JorgeVB/code_unlearning_dataset · Datasets at Hugging Face

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Return the maximum value of the Index. Parameters ---------- axis : int, optional For compatibility with NumPy. Only 0 or None are allowed. skipna : bool, default True Returns ------- scalar Maximum value. See Also ------...
Return an ndarray of the maximum argument indexer. Parameters ---------- axis : {None} Dummy argument for consistency with Series skipna : bool, default True See Also -------- numpy.ndarray.argmax def argmax(self, axis=None, skipna=True): ""...
Return the minimum value of the Index. Parameters ---------- axis : {None} Dummy argument for consistency with Series skipna : bool, default True Returns ------- scalar Minimum value. See Also -------- Index.max :...
Return a ndarray of the minimum argument indexer. Parameters ---------- axis : {None} Dummy argument for consistency with Series skipna : bool, default True Returns ------- numpy.ndarray See Also -------- numpy.ndarray.argmin...
Return a list of the values. These are each a scalar type, which is a Python scalar (for str, int, float) or a pandas scalar (for Timestamp/Timedelta/Interval/Period) Returns ------- list See Also -------- numpy.ndarray.tolist def tolist(self):...
perform the reduction type operation if we can def _reduce(self, op, name, axis=0, skipna=True, numeric_only=None, filter_type=None, **kwds): """ perform the reduction type operation if we can """ func = getattr(self, name, None) if func is None: raise TypeError("{kl...
An internal function that maps values using the input correspondence (which can be a dict, Series, or function). Parameters ---------- mapper : function, dict, or Series The input correspondence object na_action : {None, 'ignore'} If 'ignore', propagate N...
Return a Series containing counts of unique values. The resulting object will be in descending order so that the first element is the most frequently-occurring element. Excludes NA values by default. Parameters ---------- normalize : boolean, default False I...
Return number of unique elements in the object. Excludes NA values by default. Parameters ---------- dropna : bool, default True Don't include NaN in the count. Returns ------- int See Also -------- DataFrame.nunique: Method...
Memory usage of the values Parameters ---------- deep : bool Introspect the data deeply, interrogate `object` dtypes for system-level memory consumption Returns ------- bytes used See Also -------- numpy.ndarray.nbytes ...
Return the argument with an initial component of ~ or ~user replaced by that user's home directory. Parameters ---------- filepath_or_buffer : object to be converted if possible Returns ------- expanded_filepath_or_buffer : an expanded filepath or the i...
Attempt to convert a path-like object to a string. Parameters ---------- filepath_or_buffer : object to be converted Returns ------- str_filepath_or_buffer : maybe a string version of the object Notes ----- Objects supporting the fspath protocol (python 3.6+) are coerced accor...
If the filepath_or_buffer is a url, translate and return the buffer. Otherwise passthrough. Parameters ---------- filepath_or_buffer : a url, filepath (str, py.path.local or pathlib.Path), or buffer compression : {{'gzip', 'bz2', 'zip', 'xz', None}}, optional encoding :...
Get the compression method for filepath_or_buffer. If compression='infer', the inferred compression method is returned. Otherwise, the input compression method is returned unchanged, unless it's invalid, in which case an error is raised. Parameters ---------- filepath_or_buffer : a path...
Get file handle for given path/buffer and mode. Parameters ---------- path_or_buf : a path (str) or buffer mode : str mode to open path_or_buf with encoding : str or None compression : {'infer', 'gzip', 'bz2', 'zip', 'xz', None}, default None If 'infer' and `filepath_or_...
Wrap comparison operations to convert timedelta-like to timedelta64 def _td_array_cmp(cls, op): """ Wrap comparison operations to convert timedelta-like to timedelta64 """ opname = '__{name}__'.format(name=op.__name__) nat_result = opname == '__ne__' def wrapper(self, other): if isinst...
Parameters ---------- array : list-like copy : bool, default False unit : str, default "ns" The timedelta unit to treat integers as multiples of. errors : {"raise", "coerce", "ignore"}, default "raise" How to handle elements that cannot be converted to timedelta64[ns]. See ``...
Convert an ndarray with integer-dtype to timedelta64[ns] dtype, treating the integers as multiples of the given timedelta unit. Parameters ---------- data : numpy.ndarray with integer-dtype unit : str, default "ns" The timedelta unit to treat integers as multiples of. Returns -----...
Convert a object-dtyped or string-dtyped array into an timedelta64[ns]-dtyped array. Parameters ---------- data : ndarray or Index unit : str, default "ns" The timedelta unit to treat integers as multiples of. errors : {"raise", "coerce", "ignore"}, default "raise" How to handle...
Add DatetimeArray/Index or ndarray[datetime64] to TimedeltaArray. def _add_datetime_arraylike(self, other): """ Add DatetimeArray/Index or ndarray[datetime64] to TimedeltaArray. """ if isinstance(other, np.ndarray): # At this point we have already checked that dtype is datet...
Return a dataframe of the components (days, hours, minutes, seconds, milliseconds, microseconds, nanoseconds) of the Timedeltas. Returns ------- a DataFrame def components(self): """ Return a dataframe of the components (days, hours, minutes, seconds, millisecon...
Add engine to the excel writer registry.io.excel. You must use this method to integrate with ``to_excel``. Parameters ---------- klass : ExcelWriter def register_writer(klass): """ Add engine to the excel writer registry.io.excel. You must use this method to integrate with ``to_excel``. ...
Convert Excel column name like 'AB' to 0-based column index. Parameters ---------- x : str The Excel column name to convert to a 0-based column index. Returns ------- num : int The column index corresponding to the name. Raises ------ ValueError Part of the...
Convert comma separated list of column names and ranges to indices. Parameters ---------- areas : str A string containing a sequence of column ranges (or areas). Returns ------- cols : list A list of 0-based column indices. Examples -------- >>> _range2cols('A:E') ...
