_or_dtype, condition): """ Return a boolean if the condition is satisfied for the arr_or_dtype. Parameters ---------- arr_or_dtype : array-like The array-like or dtype object whose dtype we want to extract. condition : callable[Union[np.dtype, ExtensionDtypeType]] ...
def infer_dtype_from_object(dtype): """ Get a numpy dtype.type-style object for a dtype object. This methods also includes handling of the datetime64[ns] and datetime64[ns, TZ] objects. If no dtype can be found, we return ``object``. Parameters ---------- dtype : dtype, type T...
def _validate_date_like_dtype(dtype): """ Check whether the dtype is a date-like dtype. Raises an error if invalid. Parameters ---------- dtype : dtype, type The dtype to check. Raises ------ TypeError : The dtype could not be casted to a date-like dtype. ValueError : The d...
def pandas_dtype(dtype): """ Convert input into a pandas only dtype object or a numpy dtype object. Parameters ---------- dtype : object to be converted Returns ------- np.dtype or a pandas dtype Raises ------ TypeError if not a dtype """ # short-circuit if isi...
def _groupby_and_merge(by, on, left, right, _merge_pieces, check_duplicates=True): """ groupby & merge; we are always performing a left-by type operation Parameters ---------- by: field to group on: duplicates field left: left frame right: right frame _merge_p...
def merge_ordered(left, right, on=None, left_on=None, right_on=None, left_by=None, right_by=None, fill_method=None, suffixes=('_x', '_y'), how='outer'): """Perform merge with optional filling/interpolation designed for ordered data like tim...
def merge_asof(left, right, on=None, left_on=None, right_on=None, left_index=False, right_index=False, by=None, left_by=None, right_by=None, suffixes=('_x', '_y'), tolerance=None, allow_exact_matches=True, direction...
def _restore_dropped_levels_multijoin(left, right, dropped_level_names, join_index, lindexer, rindexer): """ this is an internal non-public method Returns the levels, labels and names of a multi-index to multi-index join. Depending on the type of join, this metho...
def _maybe_restore_index_levels(self, result): """ Restore index levels specified as `on` parameters Here we check for cases where `self.left_on` and `self.right_on` pairs each reference an index level in their respective DataFrames. The joined columns corresponding to these pai...
def _get_join_indexers(self): """ return the join indexers """ return _get_join_indexers(self.left_join_keys, self.right_join_keys, sort=self.sort, how=self.how)
def _create_join_index(self, index, other_index, indexer, other_indexer, how='left'): """ Create a join index by rearranging one index to match another Parameters ---------- index: Index being rearranged other_index: Index used to supply values...
def _get_merge_keys(self): """ Note: has side effects (copy/delete key columns) Parameters ---------- left right on Returns ------- left_keys, right_keys """ left_keys = [] right_keys = [] join_names = [] ...
def _get_join_indexers(self): """ return the join indexers """ def flip(xs): """ unlike np.transpose, this returns an array of tuples """ labels = list(string.ascii_lowercase[:len(xs)]) dtypes = [x.dtype for x in xs] labeled_dtypes = list(zip(labels, dtyp...
def is_dtype(cls, dtype): """Check if we match 'dtype'. Parameters ---------- dtype : object The object to check. Returns ------- is_dtype : bool Notes ----- The default implementation is True if 1. ``cls.construct_f...
def cat_core(list_of_columns, sep): """ Auxiliary function for :meth:`str.cat` Parameters ---------- list_of_columns : list of numpy arrays List of arrays to be concatenated with sep; these arrays may not contain NaNs! sep : string The separator string for concatenating ...
def str_count(arr, pat, flags=0): """ Count occurrences of pattern in each string of the Series/Index. This function is used to count the number of times a particular regex pattern is repeated in each of the string elements of the :class:`~pandas.Series`. Parameters ---------- pat : st...
def str_contains(arr, pat, case=True, flags=0, na=np.nan, regex=True): """ Test if pattern or regex is contained within a string of a Series or Index. Return boolean Series or Index based on whether a given pattern or regex is contained within a string of a Series or Index. Parameters --------...
def str_startswith(arr, pat, na=np.nan): """ Test if the start of each string element matches a pattern. Equivalent to :meth:`str.startswith`. Parameters ---------- pat : str Character sequence. Regular expressions are not accepted. na : object, default NaN Object shown if ...
def str_endswith(arr, pat, na=np.nan): """ Test if the end of each string element matches a pattern. Equivalent to :meth:`str.endswith`. Parameters ---------- pat : str Character sequence. Regular expressions are not accepted. na : object, default NaN Object shown if elemen...
def str_replace(arr, pat, repl, n=-1, case=None, flags=0, regex=True): r""" Replace occurrences of pattern/regex in the Series/Index with some other string. Equivalent to :meth:`str.replace` or :func:`re.sub`. Parameters ---------- pat : str or compiled regex String can be a charact...
def str_repeat(arr, repeats): """ Duplicate each string in the Series or Index. Parameters ---------- repeats : int or sequence of int Same value for all (int) or different value per (sequence). Returns ------- Series or Index of object Series or Index of repeated strin...
def str_match(arr, pat, case=True, flags=0, na=np.nan): """ Determine if each string matches a regular expression. Parameters ---------- pat : str Character sequence or regular expression. case : bool, default True If True, case sensitive. flags : int, default 0 (no flags) ...
def _groups_or_na_fun(regex): """Used in both extract_noexpand and extract_frame""" if regex.groups == 0: raise ValueError("pattern contains no capture groups") empty_row = [np.nan] * regex.groups def f(x): if not isinstance(x, str): return empty_row m = regex.search...
