JorgeVB/code_unlearning_dataset · Datasets at Hugging Face

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Insert item at selected position. Parameters ---------- loc : int item : hashable value : array_like allow_duplicates: bool If False, trying to insert non-unique item will raise def insert(self, loc, item, value, allow_duplicates=False): """ ...
Conform block manager to new index. def reindex_axis(self, new_index, axis, method=None, limit=None, fill_value=None, copy=True): """ Conform block manager to new index. """ new_index = ensure_index(new_index) new_index, indexer = self.axes[axis].reindex(new...
Parameters ---------- new_axis : Index indexer : ndarray of int64 or None axis : int fill_value : object allow_dups : bool pandas-indexer with -1's only. def reindex_indexer(self, new_axis, indexer, axis, fill_value=None, allow_dups=False...
Slice/take blocks along axis=0. Overloaded for SingleBlock Returns ------- new_blocks : list of Block def _slice_take_blocks_ax0(self, slice_or_indexer, fill_tuple=None): """ Slice/take blocks along axis=0. Overloaded for SingleBlock Returns -...
Take items along any axis. def take(self, indexer, axis=1, verify=True, convert=True): """ Take items along any axis. """ self._consolidate_inplace() indexer = (np.arange(indexer.start, indexer.stop, indexer.step, dtype='int64') if...
Return a blockmanager with all blocks unstacked. Parameters ---------- unstacker_func : callable A (partially-applied) ``pd.core.reshape._Unstacker`` class. fill_value : Any fill_value for newly introduced missing values. Returns ------- ...
Delete single item from SingleBlockManager. Ensures that self.blocks doesn't become empty. def delete(self, item): """ Delete single item from SingleBlockManager. Ensures that self.blocks doesn't become empty. """ loc = self.items.get_loc(item) self._block.dele...
Concatenate a list of SingleBlockManagers into a single SingleBlockManager. Used for pd.concat of Series objects with axis=0. Parameters ---------- to_concat : list of SingleBlockManagers new_axis : Index of the result Returns ------- SingleBloc...
Construct SparseSeries from array. .. deprecated:: 0.23.0 Use the pd.SparseSeries(..) constructor instead. def from_array(cls, arr, index=None, name=None, copy=False, fill_value=None, fastpath=False): """Construct SparseSeries from array. .. deprecated:: 0.23.0 ...
return my self as a sparse array, do not copy by default def as_sparse_array(self, kind=None, fill_value=None, copy=False): """ return my self as a sparse array, do not copy by default """ if fill_value is None: fill_value = self.fill_value if kind is None: kind = self....
perform a reduction operation def _reduce(self, op, name, axis=0, skipna=True, numeric_only=None, filter_type=None, kwds): """ perform a reduction operation """ return op(self.get_values(), skipna=skipna, kwds)
Return the i-th value or values in the SparseSeries by location Parameters ---------- i : int, slice, or sequence of integers Returns ------- value : scalar (int) or Series (slice, sequence) def _ixs(self, i, axis=0): """ Return the i-th value or values...
Return an object with absolute value taken. Only applicable to objects that are all numeric Returns ------- abs: same type as caller def abs(self): """ Return an object with absolute value taken. Only applicable to objects that are all numeric Returns ...
Returns value occupying requested label, default to specified missing value if not present. Analogous to dict.get Parameters ---------- label : object Label value looking for default : object, optional Value to return if label not in index Return...
Retrieve single value at passed index label .. deprecated:: 0.21.0 Please use .at[] or .iat[] accessors. Parameters ---------- index : label takeable : interpret the index as indexers, default False Returns ------- value : scalar value def get...
Quickly set single value at passed label. If label is not contained, a new object is created with the label placed at the end of the result index .. deprecated:: 0.21.0 Please use .at[] or .iat[] accessors. Parameters ---------- label : object Parti...
Convert SparseSeries to a Series. Returns ------- s : Series def to_dense(self): """ Convert SparseSeries to a Series. Returns ------- s : Series """ return Series(self.values.to_dense(), index=self.index, name=self...
Make a copy of the SparseSeries. Only the actual sparse values need to be copied def copy(self, deep=True): """ Make a copy of the SparseSeries. Only the actual sparse values need to be copied """ # TODO: https://github.com/pandas-dev/pandas/issues/22314 # We ski...
Conform sparse values to new SparseIndex Parameters ---------- new_index : {BlockIndex, IntIndex} Returns ------- reindexed : SparseSeries def sparse_reindex(self, new_index): """ Conform sparse values to new SparseIndex Parameters ----...
Cumulative sum of non-NA/null values. When performing the cumulative summation, any non-NA/null values will be skipped. The resulting SparseSeries will preserve the locations of NaN values, but the fill value will be `np.nan` regardless. Parameters ---------- axis : {0}...
Analogous to Series.dropna. If fill_value=NaN, returns a dense Series def dropna(self, axis=0, inplace=False, **kwargs): """ Analogous to Series.dropna. If fill_value=NaN, returns a dense Series """ # TODO: make more efficient # Validate axis self._get_axis_number(axis o...
Combine Series values, choosing the calling Series's values first. Result index will be the union of the two indexes Parameters ---------- other : Series Returns ------- y : Series def combine_first(self, other): """ Combine Series values, choos...
Create a cache of unique dates from an array of dates Parameters ---------- arg : integer, float, string, datetime, list, tuple, 1-d array, Series format : string Strftime format to parse time cache : boolean True attempts to create a cache of converted values convert_listlike :...
Convert array of dates with a cache and box the result Parameters ---------- arg : integer, float, string, datetime, list, tuple, 1-d array, Series cache_array : Series Cache of converted, unique dates box : boolean True boxes result as an Index-like, False returns an ndarray er...
Return results from array_strptime if a %z or %Z directive was passed. Parameters ---------- result : ndarray int64 date representations of the dates timezones : ndarray pytz timezone objects box : boolean True boxes result as an Index-like, False returns an ndarray tz :...
Helper function for to_datetime. Performs the conversions of 1D listlike of dates Parameters ---------- arg : list, tuple, ndarray, Series, Index date to be parced box : boolean True boxes result as an Index-like, False returns an ndarray name : object None or string for...