Convert `usecols` into a compatible format for parsing in `parsers.py`. Parameters ---------- usecols : object The use-columns object to potentially convert. Returns ------- converted : object The compatible format of `usecols`. def _maybe_convert_usecols(usecols): """ ...
Forward fill blank entries in row but only inside the same parent index. Used for creating headers in Multiindex. Parameters ---------- row : list List of items in a single row. control_row : list of bool Helps to determine if particular column is in same parent index as the ...
Pop the header name for MultiIndex parsing. Parameters ---------- row : list The data row to parse for the header name. index_col : int, list The index columns for our data. Assumed to be non-null. Returns ------- header_name : str The extracted header name. tri...
Ensure that we are grabbing the correct scope. def _ensure_scope(level, global_dict=None, local_dict=None, resolvers=(), target=None, **kwargs): """Ensure that we are grabbing the correct scope.""" return Scope(level + 1, global_dict=global_dict, local_dict=local_dict, resolv...
Replace a number with its hexadecimal representation. Used to tag temporary variables with their calling scope's id. def _replacer(x): """Replace a number with its hexadecimal representation. Used to tag temporary variables with their calling scope's id. """ # get the hex repr of the binary char an...
Return the padded hexadecimal id of ``obj``. def _raw_hex_id(obj): """Return the padded hexadecimal id of ``obj``.""" # interpret as a pointer since that's what really what id returns packed = struct.pack('@P', id(obj)) return ''.join(map(_replacer, packed))
Return a prettier version of obj Parameters ---------- obj : object Object to pretty print Returns ------- s : str Pretty print object repr def _get_pretty_string(obj): """Return a prettier version of obj Parameters ---------- obj : object Object to pr...
Resolve a variable name in a possibly local context Parameters ---------- key : str A variable name is_local : bool Flag indicating whether the variable is local or not (prefixed with the '@' symbol) Returns ------- value : ob...
Replace a variable name, with a potentially new value. Parameters ---------- old_key : str Current variable name to replace new_key : str New variable name to replace `old_key` with new_value : object Value to be replaced along with the possib...
Get specifically scoped variables from a list of stack frames. Parameters ---------- stack : list A list of stack frames as returned by ``inspect.stack()`` scopes : sequence of strings A sequence containing valid stack frame attribute names that evalu...
Update the current scope by going back `level` levels. Parameters ---------- level : int or None, optional, default None def update(self, level): """Update the current scope by going back `level` levels. Parameters ---------- level : int or None, optional, defa...
Add a temporary variable to the scope. Parameters ---------- value : object An arbitrary object to be assigned to a temporary variable. Returns ------- name : basestring The name of the temporary variable created. def add_tmp(self, value): ...
Return the full scope for use with passing to engines transparently as a mapping. Returns ------- vars : DeepChainMap All variables in this scope. def full_scope(self): """Return the full scope for use with passing to engines transparently as a mapping. ...
Read SAS files stored as either XPORT or SAS7BDAT format files. Parameters ---------- filepath_or_buffer : string or file-like object Path to the SAS file. format : string {'xport', 'sas7bdat'} or None If None, file format is inferred from file extension. If 'xport' or 'sas7bdat...
Install the scalar coercion methods. def _coerce_method(converter): """ Install the scalar coercion methods. """ def wrapper(self): if len(self) == 1: return converter(self.iloc[0]) raise TypeError("cannot convert the series to " "{0}".format(str(con...
Derive the "_data" and "index" attributes of a new Series from a dictionary input. Parameters ---------- data : dict or dict-like Data used to populate the new Series index : Index or index-like, default None index for the new Series: if None, use dict ke...
Construct Series from array. .. deprecated :: 0.23.0 Use pd.Series(..) constructor instead. def from_array(cls, arr, index=None, name=None, dtype=None, copy=False, fastpath=False): """ Construct Series from array. .. deprecated :: 0.23.0 Use ...
Override generic, we want to set the _typ here. def _set_axis(self, axis, labels, fastpath=False): """ Override generic, we want to set the _typ here. """ if not fastpath: labels = ensure_index(labels) is_all_dates = labels.is_all_dates if is_all_dates: ...
Return object Series which contains boxed values. .. deprecated :: 0.23.0 Use ``astype(object)`` instead. this is an internal non-public method def asobject(self): """ Return object Series which contains boxed values. .. deprecated :: 0.23.0 Use ``as...
Return selected slices of an array along given axis as a Series. .. deprecated:: 0.24.0 See Also -------- numpy.ndarray.compress def compress(self, condition, args, *kwargs): """ Return selected slices of an array along given axis as a Series. .. deprecated:...
Return the integer indices of the elements that are non-zero. .. deprecated:: 0.24.0 Please use .to_numpy().nonzero() as a replacement. This method is equivalent to calling `numpy.nonzero` on the series data. For compatibility with NumPy, the return value is the same (a tu...
Create a new view of the Series. This function will return a new Series with a view of the same underlying values in memory, optionally reinterpreted with a new data type. The new data type must preserve the same size in bytes as to not cause index misalignment. Parameters ...
Return the i-th value or values in the Series by location. Parameters ---------- i : int, slice, or sequence of integers Returns ------- scalar (int) or Series (slice, sequence) def _ixs(self, i, axis=0): """ Return the i-th value or values in the Serie...
Repeat elements of a Series. Returns a new Series where each element of the current Series is repeated consecutively a given number of times. Parameters ---------- repeats : int or array of ints The number of repetitions for each element. This should be a ...
Generate a new DataFrame or Series with the index reset. This is useful when the index needs to be treated as a column, or when the index is meaningless and needs to be reset to the default before another operation. Parameters ---------- level : int, str, tuple, or list...