def _str_extract_noexpand(arr, pat, flags=0): """ Find groups in each string in the Series using passed regular expression. This function is called from str_extract(expand=False), and can return Series, DataFrame, or Index. """ from pandas import DataFrame, Index regex = re.compile(pat...
def _str_extract_frame(arr, pat, flags=0): """ For each subject string in the Series, extract groups from the first match of regular expression pat. This function is called from str_extract(expand=True), and always returns a DataFrame. """ from pandas import DataFrame regex = re.compile(pa...
def str_extract(arr, pat, flags=0, expand=True): r""" Extract capture groups in the regex `pat` as columns in a DataFrame. For each subject string in the Series, extract groups from the first match of regular expression `pat`. Parameters ---------- pat : str Regular expression patt...
def str_extractall(arr, pat, flags=0): r""" For each subject string in the Series, extract groups from all matches of regular expression pat. When each subject string in the Series has exactly one match, extractall(pat).xs(0, level='match') is the same as extract(pat). .. versionadded:: 0.18.0 ...
def str_get_dummies(arr, sep='\|'): """ Split each string in the Series by sep and return a DataFrame of dummy/indicator variables. Parameters ---------- sep : str, default "\|" String to split on. Returns ------- DataFrame Dummy variables corresponding to values of t...
def str_findall(arr, pat, flags=0): """ Find all occurrences of pattern or regular expression in the Series/Index. Equivalent to applying :func:`re.findall` to all the elements in the Series/Index. Parameters ---------- pat : str Pattern or regular expression. flags : int, defa...
def str_find(arr, sub, start=0, end=None, side='left'): """ Return indexes in each strings in the Series/Index where the substring is fully contained between [start:end]. Return -1 on failure. Parameters ---------- sub : str Substring being searched. start : int Left edge in...
def str_pad(arr, width, side='left', fillchar=' '): """ Pad strings in the Series/Index up to width. Parameters ---------- width : int Minimum width of resulting string; additional characters will be filled with character defined in `fillchar`. side : {'left', 'right', 'both'}, ...
def str_slice(arr, start=None, stop=None, step=None): """ Slice substrings from each element in the Series or Index. Parameters ---------- start : int, optional Start position for slice operation. stop : int, optional Stop position for slice operation. step : int, optional ...
def str_slice_replace(arr, start=None, stop=None, repl=None): """ Replace a positional slice of a string with another value. Parameters ---------- start : int, optional Left index position to use for the slice. If not specified (None), the slice is unbounded on the left, i.e. slice ...
def str_strip(arr, to_strip=None, side='both'): """ Strip whitespace (including newlines) from each string in the Series/Index. Parameters ---------- to_strip : str or unicode side : {'left', 'right', 'both'}, default 'both' Returns ------- Series or Index """ if side =...
def str_wrap(arr, width, **kwargs): r""" Wrap long strings in the Series/Index to be formatted in paragraphs with length less than a given width. This method has the same keyword parameters and defaults as :class:`textwrap.TextWrapper`. Parameters ---------- width : int Maximum...
def str_get(arr, i): """ Extract element from each component at specified position. Extract element from lists, tuples, or strings in each element in the Series/Index. Parameters ---------- i : int Position of element to extract. Returns ------- Series or Index Ex...
def str_decode(arr, encoding, errors="strict"): """ Decode character string in the Series/Index using indicated encoding. Equivalent to :meth:`str.decode` in python2 and :meth:`bytes.decode` in python3. Parameters ---------- encoding : str errors : str, optional Returns -------...
def str_encode(arr, encoding, errors="strict"): """ Encode character string in the Series/Index using indicated encoding. Equivalent to :meth:`str.encode`. Parameters ---------- encoding : str errors : str, optional Returns ------- encoded : Series/Index of objects """ ...
def copy(source): "Copy a docstring from another source function (if present)" def do_copy(target): if source.__doc__: target.__doc__ = source.__doc__ return target return do_copy
def _get_series_list(self, others, ignore_index=False): """ Auxiliary function for :meth:`str.cat`. Turn potentially mixed input into a list of Series (elements without an index must match the length of the calling Series/Index). Parameters ---------- others : Se...
def cat(self, others=None, sep=None, na_rep=None, join=None): """ Concatenate strings in the Series/Index with given separator. If `others` is specified, this function concatenates the Series/Index and elements of `others` element-wise. If `others` is not passed, then all values...
def zfill(self, width): """ Pad strings in the Series/Index by prepending '0' characters. Strings in the Series/Index are padded with '0' characters on the left of the string to reach a total string length `width`. Strings in the Series/Index with length greater or equal to `wi...
def normalize(self, form): """ Return the Unicode normal form for the strings in the Series/Index. For more information on the forms, see the :func:`unicodedata.normalize`. Parameters ---------- form : {'NFC', 'NFKC', 'NFD', 'NFKD'} Unicode form ...
def get_sys_info(): "Returns system information as a dict" blob = [] # get full commit hash commit = None if os.path.isdir(".git") and os.path.isdir("pandas"): try: pipe = subprocess.Popen('git log --format="%H" -n 1'.split(" "), stdout=subpr...
def whitelist_method_generator(base, klass, whitelist): """ Yields all GroupBy member defs for DataFrame/Series names in whitelist. Parameters ---------- base : class base class klass : class class where members are defined. Should be Series or DataFrame whitelist : ...
def _dispatch(name, args, kwargs): """ Dispatch to apply. """ def outer(self, args, *kwargs): def f(x): x = self._shallow_copy(x, groupby=self._groupby) return getattr(x, name)(args, **kwargs) return self._groupby.apply(f) ...