Helper function for to_datetime. Adjust input argument to the specified origin Parameters ---------- arg : list, tuple, ndarray, Series, Index date to be adjusted origin : 'julian' or Timestamp origin offset for the arg unit : string passed unit from to_datetime, must be...
Convert argument to datetime. Parameters ---------- arg : integer, float, string, datetime, list, tuple, 1-d array, Series .. versionadded:: 0.18.1 or DataFrame/dict-like errors : {'ignore', 'raise', 'coerce'}, default 'raise' - If 'raise', then invalid parsing will raise...
assemble the unit specified fields from the arg (DataFrame) Return a Series for actual parsing Parameters ---------- arg : DataFrame errors : {'ignore', 'raise', 'coerce'}, default 'raise' - If 'raise', then invalid parsing will raise an exception - If 'coerce', then invalid parsin...
try to parse the YYYYMMDD/%Y%m%d format, try to deal with NaT-like, arg is a passed in as an object dtype, but could really be ints/strings with nan-like/or floats (e.g. with nan) Parameters ---------- arg : passed value errors : 'raise','ignore','coerce' def _attempt_YYYYMMDD(arg, errors): ...
Parse time strings to time objects using fixed strptime formats ("%H:%M", "%H%M", "%I:%M%p", "%I%M%p", "%H:%M:%S", "%H%M%S", "%I:%M:%S%p", "%I%M%S%p") Use infer_time_format if all the strings are in the same format to speed up conversion. Parameters ---------- arg : string in time format, ...
Return a new function that emits a deprecation warning on use. To use this method for a deprecated function, another function `alternative` with the same signature must exist. The deprecated function will emit a deprecation warning, and in the docstring it will contain the deprecation directive with th...
Decorator to deprecate a keyword argument of a function. Parameters ---------- old_arg_name : str Name of argument in function to deprecate new_arg_name : str or None Name of preferred argument in function. Use None to raise warning that ``old_arg_name`` keyword is deprecated. ...
Returns a tuple containing the paramenter list with defaults and parameter list. Examples -------- >>> def f(a, b, c=2): >>> return a * b * c >>> print(make_signature(f)) (['a', 'b', 'c=2'], ['a', 'b', 'c']) def make_signature(func): """ Returns a tuple containing the paramente...
Return a fixed frequency PeriodIndex, with day (calendar) as the default frequency Parameters ---------- start : string or period-like, default None Left bound for generating periods end : string or period-like, default None Right bound for generating periods periods : integer, ...
Create RangeIndex from a range object. def from_range(cls, data, name=None, dtype=None, **kwargs): """ Create RangeIndex from a range object. """ if not isinstance(data, range): raise TypeError( '{0}(...) must be called with object coercible to a ' 'range, {1...
Return a list of tuples of the (attr, formatted_value) def _format_attrs(self): """ Return a list of tuples of the (attr, formatted_value) """ attrs = self._get_data_as_items() if self.name is not None: attrs.append(('name', ibase.default_pprint(self.name))) ...
The minimum value of the RangeIndex def min(self, axis=None, skipna=True): """The minimum value of the RangeIndex""" nv.validate_minmax_axis(axis) return self._minmax('min')
The maximum value of the RangeIndex def max(self, axis=None, skipna=True): """The maximum value of the RangeIndex""" nv.validate_minmax_axis(axis) return self._minmax('max')
Returns the indices that would sort the index and its underlying data. Returns ------- argsorted : numpy array See Also -------- numpy.ndarray.argsort def argsort(self, args, *kwargs): """ Returns the indices that would sort the index and its ...
Determines if two Index objects contain the same elements. def equals(self, other): """ Determines if two Index objects contain the same elements. """ if isinstance(other, RangeIndex): ls = len(self) lo = len(other) return (ls == lo == 0 or ...
Form the intersection of two Index objects. Parameters ---------- other : Index or array-like sort : False or None, default False Sort the resulting index if possible .. versionadded:: 0.24.0 .. versionchanged:: 0.24.1 Changed the de...
Returns the smallest element greater than or equal to the limit def _min_fitting_element(self, lower_limit): """Returns the smallest element greater than or equal to the limit""" no_steps = -(-(lower_limit - self._start) // abs(self._step)) return self._start + abs(self._step) * no_steps
Returns the largest element smaller than or equal to the limit def _max_fitting_element(self, upper_limit): """Returns the largest element smaller than or equal to the limit""" no_steps = (upper_limit - self._start) // abs(self._step) return self._start + abs(self._step) * no_steps
Extended Euclidean algorithms to solve Bezout's identity: ax + by = gcd(x, y) Finds one particular solution for x, y: s, t Returns: gcd, s, t def _extended_gcd(self, a, b): """ Extended Euclidean algorithms to solve Bezout's identity: ax + by = gcd(x, y) ...
Form the union of two Index objects and sorts if possible Parameters ---------- other : Index or array-like sort : False or None, default None Whether to sort resulting index. ``sort=None`` returns a mononotically increasing ``RangeIndex`` if possible or a sorte...
add in numeric methods, specialized to RangeIndex def _add_numeric_methods_binary(cls): """ add in numeric methods, specialized to RangeIndex """ def _make_evaluate_binop(op, step=False): """ Parameters ---------- op : callable that accepts 2 parms ...
Convert the PandasArray to a :class:`numpy.ndarray`. By default, this requires no coercion or copying of data. Parameters ---------- dtype : numpy.dtype The NumPy dtype to pass to :func:`numpy.asarray`. copy : bool, default False Whether to copy the unde...
Glues together two sets of strings using the amount of space requested. The idea is to prettify. ---------- space : int number of spaces for padding lists : str list of str which being joined strlen : callable function used to calculate the length of each str. Needed for uni...
Perform ljust, center, rjust against string or list-like def justify(texts, max_len, mode='right'): """ Perform ljust, center, rjust against string or list-like """ if mode == 'left': return [x.ljust(max_len) for x in texts] elif mode == 'center': return [x.center(max_len) for x in ...
internal. pprinter for iterables. you should probably use pprint_thing() rather then calling this directly. bounds length of printed sequence, depending on options def _pprint_seq(seq, _nest_lvl=0, max_seq_items=None, **kwds): """ internal. pprinter for iterables. you should probably use pprint_thing(...