Render a string representation of the Series. Parameters ---------- buf : StringIO-like, optional Buffer to write to. na_rep : str, optional String representation of NaN to use, default 'NaN'. float_format : one-parameter function, optional Fo...
Convert Series to {label -> value} dict or dict-like object. Parameters ---------- into : class, default dict The collections.abc.Mapping subclass to use as the return object. Can be the actual class or an empty instance of the mapping type you want. If you ...
Convert Series to DataFrame. Parameters ---------- name : object, default None The passed name should substitute for the series name (if it has one). Returns ------- DataFrame DataFrame representation of Series. Examples ...
Convert Series to SparseSeries. Parameters ---------- kind : {'block', 'integer'}, default 'block' fill_value : float, defaults to NaN (missing) Value to use for filling NaN values. Returns ------- SparseSeries Sparse representation of th...
Set the Series name. Parameters ---------- name : str inplace : bool whether to modify `self` directly or return a copy def _set_name(self, name, inplace=False): """ Set the Series name. Parameters ---------- name : str inpla...
Return number of non-NA/null observations in the Series. Parameters ---------- level : int or level name, default None If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a smaller Series. Returns ------- i...
Return Series with duplicate values removed. Parameters ---------- keep : {'first', 'last', ``False``}, default 'first' - 'first' : Drop duplicates except for the first occurrence. - 'last' : Drop duplicates except for the last occurrence. - ``False`` : Drop ...
Return the row label of the minimum value. If multiple values equal the minimum, the first row label with that value is returned. Parameters ---------- skipna : bool, default True Exclude NA/null values. If the entire Series is NA, the result will be NA....
Return the row label of the maximum value. If multiple values equal the maximum, the first row label with that value is returned. Parameters ---------- skipna : bool, default True Exclude NA/null values. If the entire Series is NA, the result will be NA....
Round each value in a Series to the given number of decimals. Parameters ---------- decimals : int Number of decimal places to round to (default: 0). If decimals is negative, it specifies the number of positions to the left of the decimal point. Retu...
Return value at the given quantile. Parameters ---------- q : float or array-like, default 0.5 (50% quantile) 0 <= q <= 1, the quantile(s) to compute. interpolation : {'linear', 'lower', 'higher', 'midpoint', 'nearest'} .. versionadded:: 0.18.0 This ...
Compute correlation with `other` Series, excluding missing values. Parameters ---------- other : Series Series with which to compute the correlation. method : {'pearson', 'kendall', 'spearman'} or callable * pearson : standard correlation coefficient ...
Compute covariance with Series, excluding missing values. Parameters ---------- other : Series Series with which to compute the covariance. min_periods : int, optional Minimum number of observations needed to have a valid result. Returns ------- ...
First discrete difference of element. Calculates the difference of a Series element compared with another element in the Series (default is element in previous row). Parameters ---------- periods : int, default 1 Periods to shift for calculating difference, accepts ...
Compute the dot product between the Series and the columns of other. This method computes the dot product between the Series and another one, or the Series and each columns of a DataFrame, or the Series and each columns of an array. It can also be called using `self @ other` in Python ...
Concatenate two or more Series. Parameters ---------- to_append : Series or list/tuple of Series Series to append with self. ignore_index : bool, default False If True, do not use the index labels. .. versionadded:: 0.19.0 verify_integrity :...
Perform generic binary operation with optional fill value. Parameters ---------- other : Series func : binary operator fill_value : float or object Value to substitute for NA/null values. If both Series are NA in a location, the result will be NA regardle...
Combine the Series with a Series or scalar according to `func`. Combine the Series and `other` using `func` to perform elementwise selection for combined Series. `fill_value` is assumed when value is missing at some index from one of the two objects being combined. Parameters ...
Combine Series values, choosing the calling Series's values first. Parameters ---------- other : Series The value(s) to be combined with the `Series`. Returns ------- Series The result of combining the Series with the other object. See A...
Modify Series in place using non-NA values from passed Series. Aligns on index. Parameters ---------- other : Series Examples -------- >>> s = pd.Series([1, 2, 3]) >>> s.update(pd.Series([4, 5, 6])) >>> s 0 4 1 5 2 ...
Sort by the values. Sort a Series in ascending or descending order by some criterion. Parameters ---------- axis : {0 or 'index'}, default 0 Axis to direct sorting. The value 'index' is accepted for compatibility with DataFrame.sort_values. ascen...
Sort Series by index labels. Returns a new Series sorted by label if `inplace` argument is ``False``, otherwise updates the original series and returns None. Parameters ---------- axis : int, default 0 Axis to direct sorting. This can only be 0 for Series. l...
Override ndarray.argsort. Argsorts the value, omitting NA/null values, and places the result in the same locations as the non-NA values. Parameters ---------- axis : int Has no effect but is accepted for compatibility with numpy. kind : {'mergesort', 'quicksort', 'he...
Return the largest `n` elements. Parameters ---------- n : int, default 5 Return this many descending sorted values. keep : {'first', 'last', 'all'}, default 'first' When there are duplicate values that cannot all fit in a Series of `n` elements: ...
Return the smallest `n` elements. Parameters ---------- n : int, default 5 Return this many ascending sorted values. keep : {'first', 'last', 'all'}, default 'first' When there are duplicate values that cannot all fit in a Series of `n` elements: ...
Swap levels i and j in a MultiIndex. Parameters ---------- i, j : int, str (can be mixed) Level of index to be swapped. Can pass level name as string. Returns ------- Series Series with levels swapped in MultiIndex. .. versionchanged:: 0...