def _gotitem(self, key, ndim, subset=None): """ Sub-classes to define. Return a sliced object. Parameters ---------- key : string / list of selections ndim : 1,2 requested ndim of result subset : object, default None subset to act on ...
def to_str(s): """ Convert bytes and non-string into Python 3 str """ if isinstance(s, bytes): s = s.decode('utf-8') elif not isinstance(s, str): s = str(s) return s
def set_function_name(f, name, cls): """ Bind the name/qualname attributes of the function """ f.__name__ = name f.__qualname__ = '{klass}.{name}'.format( klass=cls.__name__, name=name) f.__module__ = cls.__module__ return f
def raise_with_traceback(exc, traceback=Ellipsis): """ Raise exception with existing traceback. If traceback is not passed, uses sys.exc_info() to get traceback. """ if traceback == Ellipsis: _, _, traceback = sys.exc_info() raise exc.with_traceback(traceback)
def _convert_to_style(cls, style_dict): """ converts a style_dict to an openpyxl style object Parameters ---------- style_dict : style dictionary to convert """ from openpyxl.style import Style xls_style = Style() for key, value in style_dict.item...
def _convert_to_style_kwargs(cls, style_dict): """ Convert a style_dict to a set of kwargs suitable for initializing or updating-on-copy an openpyxl v2 style object Parameters ---------- style_dict : dict A dict with zero or more of the following keys (or thei...
def _convert_to_color(cls, color_spec): """ Convert ``color_spec`` to an openpyxl v2 Color object Parameters ---------- color_spec : str, dict A 32-bit ARGB hex string, or a dict with zero or more of the following keys. 'rgb' ...
def _convert_to_font(cls, font_dict): """ Convert ``font_dict`` to an openpyxl v2 Font object Parameters ---------- font_dict : dict A dict with zero or more of the following keys (or their synonyms). 'name' 'size' ('sz') ...
def _convert_to_fill(cls, fill_dict): """ Convert ``fill_dict`` to an openpyxl v2 Fill object Parameters ---------- fill_dict : dict A dict with one or more of the following keys (or their synonyms), 'fill_type' ('patternType', 'patterntype') ...
def _convert_to_side(cls, side_spec): """ Convert ``side_spec`` to an openpyxl v2 Side object Parameters ---------- side_spec : str, dict A string specifying the border style, or a dict with zero or more of the following keys (or their synonyms). ...
def _convert_to_border(cls, border_dict): """ Convert ``border_dict`` to an openpyxl v2 Border object Parameters ---------- border_dict : dict A dict with zero or more of the following keys (or their synonyms). 'left' 'right' ...
def frame_apply(obj, func, axis=0, broadcast=None, raw=False, reduce=None, result_type=None, ignore_failures=False, args=None, kwds=None): """ construct and return a row or column based frame apply object """ axis = obj._get_axis_number(axis) if axis == 0: ...
def get_result(self): """ compute the results """ # dispatch to agg if is_list_like(self.f) or is_dict_like(self.f): return self.obj.aggregate(self.f, axis=self.axis, self.args, *self.kwds) # all empty if len(self.columns) == ...
def apply_empty_result(self): """ we have an empty result; at least 1 axis is 0 we will try to apply the function to an empty series in order to see if this is a reduction function """ # we are not asked to reduce or infer reduction # so just return a copy of th...
def apply_raw(self): """ apply to the values as a numpy array """ try: result = reduction.reduce(self.values, self.f, axis=self.axis) except Exception: result = np.apply_along_axis(self.f, self.axis, self.values) # TODO: mixed type case if result.ndim ==...
def wrap_results_for_axis(self): """ return the results for the rows """ results = self.results result = self.obj._constructor(data=results) if not isinstance(results[0], ABCSeries): try: result.index = self.res_columns except ValueError: ...
def wrap_results_for_axis(self): """ return the results for the columns """ results = self.results # we have requested to expand if self.result_type == 'expand': result = self.infer_to_same_shape() # we have a non-series and don't want inference elif not isi...
def infer_to_same_shape(self): """ infer the results to the same shape as the input object """ results = self.results result = self.obj._constructor(data=results) result = result.T # set the index result.index = self.res_index # infer dtypes result = re...
def cartesian_product(X): """ Numpy version of itertools.product. Sometimes faster (for large inputs)... Parameters ---------- X : list-like of list-likes Returns ------- product : list of ndarrays Examples -------- >>> cartesian_product([list('ABC'), [1, 2]]) [arr...
def _strip_schema(url): """Returns the url without the s3:// part""" result = parse_url(url, allow_fragments=False) return result.netloc + result.path
def xception(c, k=8, n_middle=8): "Preview version of Xception network. Not tested yet - use at own risk. No pretrained model yet." layers = [ conv(3, k4, 3, 2), conv(k4, k8, 3), ConvSkip(k8, k16, act=False), ConvSkip(k16, k32), ConvSkip(k32, k*91), ] for ...
def get_model(self, opt_fn, emb_sz, n_hid, n_layers, **kwargs): """ Method returns a RNN_Learner object, that wraps an instance of the RNN_Encoder module. Args: opt_fn (Optimizer): the torch optimizer function to use emb_sz (int): embedding size n_hid (int): number o...
def from_text_files(cls, path, field, train, validation, test=None, bs=64, bptt=70, **kwargs): """ Method used to instantiate a LanguageModelData object that can be used for a supported nlp task. Args: path (str): the absolute path in which temporary model data will be saved ...
def get_files(path:PathOrStr, extensions:Collection[str]=None, recurse:bool=False, include:Optional[Collection[str]]=None)->FilePathList: "Return list of files in `path` that have a suffix in `extensions`; optionally `recurse`." if recurse: res = [] for i,(p,d,f) in enumerate(os.wa...
def _databunch_load_empty(cls, path, fname:str='export.pkl'): "Load an empty `DataBunch` from the exported file in `path/fname` with optional `tfms`." sd = LabelLists.load_empty(path, fn=fname) return sd.databunch()