internal. pprinter for iterables. you should probably use pprint_thing() rather then calling this directly. def _pprint_dict(seq, _nest_lvl=0, max_seq_items=None, **kwds): """ internal. pprinter for iterables. you should probably use pprint_thing() rather then calling this directly. """ fmt = "...
This function is the sanctioned way of converting objects to a unicode representation. properly handles nested sequences containing unicode strings (unicode(object) does not) Parameters ---------- thing : anything to be formatted _nest_lvl : internal use only. pprint_thing() is mutually-re...
Return the formatted obj as a unicode string Parameters ---------- obj : object must be iterable and support __getitem__ formatter : callable string formatter for an element is_justify : boolean should justify the display name : name, optional defaults to the cla...
Return a list of tuples of the (attr, formatted_value) for common attrs, including dtype, name, length Parameters ---------- obj : object must be iterable Returns ------- list def format_object_attrs(obj): """ Return a list of tuples of the (attr, formatted_value) for ...
Load data from Google BigQuery. This function requires the `pandas-gbq package <https://pandas-gbq.readthedocs.io>`__. See the `How to authenticate with Google BigQuery <https://pandas-gbq.readthedocs.io/en/latest/howto/authentication.html>`__ guide for authentication instructions. Parameters...
Draw a matrix of scatter plots. Parameters ---------- frame : DataFrame alpha : float, optional amount of transparency applied figsize : (float,float), optional a tuple (width, height) in inches ax : Matplotlib axis object, optional grid : bool, optional setting this...
Plot a multidimensional dataset in 2D. Each Series in the DataFrame is represented as a evenly distributed slice on a circle. Each data point is rendered in the circle according to the value on each Series. Highly correlated `Series` in the `DataFrame` are placed closer on the unit circle. RadViz ...
Generate a matplotlib plot of Andrews curves, for visualising clusters of multivariate data. Andrews curves have the functional form: f(t) = x_1/sqrt(2) + x_2 sin(t) + x_3 cos(t) + x_4 sin(2t) + x_5 cos(2t) + ... Where x coefficients correspond to the values of each dimension and t is ...
Bootstrap plot on mean, median and mid-range statistics. The bootstrap plot is used to estimate the uncertainty of a statistic by relaying on random sampling with replacement [1]_. This function will generate bootstrapping plots for mean, median and mid-range statistics for the given number of samples ...
Parallel coordinates plotting. Parameters ---------- frame : DataFrame class_column : str Column name containing class names cols : list, optional A list of column names to use ax : matplotlib.axis, optional matplotlib axis object color : list or tuple, optional ...
Lag plot for time series. Parameters ---------- series : Time series lag : lag of the scatter plot, default 1 ax : Matplotlib axis object, optional kwds : Matplotlib scatter method keyword arguments, optional Returns ------- class:`matplotlib.axis.Axes` def lag_plot(series, lag=1,...
Autocorrelation plot for time series. Parameters: ----------- series: Time series ax: Matplotlib axis object, optional kwds : keywords Options to pass to matplotlib plotting method Returns: ----------- class:`matplotlib.axis.Axes` def autocorrelation_plot(series, ax=None, **kw...
Check a sequence of terms for instances of PandasObject. def _any_pandas_objects(terms): """Check a sequence of terms for instances of PandasObject.""" return any(isinstance(term.value, pd.core.generic.PandasObject) for term in terms)
Align a set of terms def _align(terms): """Align a set of terms""" try: # flatten the parse tree (a nested list, really) terms = list(com.flatten(terms)) except TypeError: # can't iterate so it must just be a constant or single variable if isinstance(terms.value, pd.core.gen...
Reconstruct an object given its type, raw value, and possibly empty (None) axes. Parameters ---------- typ : object A type obj : object The value to use in the type constructor axes : dict The axes to use to construct the resulting pandas object Returns ------- ...
Plots a Series on the given Matplotlib axes or the current axes Parameters ---------- axes : Axes series : Series Notes _____ Supports same kwargs as Axes.plot .. deprecated:: 0.23.0 Use Series.plot() instead def tsplot(series, plotf, ax=None, **kwargs): import warnings ...
Initialize axes for time-series plotting def _decorate_axes(ax, freq, kwargs): """Initialize axes for time-series plotting""" if not hasattr(ax, '_plot_data'): ax._plot_data = [] ax.freq = freq xaxis = ax.get_xaxis() xaxis.freq = freq if not hasattr(ax, 'legendlabels'): ax.lege...
Get the freq attribute of the ax object if set. Also checks shared axes (eg when using secondary yaxis, sharex=True or twinx) def _get_ax_freq(ax): """ Get the freq attribute of the ax object if set. Also checks shared axes (eg when using secondary yaxis, sharex=True or twinx) """ ax_fr...
Convert seconds to 'D days HH:MM:SS.F' def format_timedelta_ticks(x, pos, n_decimals): """ Convert seconds to 'D days HH:MM:SS.F' """ s, ns = divmod(x, 1e9) m, s = divmod(s, 60) h, m = divmod(m, 60) d, h = divmod(h, 24) decimals = int(ns * 10**(n_decimals - 9)) s = r'{:02d}:{:02d}:{...
Pretty-formats the date axis (x-axis). Major and minor ticks are automatically set for the frequency of the current underlying series. As the dynamic mode is activated by default, changing the limits of the x axis will intelligently change the positions of the ticks. def format_dateaxis(subplot, freq...
Whether all the columns in a DataFrame have the same type. Returns ------- bool Examples -------- >>> DataFrame({"A": [1, 2], "B": [3, 4]})._is_homogeneous_type True >>> DataFrame({"A": [1, 2], "B": [3.0, 4.0]})._is_homogeneous_type False ...
Return a html representation for a particular DataFrame. Mainly for IPython notebook. def _repr_html_(self): """ Return a html representation for a particular DataFrame. Mainly for IPython notebook. """ if self._info_repr(): buf = StringIO("") s...
Render a DataFrame to a console-friendly tabular output. %(shared_params)s line_width : int, optional Width to wrap a line in characters. %(returns)s See Also -------- to_html : Convert DataFrame to HTML. Examples -------- >>> d = {'co...
r""" Iterator over (column name, Series) pairs. Iterates over the DataFrame columns, returning a tuple with the column name and the content as a Series. Yields ------ label : object The column names for the DataFrame being iterated over. content : Se...