Rearrange index levels using input order. May not drop or duplicate levels. Parameters ---------- order : list of int representing new level order (reference level by number or key) Returns ------- type of caller (new object) def reorder_levels(...
Map values of Series according to input correspondence. Used for substituting each value in a Series with another value, that may be derived from a function, a ``dict`` or a :class:`Series`. Parameters ---------- arg : function, dict, or Series Mapping corre...
Invoke function on values of Series. Can be ufunc (a NumPy function that applies to the entire Series) or a Python function that only works on single values. Parameters ---------- func : function Python function or NumPy ufunc to apply. convert_dtype : bool,...
Perform a reduction operation. If we have an ndarray as a value, then simply perform the operation, otherwise delegate to the object. def _reduce(self, op, name, axis=0, skipna=True, numeric_only=None, filter_type=None, **kwds): """ Perform a reduction operation. ...
Alter Series index labels or name. Function / dict values must be unique (1-to-1). Labels not contained in a dict / Series will be left as-is. Extra labels listed don't throw an error. Alternatively, change ``Series.name`` with a scalar value. See the :ref:`user guide <basics....
Conform Series to new index with optional filling logic. .. deprecated:: 0.21.0 Use ``Series.reindex`` instead. def reindex_axis(self, labels, axis=0, **kwargs): """ Conform Series to new index with optional filling logic. .. deprecated:: 0.21.0 Use ``Series.re...
Return the memory usage of the Series. The memory usage can optionally include the contribution of the index and of elements of `object` dtype. Parameters ---------- index : bool, default True Specifies whether to include the memory usage of the Series index. ...
Check whether `values` are contained in Series. Return a boolean Series showing whether each element in the Series matches an element in the passed sequence of `values` exactly. Parameters ---------- values : set or list-like The sequence of values to test. Passing ...
Return boolean Series equivalent to left <= series <= right. This function returns a boolean vector containing `True` wherever the corresponding Series element is between the boundary values `left` and `right`. NA values are treated as `False`. Parameters ---------- lef...
Read CSV file. .. deprecated:: 0.21.0 Use :func:`pandas.read_csv` instead. It is preferable to use the more powerful :func:`pandas.read_csv` for most general purposes, but ``from_csv`` makes for an easy roundtrip to and from a file (the exact counterpart of ``to_csv...
Return a new Series with missing values removed. See the :ref:`User Guide <missing_data>` for more on which values are considered missing, and how to work with missing data. Parameters ---------- axis : {0 or 'index'}, default 0 There is only one axis to drop values...
Return Series without null values. .. deprecated:: 0.23.0 Use :meth:`Series.dropna` instead. def valid(self, inplace=False, **kwargs): """ Return Series without null values. .. deprecated:: 0.23.0 Use :meth:`Series.dropna` instead. """ warnings....
Cast to DatetimeIndex of Timestamps, at beginning of period. Parameters ---------- freq : str, default frequency of PeriodIndex Desired frequency. how : {'s', 'e', 'start', 'end'} Convention for converting period to timestamp; start of period vs. en...
Convert Series from DatetimeIndex to PeriodIndex with desired frequency (inferred from index if not passed). Parameters ---------- freq : str, default None Frequency associated with the PeriodIndex. copy : bool, default True Whether or not to return a cop...
Convert argument to a numeric type. The default return dtype is `float64` or `int64` depending on the data supplied. Use the `downcast` parameter to obtain other dtypes. Please note that precision loss may occur if really large numbers are passed in. Due to the internal limitations of `ndarray`, i...
Create a 0-dim ndarray containing the fill value Parameters ---------- arr : SparseArray Returns ------- fill_value : ndarray 0-dim ndarray with just the fill value. Notes ----- coerce fill_value to arr dtype if possible int64 SparseArray can have NaN as fill_value if ...
Perform a binary operation between two arrays. Parameters ---------- left : Union[SparseArray, ndarray] right : Union[SparseArray, ndarray] op : Callable The binary operation to perform name str Name of the callable. Returns ------- SparseArray def _sparse_array_op...
wrap op result to have correct dtype def _wrap_result(name, data, sparse_index, fill_value, dtype=None): """ wrap op result to have correct dtype """ if name.startswith('__'): # e.g. __eq__ --> eq name = name[2:-2] if name in ('eq', 'ne', 'lt', 'gt', 'le', 'ge'): dtype = np...
array must be SparseSeries or SparseArray def _maybe_to_sparse(array): """ array must be SparseSeries or SparseArray """ if isinstance(array, ABCSparseSeries): array = array.values.copy() return array
return an ndarray for our input, in a platform independent manner def _sanitize_values(arr): """ return an ndarray for our input, in a platform independent manner """ if hasattr(arr, 'values'): arr = arr.values else: # scalar if is_scalar(arr): arr = [a...
Convert ndarray to sparse format Parameters ---------- arr : ndarray kind : {'block', 'integer'} fill_value : NaN or another value dtype : np.dtype, optional copy : bool, default False Returns ------- (sparse_values, index, fill_value) : (ndarray, SparseIndex, Scalar) def make...
The percent of non- ``fill_value`` points, as decimal. Examples -------- >>> s = SparseArray([0, 0, 1, 1, 1], fill_value=0) >>> s.density 0.6 def density(self): """ The percent of non- ``fill_value`` points, as decimal. Examples -------- ...
Fill missing values with `value`. Parameters ---------- value : scalar, optional method : str, optional .. warning:: Using 'method' will result in high memory use, as all `fill_value` methods will be converted to an in-memory nd...
Get the location of the first missing value. Returns ------- int def _first_fill_value_loc(self): """ Get the location of the first missing value. Returns ------- int """ if len(self) == 0 or self.sp_index.npoints == len(self): ...
Returns a Series containing counts of unique values. Parameters ---------- dropna : boolean, default True Don't include counts of NaN, even if NaN is in sp_values. Returns ------- counts : Series def value_counts(self, dropna=True): """ Retu...