def _generate_range_overflow_safe_signed(endpoint, periods, stride, side): """ A special case for _generate_range_overflow_safe where `periods * stride` can be calculated without overflowing int64 bounds. """ assert side in ['start', 'end'] if side == 'end': stride *= -1 with np.err...

def set_locale(new_locale, lc_var=locale.LC_ALL): """ Context manager for temporarily setting a locale. Parameters ---------- new_locale : str or tuple A string of the form <language_country>.<encoding>. For example to set the current locale to US English with a UTF8 encoding, you w...

def can_set_locale(lc, lc_var=locale.LC_ALL): """ Check to see if we can set a locale, and subsequently get the locale, without raising an Exception. Parameters ---------- lc : str The locale to attempt to set. lc_var : int, default `locale.LC_ALL` The category of the locale...

def _valid_locales(locales, normalize): """ Return a list of normalized locales that do not throw an ``Exception`` when set. Parameters ---------- locales : str A string where each locale is separated by a newline. normalize : bool Whether to call ``locale.normalize`` on eac...

def get_locales(prefix=None, normalize=True, locale_getter=_default_locale_getter): """ Get all the locales that are available on the system. Parameters ---------- prefix : str If not ``None`` then return only those locales with the prefix provided. For example to ge...

def ensure_float(arr): """ Ensure that an array object has a float dtype if possible. Parameters ---------- arr : array-like The array whose data type we want to enforce as float. Returns ------- float_arr : The original array cast to the float dtype if possible...

def ensure_categorical(arr): """ Ensure that an array-like object is a Categorical (if not already). Parameters ---------- arr : array-like The array that we want to convert into a Categorical. Returns ------- cat_arr : The original array cast as a Categorical. If it already ...

def ensure_int64_or_float64(arr, copy=False): """ Ensure that an dtype array of some integer dtype has an int64 dtype if possible If it's not possible, potentially because of overflow, convert the array to float64 instead. Parameters ---------- arr : array-like The array whose...

def classes_and_not_datetimelike(*klasses): """ evaluate if the tipo is a subclass of the klasses and not a datetimelike """ return lambda tipo: (issubclass(tipo, klasses) and not issubclass(tipo, (np.datetime64, np.timedelta64)))

def is_sparse(arr): """ Check whether an array-like is a 1-D pandas sparse array. Check that the one-dimensional array-like is a pandas sparse array. Returns True if it is a pandas sparse array, not another type of sparse array. Parameters ---------- arr : array-like Array-like...

def is_scipy_sparse(arr): """ Check whether an array-like is a scipy.sparse.spmatrix instance. Parameters ---------- arr : array-like The array-like to check. Returns ------- boolean Whether or not the array-like is a scipy.sparse.spmatrix instance. Notes -----...

def is_offsetlike(arr_or_obj): """ Check if obj or all elements of list-like is DateOffset Parameters ---------- arr_or_obj : object Returns ------- boolean Whether the object is a DateOffset or listlike of DatetOffsets Examples -------- >>> is_offsetlike(pd.DateOf...

def is_period(arr): """ Check whether an array-like is a periodical index. .. deprecated:: 0.24.0 Parameters ---------- arr : array-like The array-like to check. Returns ------- boolean Whether or not the array-like is a periodical index. Examples --------...

def is_string_dtype(arr_or_dtype): """ Check whether the provided array or dtype is of the string dtype. Parameters ---------- arr_or_dtype : array-like The array or dtype to check. Returns ------- boolean Whether or not the array or dtype is of the string dtype. E...

def is_period_arraylike(arr): """ Check whether an array-like is a periodical array-like or PeriodIndex. Parameters ---------- arr : array-like The array-like to check. Returns ------- boolean Whether or not the array-like is a periodical array-like or PeriodInd...