Iterate over DataFrame rows as (index, Series) pairs. Yields ------ index : label or tuple of label The index of the row. A tuple for a `MultiIndex`. data : Series The data of the row as a Series. it : generator A generator that iterates over...
Iterate over DataFrame rows as namedtuples. Parameters ---------- index : bool, default True If True, return the index as the first element of the tuple. name : str or None, default "Pandas" The name of the returned namedtuples or None to return regular ...
Compute the matrix mutiplication between the DataFrame and other. This method computes the matrix product between the DataFrame and the values of an other Series, DataFrame or a numpy array. It can also be called using ``self @ other`` in Python >= 3.5. Parameters ---------- ...
Construct DataFrame from dict of array-like or dicts. Creates DataFrame object from dictionary by columns or by index allowing dtype specification. Parameters ---------- data : dict Of the form {field : array-like} or {field : dict}. orient : {'columns', 'in...
Convert the DataFrame to a NumPy array. .. versionadded:: 0.24.0 By default, the dtype of the returned array will be the common NumPy dtype of all types in the DataFrame. For example, if the dtypes are ``float16`` and ``float32``, the results dtype will be ``float32``. This may...
Convert the DataFrame to a dictionary. The type of the key-value pairs can be customized with the parameters (see below). Parameters ---------- orient : str {'dict', 'list', 'series', 'split', 'records', 'index'} Determines the type of the values of the dictionary. ...
Write a DataFrame to a Google BigQuery table. This function requires the `pandas-gbq package <https://pandas-gbq.readthedocs.io>`__. See the `How to authenticate with Google BigQuery <https://pandas-gbq.readthedocs.io/en/latest/howto/authentication.html>`__ guide for authentica...
Convert structured or record ndarray to DataFrame. Parameters ---------- data : ndarray (structured dtype), list of tuples, dict, or DataFrame index : string, list of fields, array-like Field of array to use as the index, alternately a specific set of input label...
Convert DataFrame to a NumPy record array. Index will be included as the first field of the record array if requested. Parameters ---------- index : bool, default True Include index in resulting record array, stored in 'index' field or using the index la...
Construct a DataFrame from a list of tuples. .. deprecated:: 0.23.0 `from_items` is deprecated and will be removed in a future version. Use :meth:`DataFrame.from_dict(dict(items)) <DataFrame.from_dict>` instead. :meth:`DataFrame.from_dict(OrderedDict(items)) <DataFrame.f...
Read CSV file. .. deprecated:: 0.21.0 Use :func:`read_csv` instead. It is preferable to use the more powerful :func:`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``), especiall...
Convert to SparseDataFrame. Implement the sparse version of the DataFrame meaning that any data matching a specific value it's omitted in the representation. The sparse DataFrame allows for a more efficient storage. Parameters ---------- fill_value : float, default None...
Export DataFrame object to Stata dta format. Writes the DataFrame to a Stata dataset file. "dta" files contain a Stata dataset. Parameters ---------- fname : str, buffer or path object String, path object (pathlib.Path or py._path.local.LocalPath) or obj...
Write out the binary feather-format for DataFrames. .. versionadded:: 0.20.0 Parameters ---------- fname : str string file path def to_feather(self, fname): """ Write out the binary feather-format for DataFrames. .. versionadded:: 0.20.0 P...
Write a DataFrame to the binary parquet format. .. versionadded:: 0.21.0 This function writes the dataframe as a `parquet file <https://parquet.apache.org/>`_. You can choose different parquet backends, and have the option of compression. See :ref:`the user guide <io.parquet>` ...
Render a DataFrame as an HTML table. %(shared_params)s bold_rows : bool, default True Make the row labels bold in the output. classes : str or list or tuple, default None CSS class(es) to apply to the resulting html table. escape : bool, default True C...
Print a concise summary of a DataFrame. This method prints information about a DataFrame including the index dtype and column dtypes, non-null values and memory usage. Parameters ---------- verbose : bool, optional Whether to print the full summary. By default, the ...
Return the memory usage of each column in bytes. The memory usage can optionally include the contribution of the index and elements of `object` dtype. This value is displayed in `DataFrame.info` by default. This can be suppressed by setting ``pandas.options.display.memory_usage`` to Fa...
Transpose index and columns. Reflect the DataFrame over its main diagonal by writing rows as columns and vice-versa. The property :attr:`.T` is an accessor to the method :meth:`transpose`. Parameters ---------- copy : bool, default False If True, the underly...
Quickly retrieve single value at passed column and index. .. deprecated:: 0.21.0 Use .at[] or .iat[] accessors instead. Parameters ---------- index : row label col : column label takeable : interpret the index/col as indexers, default False Returns ...
Put single value at passed column and index. .. deprecated:: 0.21.0 Use .at[] or .iat[] accessors instead. Parameters ---------- index : row label col : column label value : scalar takeable : interpret the index/col as indexers, default False ...
Parameters ---------- i : int, slice, or sequence of integers axis : int Notes ----- If slice passed, the resulting data will be a view. def _ixs(self, i, axis=0): """ Parameters ---------- i : int, slice, or sequence of integers ...
Query the columns of a DataFrame with a boolean expression. Parameters ---------- expr : str The query string to evaluate. You can refer to variables in the environment by prefixing them with an '@' character like ``@a + b``. .. versionadded:: 0...
Evaluate a string describing operations on DataFrame columns. Operates on columns only, not specific rows or elements. This allows `eval` to run arbitrary code, which can make you vulnerable to code injection if you pass user input to this function. Parameters ---------- ...
Return a subset of the DataFrame's columns based on the column dtypes. Parameters ---------- include, exclude : scalar or list-like A selection of dtypes or strings to be included/excluded. At least one of these parameters must be supplied. Returns -----...