Return the maximum value of the Index. Parameters ---------- axis : int, optional For compatibility with NumPy. Only 0 or None are allowed. skipna : bool, default True Returns ------- scalar Maximum value. See Also ------...

Return an ndarray of the maximum argument indexer. Parameters ---------- axis : {None} Dummy argument for consistency with Series skipna : bool, default True See Also -------- numpy.ndarray.argmax def argmax(self, axis=None, skipna=True): ""...

Return the minimum value of the Index. Parameters ---------- axis : {None} Dummy argument for consistency with Series skipna : bool, default True Returns ------- scalar Minimum value. See Also -------- Index.max :...

Return a ndarray of the minimum argument indexer. Parameters ---------- axis : {None} Dummy argument for consistency with Series skipna : bool, default True Returns ------- numpy.ndarray See Also -------- numpy.ndarray.argmin...

Return a list of the values. These are each a scalar type, which is a Python scalar (for str, int, float) or a pandas scalar (for Timestamp/Timedelta/Interval/Period) Returns ------- list See Also -------- numpy.ndarray.tolist def tolist(self):...

perform the reduction type operation if we can def _reduce(self, op, name, axis=0, skipna=True, numeric_only=None, filter_type=None, **kwds): """ perform the reduction type operation if we can """ func = getattr(self, name, None) if func is None: raise TypeError("{kl...

An internal function that maps values using the input correspondence (which can be a dict, Series, or function). Parameters ---------- mapper : function, dict, or Series The input correspondence object na_action : {None, 'ignore'} If 'ignore', propagate N...

Return a Series containing counts of unique values. The resulting object will be in descending order so that the first element is the most frequently-occurring element. Excludes NA values by default. Parameters ---------- normalize : boolean, default False I...

Return number of unique elements in the object. Excludes NA values by default. Parameters ---------- dropna : bool, default True Don't include NaN in the count. Returns ------- int See Also -------- DataFrame.nunique: Method...

Memory usage of the values Parameters ---------- deep : bool Introspect the data deeply, interrogate `object` dtypes for system-level memory consumption Returns ------- bytes used See Also -------- numpy.ndarray.nbytes ...

Return the argument with an initial component of ~ or ~user replaced by that user's home directory. Parameters ---------- filepath_or_buffer : object to be converted if possible Returns ------- expanded_filepath_or_buffer : an expanded filepath or the i...

Attempt to convert a path-like object to a string. Parameters ---------- filepath_or_buffer : object to be converted Returns ------- str_filepath_or_buffer : maybe a string version of the object Notes ----- Objects supporting the fspath protocol (python 3.6+) are coerced accor...

If the filepath_or_buffer is a url, translate and return the buffer. Otherwise passthrough. Parameters ---------- filepath_or_buffer : a url, filepath (str, py.path.local or pathlib.Path), or buffer compression : {{'gzip', 'bz2', 'zip', 'xz', None}}, optional encoding :...

Get the compression method for filepath_or_buffer. If compression='infer', the inferred compression method is returned. Otherwise, the input compression method is returned unchanged, unless it's invalid, in which case an error is raised. Parameters ---------- filepath_or_buffer : a path...

Get file handle for given path/buffer and mode. Parameters ---------- path_or_buf : a path (str) or buffer mode : str mode to open path_or_buf with encoding : str or None compression : {'infer', 'gzip', 'bz2', 'zip', 'xz', None}, default None If 'infer' and `filepath_or_...

Wrap comparison operations to convert timedelta-like to timedelta64 def _td_array_cmp(cls, op): """ Wrap comparison operations to convert timedelta-like to timedelta64 """ opname = '__{name}__'.format(name=op.__name__) nat_result = opname == '__ne__' def wrapper(self, other): if isinst...

Parameters ---------- array : list-like copy : bool, default False unit : str, default "ns" The timedelta unit to treat integers as multiples of. errors : {"raise", "coerce", "ignore"}, default "raise" How to handle elements that cannot be converted to timedelta64[ns]. See ``...

Convert an ndarray with integer-dtype to timedelta64[ns] dtype, treating the integers as multiples of the given timedelta unit. Parameters ---------- data : numpy.ndarray with integer-dtype unit : str, default "ns" The timedelta unit to treat integers as multiples of. Returns -----...

Convert a object-dtyped or string-dtyped array into an timedelta64[ns]-dtyped array. Parameters ---------- data : ndarray or Index unit : str, default "ns" The timedelta unit to treat integers as multiples of. errors : {"raise", "coerce", "ignore"}, default "raise" How to handle...

Add DatetimeArray/Index or ndarray[datetime64] to TimedeltaArray. def _add_datetime_arraylike(self, other): """ Add DatetimeArray/Index or ndarray[datetime64] to TimedeltaArray. """ if isinstance(other, np.ndarray): # At this point we have already checked that dtype is datet...

Return a dataframe of the components (days, hours, minutes, seconds, milliseconds, microseconds, nanoseconds) of the Timedeltas. Returns ------- a DataFrame def components(self): """ Return a dataframe of the components (days, hours, minutes, seconds, millisecon...

Add engine to the excel writer registry.io.excel. You must use this method to integrate with ``to_excel``. Parameters ---------- klass : ExcelWriter def register_writer(klass): """ Add engine to the excel writer registry.io.excel. You must use this method to integrate with ``to_excel``. ...

Convert Excel column name like 'AB' to 0-based column index. Parameters ---------- x : str The Excel column name to convert to a 0-based column index. Returns ------- num : int The column index corresponding to the name. Raises ------ ValueError Part of the...

Convert comma separated list of column names and ranges to indices. Parameters ---------- areas : str A string containing a sequence of column ranges (or areas). Returns ------- cols : list A list of 0-based column indices. Examples -------- >>> _range2cols('A:E') ...