def is_datetime_arraylike(arr): """ Check whether an array-like is a datetime array-like or DatetimeIndex. Parameters ---------- arr : array-like The array-like to check. Returns ------- boolean Whether or not the array-like is a datetime array-like or DatetimeI...

def is_datetimelike(arr): """ Check whether an array-like is a datetime-like array-like. Acceptable datetime-like objects are (but not limited to) datetime indices, periodic indices, and timedelta indices. Parameters ---------- arr : array-like The array-like to check. Returns...

def is_dtype_equal(source, target): """ Check if two dtypes are equal. Parameters ---------- source : The first dtype to compare target : The second dtype to compare Returns ---------- boolean Whether or not the two dtypes are equal. Examples -------- >>> is_dt...

def is_dtype_union_equal(source, target): """ Check whether two arrays have compatible dtypes to do a union. numpy types are checked with ``is_dtype_equal``. Extension types are checked separately. Parameters ---------- source : The first dtype to compare target : The second dtype to co...

def is_datetime64_ns_dtype(arr_or_dtype): """ Check whether the provided array or dtype is of the datetime64[ns] dtype. Parameters ---------- arr_or_dtype : array-like The array or dtype to check. Returns ------- boolean Whether or not the array or dtype is of the datet...

def is_numeric_v_string_like(a, b): """ Check if we are comparing a string-like object to a numeric ndarray. NumPy doesn't like to compare such objects, especially numeric arrays and scalar string-likes. Parameters ---------- a : array-like, scalar The first object to check. b ...

def is_datetimelike_v_numeric(a, b): """ Check if we are comparing a datetime-like object to a numeric object. By "numeric," we mean an object that is either of an int or float dtype. Parameters ---------- a : array-like, scalar The first object to check. b : array-like, scalar ...

def is_datetimelike_v_object(a, b): """ Check if we are comparing a datetime-like object to an object instance. Parameters ---------- a : array-like, scalar The first object to check. b : array-like, scalar The second object to check. Returns ------- boolean ...

def needs_i8_conversion(arr_or_dtype): """ Check whether the array or dtype should be converted to int64. An array-like or dtype "needs" such a conversion if the array-like or dtype is of a datetime-like dtype Parameters ---------- arr_or_dtype : array-like The array or dtype to ch...

def is_bool_dtype(arr_or_dtype): """ Check whether the provided array or dtype is of a boolean dtype. Parameters ---------- arr_or_dtype : array-like The array or dtype to check. Returns ------- boolean Whether or not the array or dtype is of a boolean dtype. Notes...

def is_extension_type(arr): """ Check whether an array-like is of a pandas extension class instance. Extension classes include categoricals, pandas sparse objects (i.e. classes represented within the pandas library and not ones external to it like scipy sparse matrices), and datetime-like arrays. ...

def is_extension_array_dtype(arr_or_dtype): """ Check if an object is a pandas extension array type. See the :ref:`Use Guide <extending.extension-types>` for more. Parameters ---------- arr_or_dtype : object For array-like input, the ``.dtype`` attribute will be extracted. ...

def _is_dtype(arr_or_dtype, condition): """ Return a boolean if the condition is satisfied for the arr_or_dtype. Parameters ---------- arr_or_dtype : array-like, str, np.dtype, or ExtensionArrayType The array-like or dtype object whose dtype we want to extract. condition : callable[Unio...

def _get_dtype(arr_or_dtype): """ Get the dtype instance associated with an array or dtype object. Parameters ---------- arr_or_dtype : array-like The array-like or dtype object whose dtype we want to extract. Returns ------- obj_dtype : The extract dtype instance from the ...

def _is_dtype_type(arr_or_dtype, condition): """ Return a boolean if the condition is satisfied for the arr_or_dtype. Parameters ---------- arr_or_dtype : array-like The array-like or dtype object whose dtype we want to extract. condition : callable[Union[np.dtype, ExtensionDtypeType]] ...

def infer_dtype_from_object(dtype): """ Get a numpy dtype.type-style object for a dtype object. This methods also includes handling of the datetime64[ns] and datetime64[ns, TZ] objects. If no dtype can be found, we return ``object``. Parameters ---------- dtype : dtype, type T...

def _validate_date_like_dtype(dtype): """ Check whether the dtype is a date-like dtype. Raises an error if invalid. Parameters ---------- dtype : dtype, type The dtype to check. Raises ------ TypeError : The dtype could not be casted to a date-like dtype. ValueError : The d...

def pandas_dtype(dtype): """ Convert input into a pandas only dtype object or a numpy dtype object. Parameters ---------- dtype : object to be converted Returns ------- np.dtype or a pandas dtype Raises ------ TypeError if not a dtype """ # short-circuit if isi...

def _groupby_and_merge(by, on, left, right, _merge_pieces, check_duplicates=True): """ groupby & merge; we are always performing a left-by type operation Parameters ---------- by: field to group on: duplicates field left: left frame right: right frame _merge_p...

def merge_ordered(left, right, on=None, left_on=None, right_on=None, left_by=None, right_by=None, fill_method=None, suffixes=('_x', '_y'), how='outer'): """Perform merge with optional filling/interpolation designed for ordered data like tim...