Insert item at selected position. Parameters ---------- loc : int item : hashable value : array_like allow_duplicates: bool If False, trying to insert non-unique item will raise def insert(self, loc, item, value, allow_duplicates=False): """ ...

Conform block manager to new index. def reindex_axis(self, new_index, axis, method=None, limit=None, fill_value=None, copy=True): """ Conform block manager to new index. """ new_index = ensure_index(new_index) new_index, indexer = self.axes[axis].reindex(new...

Parameters ---------- new_axis : Index indexer : ndarray of int64 or None axis : int fill_value : object allow_dups : bool pandas-indexer with -1's only. def reindex_indexer(self, new_axis, indexer, axis, fill_value=None, allow_dups=False...

Slice/take blocks along axis=0. Overloaded for SingleBlock Returns ------- new_blocks : list of Block def _slice_take_blocks_ax0(self, slice_or_indexer, fill_tuple=None): """ Slice/take blocks along axis=0. Overloaded for SingleBlock Returns -...

Take items along any axis. def take(self, indexer, axis=1, verify=True, convert=True): """ Take items along any axis. """ self._consolidate_inplace() indexer = (np.arange(indexer.start, indexer.stop, indexer.step, dtype='int64') if...

Return a blockmanager with all blocks unstacked. Parameters ---------- unstacker_func : callable A (partially-applied) ``pd.core.reshape._Unstacker`` class. fill_value : Any fill_value for newly introduced missing values. Returns ------- ...

Delete single item from SingleBlockManager. Ensures that self.blocks doesn't become empty. def delete(self, item): """ Delete single item from SingleBlockManager. Ensures that self.blocks doesn't become empty. """ loc = self.items.get_loc(item) self._block.dele...

Concatenate a list of SingleBlockManagers into a single SingleBlockManager. Used for pd.concat of Series objects with axis=0. Parameters ---------- to_concat : list of SingleBlockManagers new_axis : Index of the result Returns ------- SingleBloc...

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

return my self as a sparse array, do not copy by default def as_sparse_array(self, kind=None, fill_value=None, copy=False): """ return my self as a sparse array, do not copy by default """ if fill_value is None: fill_value = self.fill_value if kind is None: kind = self....

perform a reduction operation def _reduce(self, op, name, axis=0, skipna=True, numeric_only=None, filter_type=None, **kwds): """ perform a reduction operation """ return op(self.get_values(), skipna=skipna, **kwds)

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

Return an object with absolute value taken. Only applicable to objects that are all numeric Returns ------- abs: same type as caller def abs(self): """ Return an object with absolute value taken. Only applicable to objects that are all numeric Returns ...