Convert `usecols` into a compatible format for parsing in `parsers.py`. Parameters ---------- usecols : object The use-columns object to potentially convert. Returns ------- converted : object The compatible format of `usecols`. def _maybe_convert_usecols(usecols): """ ...

Forward fill blank entries in row but only inside the same parent index. Used for creating headers in Multiindex. Parameters ---------- row : list List of items in a single row. control_row : list of bool Helps to determine if particular column is in same parent index as the ...

Pop the header name for MultiIndex parsing. Parameters ---------- row : list The data row to parse for the header name. index_col : int, list The index columns for our data. Assumed to be non-null. Returns ------- header_name : str The extracted header name. tri...

Ensure that we are grabbing the correct scope. def _ensure_scope(level, global_dict=None, local_dict=None, resolvers=(), target=None, **kwargs): """Ensure that we are grabbing the correct scope.""" return Scope(level + 1, global_dict=global_dict, local_dict=local_dict, resolv...

Replace a number with its hexadecimal representation. Used to tag temporary variables with their calling scope's id. def _replacer(x): """Replace a number with its hexadecimal representation. Used to tag temporary variables with their calling scope's id. """ # get the hex repr of the binary char an...

Return the padded hexadecimal id of ``obj``. def _raw_hex_id(obj): """Return the padded hexadecimal id of ``obj``.""" # interpret as a pointer since that's what really what id returns packed = struct.pack('@P', id(obj)) return ''.join(map(_replacer, packed))

Return a prettier version of obj Parameters ---------- obj : object Object to pretty print Returns ------- s : str Pretty print object repr def _get_pretty_string(obj): """Return a prettier version of obj Parameters ---------- obj : object Object to pr...

Resolve a variable name in a possibly local context Parameters ---------- key : str A variable name is_local : bool Flag indicating whether the variable is local or not (prefixed with the '@' symbol) Returns ------- value : ob...

Replace a variable name, with a potentially new value. Parameters ---------- old_key : str Current variable name to replace new_key : str New variable name to replace `old_key` with new_value : object Value to be replaced along with the possib...

Get specifically scoped variables from a list of stack frames. Parameters ---------- stack : list A list of stack frames as returned by ``inspect.stack()`` scopes : sequence of strings A sequence containing valid stack frame attribute names that evalu...

Update the current scope by going back `level` levels. Parameters ---------- level : int or None, optional, default None def update(self, level): """Update the current scope by going back `level` levels. Parameters ---------- level : int or None, optional, defa...

Add a temporary variable to the scope. Parameters ---------- value : object An arbitrary object to be assigned to a temporary variable. Returns ------- name : basestring The name of the temporary variable created. def add_tmp(self, value): ...

Return the full scope for use with passing to engines transparently as a mapping. Returns ------- vars : DeepChainMap All variables in this scope. def full_scope(self): """Return the full scope for use with passing to engines transparently as a mapping. ...

Read SAS files stored as either XPORT or SAS7BDAT format files. Parameters ---------- filepath_or_buffer : string or file-like object Path to the SAS file. format : string {'xport', 'sas7bdat'} or None If None, file format is inferred from file extension. If 'xport' or 'sas7bdat...

Install the scalar coercion methods. def _coerce_method(converter): """ Install the scalar coercion methods. """ def wrapper(self): if len(self) == 1: return converter(self.iloc[0]) raise TypeError("cannot convert the series to " "{0}".format(str(con...

Derive the "_data" and "index" attributes of a new Series from a dictionary input. Parameters ---------- data : dict or dict-like Data used to populate the new Series index : Index or index-like, default None index for the new Series: if None, use dict ke...

Construct Series from array. .. deprecated :: 0.23.0 Use pd.Series(..) constructor instead. def from_array(cls, arr, index=None, name=None, dtype=None, copy=False, fastpath=False): """ Construct Series from array. .. deprecated :: 0.23.0 Use ...

Override generic, we want to set the _typ here. def _set_axis(self, axis, labels, fastpath=False): """ Override generic, we want to set the _typ here. """ if not fastpath: labels = ensure_index(labels) is_all_dates = labels.is_all_dates if is_all_dates: ...

Return object Series which contains boxed values. .. deprecated :: 0.23.0 Use ``astype(object)`` instead. *this is an internal non-public method* def asobject(self): """ Return object Series which contains boxed values. .. deprecated :: 0.23.0 Use ``as...

Return selected slices of an array along given axis as a Series. .. deprecated:: 0.24.0 See Also -------- numpy.ndarray.compress def compress(self, condition, *args, **kwargs): """ Return selected slices of an array along given axis as a Series. .. deprecated:...

Return the *integer* indices of the elements that are non-zero. .. deprecated:: 0.24.0 Please use .to_numpy().nonzero() as a replacement. This method is equivalent to calling `numpy.nonzero` on the series data. For compatibility with NumPy, the return value is the same (a tu...

Create a new view of the Series. This function will return a new Series with a view of the same underlying values in memory, optionally reinterpreted with a new data type. The new data type must preserve the same size in bytes as to not cause index misalignment. Parameters ...

Return the i-th value or values in the Series by location. Parameters ---------- i : int, slice, or sequence of integers Returns ------- scalar (int) or Series (slice, sequence) def _ixs(self, i, axis=0): """ Return the i-th value or values in the Serie...

Repeat elements of a Series. Returns a new Series where each element of the current Series is repeated consecutively a given number of times. Parameters ---------- repeats : int or array of ints The number of repetitions for each element. This should be a ...

Generate a new DataFrame or Series with the index reset. This is useful when the index needs to be treated as a column, or when the index is meaningless and needs to be reset to the default before another operation. Parameters ---------- level : int, str, tuple, or list...