def merge_asof(left, right, on=None, left_on=None, right_on=None, left_index=False, right_index=False, by=None, left_by=None, right_by=None, suffixes=('_x', '_y'), tolerance=None, allow_exact_matches=True, direction...

def _restore_dropped_levels_multijoin(left, right, dropped_level_names, join_index, lindexer, rindexer): """ *this is an internal non-public method* Returns the levels, labels and names of a multi-index to multi-index join. Depending on the type of join, this metho...

def _maybe_restore_index_levels(self, result): """ Restore index levels specified as `on` parameters Here we check for cases where `self.left_on` and `self.right_on` pairs each reference an index level in their respective DataFrames. The joined columns corresponding to these pai...

def _get_join_indexers(self): """ return the join indexers """ return _get_join_indexers(self.left_join_keys, self.right_join_keys, sort=self.sort, how=self.how)

def _create_join_index(self, index, other_index, indexer, other_indexer, how='left'): """ Create a join index by rearranging one index to match another Parameters ---------- index: Index being rearranged other_index: Index used to supply values...

def _get_merge_keys(self): """ Note: has side effects (copy/delete key columns) Parameters ---------- left right on Returns ------- left_keys, right_keys """ left_keys = [] right_keys = [] join_names = [] ...

def _get_join_indexers(self): """ return the join indexers """ def flip(xs): """ unlike np.transpose, this returns an array of tuples """ labels = list(string.ascii_lowercase[:len(xs)]) dtypes = [x.dtype for x in xs] labeled_dtypes = list(zip(labels, dtyp...

def is_dtype(cls, dtype): """Check if we match 'dtype'. Parameters ---------- dtype : object The object to check. Returns ------- is_dtype : bool Notes ----- The default implementation is True if 1. ``cls.construct_f...

def cat_core(list_of_columns, sep): """ Auxiliary function for :meth:`str.cat` Parameters ---------- list_of_columns : list of numpy arrays List of arrays to be concatenated with sep; these arrays may not contain NaNs! sep : string The separator string for concatenating ...

def str_count(arr, pat, flags=0): """ Count occurrences of pattern in each string of the Series/Index. This function is used to count the number of times a particular regex pattern is repeated in each of the string elements of the :class:`~pandas.Series`. Parameters ---------- pat : st...

def str_contains(arr, pat, case=True, flags=0, na=np.nan, regex=True): """ Test if pattern or regex is contained within a string of a Series or Index. Return boolean Series or Index based on whether a given pattern or regex is contained within a string of a Series or Index. Parameters --------...

def str_startswith(arr, pat, na=np.nan): """ Test if the start of each string element matches a pattern. Equivalent to :meth:`str.startswith`. Parameters ---------- pat : str Character sequence. Regular expressions are not accepted. na : object, default NaN Object shown if ...

def str_endswith(arr, pat, na=np.nan): """ Test if the end of each string element matches a pattern. Equivalent to :meth:`str.endswith`. Parameters ---------- pat : str Character sequence. Regular expressions are not accepted. na : object, default NaN Object shown if elemen...

def str_replace(arr, pat, repl, n=-1, case=None, flags=0, regex=True): r""" Replace occurrences of pattern/regex in the Series/Index with some other string. Equivalent to :meth:`str.replace` or :func:`re.sub`. Parameters ---------- pat : str or compiled regex String can be a charact...

def str_repeat(arr, repeats): """ Duplicate each string in the Series or Index. Parameters ---------- repeats : int or sequence of int Same value for all (int) or different value per (sequence). Returns ------- Series or Index of object Series or Index of repeated strin...

def str_match(arr, pat, case=True, flags=0, na=np.nan): """ Determine if each string matches a regular expression. Parameters ---------- pat : str Character sequence or regular expression. case : bool, default True If True, case sensitive. flags : int, default 0 (no flags) ...

def _groups_or_na_fun(regex): """Used in both extract_noexpand and extract_frame""" if regex.groups == 0: raise ValueError("pattern contains no capture groups") empty_row = [np.nan] * regex.groups def f(x): if not isinstance(x, str): return empty_row m = regex.search...

def _str_extract_noexpand(arr, pat, flags=0): """ Find groups in each string in the Series using passed regular expression. This function is called from str_extract(expand=False), and can return Series, DataFrame, or Index. """ from pandas import DataFrame, Index regex = re.compile(pat...

def _str_extract_frame(arr, pat, flags=0): """ For each subject string in the Series, extract groups from the first match of regular expression pat. This function is called from str_extract(expand=True), and always returns a DataFrame. """ from pandas import DataFrame regex = re.compile(pa...

def str_extract(arr, pat, flags=0, expand=True): r""" Extract capture groups in the regex `pat` as columns in a DataFrame. For each subject string in the Series, extract groups from the first match of regular expression `pat`. Parameters ---------- pat : str Regular expression patt...

def str_extractall(arr, pat, flags=0): r""" For each subject string in the Series, extract groups from all matches of regular expression pat. When each subject string in the Series has exactly one match, extractall(pat).xs(0, level='match') is the same as extract(pat). .. versionadded:: 0.18.0 ...

def str_get_dummies(arr, sep='|'): """ Split each string in the Series by sep and return a DataFrame of dummy/indicator variables. Parameters ---------- sep : str, default "|" String to split on. Returns ------- DataFrame Dummy variables corresponding to values of t...