Returns value occupying requested label, default to specified missing value if not present. Analogous to dict.get Parameters ---------- label : object Label value looking for default : object, optional Value to return if label not in index Return...

Retrieve single value at passed index label .. deprecated:: 0.21.0 Please use .at[] or .iat[] accessors. Parameters ---------- index : label takeable : interpret the index as indexers, default False Returns ------- value : scalar value def get...

Quickly set single value at passed label. If label is not contained, a new object is created with the label placed at the end of the result index .. deprecated:: 0.21.0 Please use .at[] or .iat[] accessors. Parameters ---------- label : object Parti...

Convert SparseSeries to a Series. Returns ------- s : Series def to_dense(self): """ Convert SparseSeries to a Series. Returns ------- s : Series """ return Series(self.values.to_dense(), index=self.index, name=self...

Make a copy of the SparseSeries. Only the actual sparse values need to be copied def copy(self, deep=True): """ Make a copy of the SparseSeries. Only the actual sparse values need to be copied """ # TODO: https://github.com/pandas-dev/pandas/issues/22314 # We ski...

Conform sparse values to new SparseIndex Parameters ---------- new_index : {BlockIndex, IntIndex} Returns ------- reindexed : SparseSeries def sparse_reindex(self, new_index): """ Conform sparse values to new SparseIndex Parameters ----...

Cumulative sum of non-NA/null values. When performing the cumulative summation, any non-NA/null values will be skipped. The resulting SparseSeries will preserve the locations of NaN values, but the fill value will be `np.nan` regardless. Parameters ---------- axis : {0}...

Analogous to Series.dropna. If fill_value=NaN, returns a dense Series def dropna(self, axis=0, inplace=False, **kwargs): """ Analogous to Series.dropna. If fill_value=NaN, returns a dense Series """ # TODO: make more efficient # Validate axis self._get_axis_number(axis o...

Combine Series values, choosing the calling Series's values first. Result index will be the union of the two indexes Parameters ---------- other : Series Returns ------- y : Series def combine_first(self, other): """ Combine Series values, choos...

Create a cache of unique dates from an array of dates Parameters ---------- arg : integer, float, string, datetime, list, tuple, 1-d array, Series format : string Strftime format to parse time cache : boolean True attempts to create a cache of converted values convert_listlike :...

Convert array of dates with a cache and box the result Parameters ---------- arg : integer, float, string, datetime, list, tuple, 1-d array, Series cache_array : Series Cache of converted, unique dates box : boolean True boxes result as an Index-like, False returns an ndarray er...

Return results from array_strptime if a %z or %Z directive was passed. Parameters ---------- result : ndarray int64 date representations of the dates timezones : ndarray pytz timezone objects box : boolean True boxes result as an Index-like, False returns an ndarray tz :...

Helper function for to_datetime. Performs the conversions of 1D listlike of dates Parameters ---------- arg : list, tuple, ndarray, Series, Index date to be parced box : boolean True boxes result as an Index-like, False returns an ndarray name : object None or string for...

Helper function for to_datetime. Adjust input argument to the specified origin Parameters ---------- arg : list, tuple, ndarray, Series, Index date to be adjusted origin : 'julian' or Timestamp origin offset for the arg unit : string passed unit from to_datetime, must be...

Convert argument to datetime. Parameters ---------- arg : integer, float, string, datetime, list, tuple, 1-d array, Series .. versionadded:: 0.18.1 or DataFrame/dict-like errors : {'ignore', 'raise', 'coerce'}, default 'raise' - If 'raise', then invalid parsing will raise...

assemble the unit specified fields from the arg (DataFrame) Return a Series for actual parsing Parameters ---------- arg : DataFrame errors : {'ignore', 'raise', 'coerce'}, default 'raise' - If 'raise', then invalid parsing will raise an exception - If 'coerce', then invalid parsin...

try to parse the YYYYMMDD/%Y%m%d format, try to deal with NaT-like, arg is a passed in as an object dtype, but could really be ints/strings with nan-like/or floats (e.g. with nan) Parameters ---------- arg : passed value errors : 'raise','ignore','coerce' def _attempt_YYYYMMDD(arg, errors): ...

Parse time strings to time objects using fixed strptime formats ("%H:%M", "%H%M", "%I:%M%p", "%I%M%p", "%H:%M:%S", "%H%M%S", "%I:%M:%S%p", "%I%M%S%p") Use infer_time_format if all the strings are in the same format to speed up conversion. Parameters ---------- arg : string in time format, ...

Return a new function that emits a deprecation warning on use. To use this method for a deprecated function, another function `alternative` with the same signature must exist. The deprecated function will emit a deprecation warning, and in the docstring it will contain the deprecation directive with th...

Decorator to deprecate a keyword argument of a function. Parameters ---------- old_arg_name : str Name of argument in function to deprecate new_arg_name : str or None Name of preferred argument in function. Use None to raise warning that ``old_arg_name`` keyword is deprecated. ...

Returns a tuple containing the paramenter list with defaults and parameter list. Examples -------- >>> def f(a, b, c=2): >>> return a * b * c >>> print(make_signature(f)) (['a', 'b', 'c=2'], ['a', 'b', 'c']) def make_signature(func): """ Returns a tuple containing the paramente...