Render a string representation of the Series. Parameters ---------- buf : StringIO-like, optional Buffer to write to. na_rep : str, optional String representation of NaN to use, default 'NaN'. float_format : one-parameter function, optional Fo...

Convert Series to {label -> value} dict or dict-like object. Parameters ---------- into : class, default dict The collections.abc.Mapping subclass to use as the return object. Can be the actual class or an empty instance of the mapping type you want. If you ...

Convert Series to DataFrame. Parameters ---------- name : object, default None The passed name should substitute for the series name (if it has one). Returns ------- DataFrame DataFrame representation of Series. Examples ...

Convert Series to SparseSeries. Parameters ---------- kind : {'block', 'integer'}, default 'block' fill_value : float, defaults to NaN (missing) Value to use for filling NaN values. Returns ------- SparseSeries Sparse representation of th...

Set the Series name. Parameters ---------- name : str inplace : bool whether to modify `self` directly or return a copy def _set_name(self, name, inplace=False): """ Set the Series name. Parameters ---------- name : str inpla...

Return number of non-NA/null observations in the Series. Parameters ---------- level : int or level name, default None If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a smaller Series. Returns ------- i...

Return Series with duplicate values removed. Parameters ---------- keep : {'first', 'last', ``False``}, default 'first' - 'first' : Drop duplicates except for the first occurrence. - 'last' : Drop duplicates except for the last occurrence. - ``False`` : Drop ...

Return the row label of the minimum value. If multiple values equal the minimum, the first row label with that value is returned. Parameters ---------- skipna : bool, default True Exclude NA/null values. If the entire Series is NA, the result will be NA....

Return the row label of the maximum value. If multiple values equal the maximum, the first row label with that value is returned. Parameters ---------- skipna : bool, default True Exclude NA/null values. If the entire Series is NA, the result will be NA....

Round each value in a Series to the given number of decimals. Parameters ---------- decimals : int Number of decimal places to round to (default: 0). If decimals is negative, it specifies the number of positions to the left of the decimal point. Retu...

Return value at the given quantile. Parameters ---------- q : float or array-like, default 0.5 (50% quantile) 0 <= q <= 1, the quantile(s) to compute. interpolation : {'linear', 'lower', 'higher', 'midpoint', 'nearest'} .. versionadded:: 0.18.0 This ...

Compute correlation with `other` Series, excluding missing values. Parameters ---------- other : Series Series with which to compute the correlation. method : {'pearson', 'kendall', 'spearman'} or callable * pearson : standard correlation coefficient ...

Compute covariance with Series, excluding missing values. Parameters ---------- other : Series Series with which to compute the covariance. min_periods : int, optional Minimum number of observations needed to have a valid result. Returns ------- ...

First discrete difference of element. Calculates the difference of a Series element compared with another element in the Series (default is element in previous row). Parameters ---------- periods : int, default 1 Periods to shift for calculating difference, accepts ...

Compute the dot product between the Series and the columns of other. This method computes the dot product between the Series and another one, or the Series and each columns of a DataFrame, or the Series and each columns of an array. It can also be called using `self @ other` in Python ...

Concatenate two or more Series. Parameters ---------- to_append : Series or list/tuple of Series Series to append with self. ignore_index : bool, default False If True, do not use the index labels. .. versionadded:: 0.19.0 verify_integrity :...

Perform generic binary operation with optional fill value. Parameters ---------- other : Series func : binary operator fill_value : float or object Value to substitute for NA/null values. If both Series are NA in a location, the result will be NA regardle...

Combine the Series with a Series or scalar according to `func`. Combine the Series and `other` using `func` to perform elementwise selection for combined Series. `fill_value` is assumed when value is missing at some index from one of the two objects being combined. Parameters ...

Combine Series values, choosing the calling Series's values first. Parameters ---------- other : Series The value(s) to be combined with the `Series`. Returns ------- Series The result of combining the Series with the other object. See A...

Modify Series in place using non-NA values from passed Series. Aligns on index. Parameters ---------- other : Series Examples -------- >>> s = pd.Series([1, 2, 3]) >>> s.update(pd.Series([4, 5, 6])) >>> s 0 4 1 5 2 ...

Sort by the values. Sort a Series in ascending or descending order by some criterion. Parameters ---------- axis : {0 or 'index'}, default 0 Axis to direct sorting. The value 'index' is accepted for compatibility with DataFrame.sort_values. ascen...

Sort Series by index labels. Returns a new Series sorted by label if `inplace` argument is ``False``, otherwise updates the original series and returns None. Parameters ---------- axis : int, default 0 Axis to direct sorting. This can only be 0 for Series. l...

Override ndarray.argsort. Argsorts the value, omitting NA/null values, and places the result in the same locations as the non-NA values. Parameters ---------- axis : int Has no effect but is accepted for compatibility with numpy. kind : {'mergesort', 'quicksort', 'he...

Return the largest `n` elements. Parameters ---------- n : int, default 5 Return this many descending sorted values. keep : {'first', 'last', 'all'}, default 'first' When there are duplicate values that cannot all fit in a Series of `n` elements: ...

Return the smallest `n` elements. Parameters ---------- n : int, default 5 Return this many ascending sorted values. keep : {'first', 'last', 'all'}, default 'first' When there are duplicate values that cannot all fit in a Series of `n` elements: ...

Swap levels i and j in a MultiIndex. Parameters ---------- i, j : int, str (can be mixed) Level of index to be swapped. Can pass level name as string. Returns ------- Series Series with levels swapped in MultiIndex. .. versionchanged:: 0...

Rearrange index levels using input order. May not drop or duplicate levels. Parameters ---------- order : list of int representing new level order (reference level by number or key) Returns ------- type of caller (new object) def reorder_levels(...