def str_findall(arr, pat, flags=0): """ Find all occurrences of pattern or regular expression in the Series/Index. Equivalent to applying :func:`re.findall` to all the elements in the Series/Index. Parameters ---------- pat : str Pattern or regular expression. flags : int, defa...

def str_find(arr, sub, start=0, end=None, side='left'): """ Return indexes in each strings in the Series/Index where the substring is fully contained between [start:end]. Return -1 on failure. Parameters ---------- sub : str Substring being searched. start : int Left edge in...

def str_pad(arr, width, side='left', fillchar=' '): """ Pad strings in the Series/Index up to width. Parameters ---------- width : int Minimum width of resulting string; additional characters will be filled with character defined in `fillchar`. side : {'left', 'right', 'both'}, ...

def str_slice(arr, start=None, stop=None, step=None): """ Slice substrings from each element in the Series or Index. Parameters ---------- start : int, optional Start position for slice operation. stop : int, optional Stop position for slice operation. step : int, optional ...

def str_slice_replace(arr, start=None, stop=None, repl=None): """ Replace a positional slice of a string with another value. Parameters ---------- start : int, optional Left index position to use for the slice. If not specified (None), the slice is unbounded on the left, i.e. slice ...

def str_strip(arr, to_strip=None, side='both'): """ Strip whitespace (including newlines) from each string in the Series/Index. Parameters ---------- to_strip : str or unicode side : {'left', 'right', 'both'}, default 'both' Returns ------- Series or Index """ if side =...

def str_wrap(arr, width, **kwargs): r""" Wrap long strings in the Series/Index to be formatted in paragraphs with length less than a given width. This method has the same keyword parameters and defaults as :class:`textwrap.TextWrapper`. Parameters ---------- width : int Maximum...

def str_get(arr, i): """ Extract element from each component at specified position. Extract element from lists, tuples, or strings in each element in the Series/Index. Parameters ---------- i : int Position of element to extract. Returns ------- Series or Index Ex...

def str_decode(arr, encoding, errors="strict"): """ Decode character string in the Series/Index using indicated encoding. Equivalent to :meth:`str.decode` in python2 and :meth:`bytes.decode` in python3. Parameters ---------- encoding : str errors : str, optional Returns -------...

def str_encode(arr, encoding, errors="strict"): """ Encode character string in the Series/Index using indicated encoding. Equivalent to :meth:`str.encode`. Parameters ---------- encoding : str errors : str, optional Returns ------- encoded : Series/Index of objects """ ...

def copy(source): "Copy a docstring from another source function (if present)" def do_copy(target): if source.__doc__: target.__doc__ = source.__doc__ return target return do_copy

def _get_series_list(self, others, ignore_index=False): """ Auxiliary function for :meth:`str.cat`. Turn potentially mixed input into a list of Series (elements without an index must match the length of the calling Series/Index). Parameters ---------- others : Se...

def cat(self, others=None, sep=None, na_rep=None, join=None): """ Concatenate strings in the Series/Index with given separator. If `others` is specified, this function concatenates the Series/Index and elements of `others` element-wise. If `others` is not passed, then all values...

def zfill(self, width): """ Pad strings in the Series/Index by prepending '0' characters. Strings in the Series/Index are padded with '0' characters on the left of the string to reach a total string length `width`. Strings in the Series/Index with length greater or equal to `wi...

def normalize(self, form): """ Return the Unicode normal form for the strings in the Series/Index. For more information on the forms, see the :func:`unicodedata.normalize`. Parameters ---------- form : {'NFC', 'NFKC', 'NFD', 'NFKD'} Unicode form ...

def get_sys_info(): "Returns system information as a dict" blob = [] # get full commit hash commit = None if os.path.isdir(".git") and os.path.isdir("pandas"): try: pipe = subprocess.Popen('git log --format="%H" -n 1'.split(" "), stdout=subpr...

def whitelist_method_generator(base, klass, whitelist): """ Yields all GroupBy member defs for DataFrame/Series names in whitelist. Parameters ---------- base : class base class klass : class class where members are defined. Should be Series or DataFrame whitelist : ...

def _dispatch(name, *args, **kwargs): """ Dispatch to apply. """ def outer(self, *args, **kwargs): def f(x): x = self._shallow_copy(x, groupby=self._groupby) return getattr(x, name)(*args, **kwargs) return self._groupby.apply(f) ...

def _gotitem(self, key, ndim, subset=None): """ Sub-classes to define. Return a sliced object. Parameters ---------- key : string / list of selections ndim : 1,2 requested ndim of result subset : object, default None subset to act on ...

def to_str(s): """ Convert bytes and non-string into Python 3 str """ if isinstance(s, bytes): s = s.decode('utf-8') elif not isinstance(s, str): s = str(s) return s

def set_function_name(f, name, cls): """ Bind the name/qualname attributes of the function """ f.__name__ = name f.__qualname__ = '{klass}.{name}'.format( klass=cls.__name__, name=name) f.__module__ = cls.__module__ return f

def raise_with_traceback(exc, traceback=Ellipsis): """ Raise exception with existing traceback. If traceback is not passed, uses sys.exc_info() to get traceback. """ if traceback == Ellipsis: _, _, traceback = sys.exc_info() raise exc.with_traceback(traceback)

def _convert_to_style(cls, style_dict): """ converts a style_dict to an openpyxl style object Parameters ---------- style_dict : style dictionary to convert """ from openpyxl.style import Style xls_style = Style() for key, value in style_dict.item...