Return a fixed frequency PeriodIndex, with day (calendar) as the default frequency Parameters ---------- start : string or period-like, default None Left bound for generating periods end : string or period-like, default None Right bound for generating periods periods : integer, ...

Create RangeIndex from a range object. def from_range(cls, data, name=None, dtype=None, **kwargs): """ Create RangeIndex from a range object. """ if not isinstance(data, range): raise TypeError( '{0}(...) must be called with object coercible to a ' 'range, {1...

Return a list of tuples of the (attr, formatted_value) def _format_attrs(self): """ Return a list of tuples of the (attr, formatted_value) """ attrs = self._get_data_as_items() if self.name is not None: attrs.append(('name', ibase.default_pprint(self.name))) ...

The minimum value of the RangeIndex def min(self, axis=None, skipna=True): """The minimum value of the RangeIndex""" nv.validate_minmax_axis(axis) return self._minmax('min')

The maximum value of the RangeIndex def max(self, axis=None, skipna=True): """The maximum value of the RangeIndex""" nv.validate_minmax_axis(axis) return self._minmax('max')

Returns the indices that would sort the index and its underlying data. Returns ------- argsorted : numpy array See Also -------- numpy.ndarray.argsort def argsort(self, *args, **kwargs): """ Returns the indices that would sort the index and its ...

Determines if two Index objects contain the same elements. def equals(self, other): """ Determines if two Index objects contain the same elements. """ if isinstance(other, RangeIndex): ls = len(self) lo = len(other) return (ls == lo == 0 or ...

Form the intersection of two Index objects. Parameters ---------- other : Index or array-like sort : False or None, default False Sort the resulting index if possible .. versionadded:: 0.24.0 .. versionchanged:: 0.24.1 Changed the de...

Returns the smallest element greater than or equal to the limit def _min_fitting_element(self, lower_limit): """Returns the smallest element greater than or equal to the limit""" no_steps = -(-(lower_limit - self._start) // abs(self._step)) return self._start + abs(self._step) * no_steps

Returns the largest element smaller than or equal to the limit def _max_fitting_element(self, upper_limit): """Returns the largest element smaller than or equal to the limit""" no_steps = (upper_limit - self._start) // abs(self._step) return self._start + abs(self._step) * no_steps

Extended Euclidean algorithms to solve Bezout's identity: a*x + b*y = gcd(x, y) Finds one particular solution for x, y: s, t Returns: gcd, s, t def _extended_gcd(self, a, b): """ Extended Euclidean algorithms to solve Bezout's identity: a*x + b*y = gcd(x, y) ...

Form the union of two Index objects and sorts if possible Parameters ---------- other : Index or array-like sort : False or None, default None Whether to sort resulting index. ``sort=None`` returns a mononotically increasing ``RangeIndex`` if possible or a sorte...

add in numeric methods, specialized to RangeIndex def _add_numeric_methods_binary(cls): """ add in numeric methods, specialized to RangeIndex """ def _make_evaluate_binop(op, step=False): """ Parameters ---------- op : callable that accepts 2 parms ...

Convert the PandasArray to a :class:`numpy.ndarray`. By default, this requires no coercion or copying of data. Parameters ---------- dtype : numpy.dtype The NumPy dtype to pass to :func:`numpy.asarray`. copy : bool, default False Whether to copy the unde...

Glues together two sets of strings using the amount of space requested. The idea is to prettify. ---------- space : int number of spaces for padding lists : str list of str which being joined strlen : callable function used to calculate the length of each str. Needed for uni...

Perform ljust, center, rjust against string or list-like def justify(texts, max_len, mode='right'): """ Perform ljust, center, rjust against string or list-like """ if mode == 'left': return [x.ljust(max_len) for x in texts] elif mode == 'center': return [x.center(max_len) for x in ...

internal. pprinter for iterables. you should probably use pprint_thing() rather then calling this directly. bounds length of printed sequence, depending on options def _pprint_seq(seq, _nest_lvl=0, max_seq_items=None, **kwds): """ internal. pprinter for iterables. you should probably use pprint_thing(...

internal. pprinter for iterables. you should probably use pprint_thing() rather then calling this directly. def _pprint_dict(seq, _nest_lvl=0, max_seq_items=None, **kwds): """ internal. pprinter for iterables. you should probably use pprint_thing() rather then calling this directly. """ fmt = "...

This function is the sanctioned way of converting objects to a unicode representation. properly handles nested sequences containing unicode strings (unicode(object) does not) Parameters ---------- thing : anything to be formatted _nest_lvl : internal use only. pprint_thing() is mutually-re...

Return the formatted obj as a unicode string Parameters ---------- obj : object must be iterable and support __getitem__ formatter : callable string formatter for an element is_justify : boolean should justify the display name : name, optional defaults to the cla...

Return a list of tuples of the (attr, formatted_value) for common attrs, including dtype, name, length Parameters ---------- obj : object must be iterable Returns ------- list def format_object_attrs(obj): """ Return a list of tuples of the (attr, formatted_value) for ...

Load data from Google BigQuery. This function requires the `pandas-gbq package <https://pandas-gbq.readthedocs.io>`__. See the `How to authenticate with Google BigQuery <https://pandas-gbq.readthedocs.io/en/latest/howto/authentication.html>`__ guide for authentication instructions. Parameters...