Map values of Series according to input correspondence. Used for substituting each value in a Series with another value, that may be derived from a function, a ``dict`` or a :class:`Series`. Parameters ---------- arg : function, dict, or Series Mapping corre...

Invoke function on values of Series. Can be ufunc (a NumPy function that applies to the entire Series) or a Python function that only works on single values. Parameters ---------- func : function Python function or NumPy ufunc to apply. convert_dtype : bool,...

Perform a reduction operation. If we have an ndarray as a value, then simply perform the operation, otherwise delegate to the object. def _reduce(self, op, name, axis=0, skipna=True, numeric_only=None, filter_type=None, **kwds): """ Perform a reduction operation. ...

Alter Series index labels or name. Function / dict values must be unique (1-to-1). Labels not contained in a dict / Series will be left as-is. Extra labels listed don't throw an error. Alternatively, change ``Series.name`` with a scalar value. See the :ref:`user guide <basics....

Conform Series to new index with optional filling logic. .. deprecated:: 0.21.0 Use ``Series.reindex`` instead. def reindex_axis(self, labels, axis=0, **kwargs): """ Conform Series to new index with optional filling logic. .. deprecated:: 0.21.0 Use ``Series.re...

Return the memory usage of the Series. The memory usage can optionally include the contribution of the index and of elements of `object` dtype. Parameters ---------- index : bool, default True Specifies whether to include the memory usage of the Series index. ...

Check whether `values` are contained in Series. Return a boolean Series showing whether each element in the Series matches an element in the passed sequence of `values` exactly. Parameters ---------- values : set or list-like The sequence of values to test. Passing ...

Return boolean Series equivalent to left <= series <= right. This function returns a boolean vector containing `True` wherever the corresponding Series element is between the boundary values `left` and `right`. NA values are treated as `False`. Parameters ---------- lef...

Read CSV file. .. deprecated:: 0.21.0 Use :func:`pandas.read_csv` instead. It is preferable to use the more powerful :func:`pandas.read_csv` for most general purposes, but ``from_csv`` makes for an easy roundtrip to and from a file (the exact counterpart of ``to_csv...

Return a new Series with missing values removed. See the :ref:`User Guide <missing_data>` for more on which values are considered missing, and how to work with missing data. Parameters ---------- axis : {0 or 'index'}, default 0 There is only one axis to drop values...

Return Series without null values. .. deprecated:: 0.23.0 Use :meth:`Series.dropna` instead. def valid(self, inplace=False, **kwargs): """ Return Series without null values. .. deprecated:: 0.23.0 Use :meth:`Series.dropna` instead. """ warnings....

Cast to DatetimeIndex of Timestamps, at *beginning* of period. Parameters ---------- freq : str, default frequency of PeriodIndex Desired frequency. how : {'s', 'e', 'start', 'end'} Convention for converting period to timestamp; start of period vs. en...

Convert Series from DatetimeIndex to PeriodIndex with desired frequency (inferred from index if not passed). Parameters ---------- freq : str, default None Frequency associated with the PeriodIndex. copy : bool, default True Whether or not to return a cop...

Convert argument to a numeric type. The default return dtype is `float64` or `int64` depending on the data supplied. Use the `downcast` parameter to obtain other dtypes. Please note that precision loss may occur if really large numbers are passed in. Due to the internal limitations of `ndarray`, i...

Create a 0-dim ndarray containing the fill value Parameters ---------- arr : SparseArray Returns ------- fill_value : ndarray 0-dim ndarray with just the fill value. Notes ----- coerce fill_value to arr dtype if possible int64 SparseArray can have NaN as fill_value if ...

Perform a binary operation between two arrays. Parameters ---------- left : Union[SparseArray, ndarray] right : Union[SparseArray, ndarray] op : Callable The binary operation to perform name str Name of the callable. Returns ------- SparseArray def _sparse_array_op...

wrap op result to have correct dtype def _wrap_result(name, data, sparse_index, fill_value, dtype=None): """ wrap op result to have correct dtype """ if name.startswith('__'): # e.g. __eq__ --> eq name = name[2:-2] if name in ('eq', 'ne', 'lt', 'gt', 'le', 'ge'): dtype = np...

array must be SparseSeries or SparseArray def _maybe_to_sparse(array): """ array must be SparseSeries or SparseArray """ if isinstance(array, ABCSparseSeries): array = array.values.copy() return array

return an ndarray for our input, in a platform independent manner def _sanitize_values(arr): """ return an ndarray for our input, in a platform independent manner """ if hasattr(arr, 'values'): arr = arr.values else: # scalar if is_scalar(arr): arr = [a...

Convert ndarray to sparse format Parameters ---------- arr : ndarray kind : {'block', 'integer'} fill_value : NaN or another value dtype : np.dtype, optional copy : bool, default False Returns ------- (sparse_values, index, fill_value) : (ndarray, SparseIndex, Scalar) def make...

The percent of non- ``fill_value`` points, as decimal. Examples -------- >>> s = SparseArray([0, 0, 1, 1, 1], fill_value=0) >>> s.density 0.6 def density(self): """ The percent of non- ``fill_value`` points, as decimal. Examples -------- ...

Fill missing values with `value`. Parameters ---------- value : scalar, optional method : str, optional .. warning:: Using 'method' will result in high memory use, as all `fill_value` methods will be converted to an in-memory nd...

Get the location of the first missing value. Returns ------- int def _first_fill_value_loc(self): """ Get the location of the first missing value. Returns ------- int """ if len(self) == 0 or self.sp_index.npoints == len(self): ...

Returns a Series containing counts of unique values. Parameters ---------- dropna : boolean, default True Don't include counts of NaN, even if NaN is in sp_values. Returns ------- counts : Series def value_counts(self, dropna=True): """ Retu...