def _convert_to_style_kwargs(cls, style_dict): """ Convert a style_dict to a set of kwargs suitable for initializing or updating-on-copy an openpyxl v2 style object Parameters ---------- style_dict : dict A dict with zero or more of the following keys (or thei...

def _convert_to_color(cls, color_spec): """ Convert ``color_spec`` to an openpyxl v2 Color object Parameters ---------- color_spec : str, dict A 32-bit ARGB hex string, or a dict with zero or more of the following keys. 'rgb' ...

def _convert_to_font(cls, font_dict): """ Convert ``font_dict`` to an openpyxl v2 Font object Parameters ---------- font_dict : dict A dict with zero or more of the following keys (or their synonyms). 'name' 'size' ('sz') ...

def _convert_to_fill(cls, fill_dict): """ Convert ``fill_dict`` to an openpyxl v2 Fill object Parameters ---------- fill_dict : dict A dict with one or more of the following keys (or their synonyms), 'fill_type' ('patternType', 'patterntype') ...

def _convert_to_side(cls, side_spec): """ Convert ``side_spec`` to an openpyxl v2 Side object Parameters ---------- side_spec : str, dict A string specifying the border style, or a dict with zero or more of the following keys (or their synonyms). ...

def _convert_to_border(cls, border_dict): """ Convert ``border_dict`` to an openpyxl v2 Border object Parameters ---------- border_dict : dict A dict with zero or more of the following keys (or their synonyms). 'left' 'right' ...

def frame_apply(obj, func, axis=0, broadcast=None, raw=False, reduce=None, result_type=None, ignore_failures=False, args=None, kwds=None): """ construct and return a row or column based frame apply object """ axis = obj._get_axis_number(axis) if axis == 0: ...

def get_result(self): """ compute the results """ # dispatch to agg if is_list_like(self.f) or is_dict_like(self.f): return self.obj.aggregate(self.f, axis=self.axis, *self.args, **self.kwds) # all empty if len(self.columns) == ...

def apply_empty_result(self): """ we have an empty result; at least 1 axis is 0 we will try to apply the function to an empty series in order to see if this is a reduction function """ # we are not asked to reduce or infer reduction # so just return a copy of th...

def apply_raw(self): """ apply to the values as a numpy array """ try: result = reduction.reduce(self.values, self.f, axis=self.axis) except Exception: result = np.apply_along_axis(self.f, self.axis, self.values) # TODO: mixed type case if result.ndim ==...

def wrap_results_for_axis(self): """ return the results for the rows """ results = self.results result = self.obj._constructor(data=results) if not isinstance(results[0], ABCSeries): try: result.index = self.res_columns except ValueError: ...

def wrap_results_for_axis(self): """ return the results for the columns """ results = self.results # we have requested to expand if self.result_type == 'expand': result = self.infer_to_same_shape() # we have a non-series and don't want inference elif not isi...

def infer_to_same_shape(self): """ infer the results to the same shape as the input object """ results = self.results result = self.obj._constructor(data=results) result = result.T # set the index result.index = self.res_index # infer dtypes result = re...

def cartesian_product(X): """ Numpy version of itertools.product. Sometimes faster (for large inputs)... Parameters ---------- X : list-like of list-likes Returns ------- product : list of ndarrays Examples -------- >>> cartesian_product([list('ABC'), [1, 2]]) [arr...

def _strip_schema(url): """Returns the url without the s3:// part""" result = parse_url(url, allow_fragments=False) return result.netloc + result.path

def xception(c, k=8, n_middle=8): "Preview version of Xception network. Not tested yet - use at own risk. No pretrained model yet." layers = [ conv(3, k*4, 3, 2), conv(k*4, k*8, 3), ConvSkip(k*8, k*16, act=False), ConvSkip(k*16, k*32), ConvSkip(k*32, k*91), ] for ...

def get_model(self, opt_fn, emb_sz, n_hid, n_layers, **kwargs): """ Method returns a RNN_Learner object, that wraps an instance of the RNN_Encoder module. Args: opt_fn (Optimizer): the torch optimizer function to use emb_sz (int): embedding size n_hid (int): number o...

def from_text_files(cls, path, field, train, validation, test=None, bs=64, bptt=70, **kwargs): """ Method used to instantiate a LanguageModelData object that can be used for a supported nlp task. Args: path (str): the absolute path in which temporary model data will be saved ...

def get_files(path:PathOrStr, extensions:Collection[str]=None, recurse:bool=False, include:Optional[Collection[str]]=None)->FilePathList: "Return list of files in `path` that have a suffix in `extensions`; optionally `recurse`." if recurse: res = [] for i,(p,d,f) in enumerate(os.wa...

def _databunch_load_empty(cls, path, fname:str='export.pkl'): "Load an empty `DataBunch` from the exported file in `path/fname` with optional `tfms`." sd = LabelLists.load_empty(path, fn=fname) return sd.databunch()