Draw a matrix of scatter plots. Parameters ---------- frame : DataFrame alpha : float, optional amount of transparency applied figsize : (float,float), optional a tuple (width, height) in inches ax : Matplotlib axis object, optional grid : bool, optional setting this...

Plot a multidimensional dataset in 2D. Each Series in the DataFrame is represented as a evenly distributed slice on a circle. Each data point is rendered in the circle according to the value on each Series. Highly correlated `Series` in the `DataFrame` are placed closer on the unit circle. RadViz ...

Generate a matplotlib plot of Andrews curves, for visualising clusters of multivariate data. Andrews curves have the functional form: f(t) = x_1/sqrt(2) + x_2 sin(t) + x_3 cos(t) + x_4 sin(2t) + x_5 cos(2t) + ... Where x coefficients correspond to the values of each dimension and t is ...

Bootstrap plot on mean, median and mid-range statistics. The bootstrap plot is used to estimate the uncertainty of a statistic by relaying on random sampling with replacement [1]_. This function will generate bootstrapping plots for mean, median and mid-range statistics for the given number of samples ...

Parallel coordinates plotting. Parameters ---------- frame : DataFrame class_column : str Column name containing class names cols : list, optional A list of column names to use ax : matplotlib.axis, optional matplotlib axis object color : list or tuple, optional ...

Lag plot for time series. Parameters ---------- series : Time series lag : lag of the scatter plot, default 1 ax : Matplotlib axis object, optional kwds : Matplotlib scatter method keyword arguments, optional Returns ------- class:`matplotlib.axis.Axes` def lag_plot(series, lag=1,...

Autocorrelation plot for time series. Parameters: ----------- series: Time series ax: Matplotlib axis object, optional kwds : keywords Options to pass to matplotlib plotting method Returns: ----------- class:`matplotlib.axis.Axes` def autocorrelation_plot(series, ax=None, **kw...

Check a sequence of terms for instances of PandasObject. def _any_pandas_objects(terms): """Check a sequence of terms for instances of PandasObject.""" return any(isinstance(term.value, pd.core.generic.PandasObject) for term in terms)

Align a set of terms def _align(terms): """Align a set of terms""" try: # flatten the parse tree (a nested list, really) terms = list(com.flatten(terms)) except TypeError: # can't iterate so it must just be a constant or single variable if isinstance(terms.value, pd.core.gen...

Reconstruct an object given its type, raw value, and possibly empty (None) axes. Parameters ---------- typ : object A type obj : object The value to use in the type constructor axes : dict The axes to use to construct the resulting pandas object Returns ------- ...

Plots a Series on the given Matplotlib axes or the current axes Parameters ---------- axes : Axes series : Series Notes _____ Supports same kwargs as Axes.plot .. deprecated:: 0.23.0 Use Series.plot() instead def tsplot(series, plotf, ax=None, **kwargs): import warnings ...

Initialize axes for time-series plotting def _decorate_axes(ax, freq, kwargs): """Initialize axes for time-series plotting""" if not hasattr(ax, '_plot_data'): ax._plot_data = [] ax.freq = freq xaxis = ax.get_xaxis() xaxis.freq = freq if not hasattr(ax, 'legendlabels'): ax.lege...

Get the freq attribute of the ax object if set. Also checks shared axes (eg when using secondary yaxis, sharex=True or twinx) def _get_ax_freq(ax): """ Get the freq attribute of the ax object if set. Also checks shared axes (eg when using secondary yaxis, sharex=True or twinx) """ ax_fr...

Convert seconds to 'D days HH:MM:SS.F' def format_timedelta_ticks(x, pos, n_decimals): """ Convert seconds to 'D days HH:MM:SS.F' """ s, ns = divmod(x, 1e9) m, s = divmod(s, 60) h, m = divmod(m, 60) d, h = divmod(h, 24) decimals = int(ns * 10**(n_decimals - 9)) s = r'{:02d}:{:02d}:{...

Pretty-formats the date axis (x-axis). Major and minor ticks are automatically set for the frequency of the current underlying series. As the dynamic mode is activated by default, changing the limits of the x axis will intelligently change the positions of the ticks. def format_dateaxis(subplot, freq...

Whether all the columns in a DataFrame have the same type. Returns ------- bool Examples -------- >>> DataFrame({"A": [1, 2], "B": [3, 4]})._is_homogeneous_type True >>> DataFrame({"A": [1, 2], "B": [3.0, 4.0]})._is_homogeneous_type False ...

Return a html representation for a particular DataFrame. Mainly for IPython notebook. def _repr_html_(self): """ Return a html representation for a particular DataFrame. Mainly for IPython notebook. """ if self._info_repr(): buf = StringIO("") s...

Render a DataFrame to a console-friendly tabular output. %(shared_params)s line_width : int, optional Width to wrap a line in characters. %(returns)s See Also -------- to_html : Convert DataFrame to HTML. Examples -------- >>> d = {'co...

r""" Iterator over (column name, Series) pairs. Iterates over the DataFrame columns, returning a tuple with the column name and the content as a Series. Yields ------ label : object The column names for the DataFrame being iterated over. content : Se...

Iterate over DataFrame rows as (index, Series) pairs. Yields ------ index : label or tuple of label The index of the row. A tuple for a `MultiIndex`. data : Series The data of the row as a Series. it : generator A generator that iterates over...

Iterate over DataFrame rows as namedtuples. Parameters ---------- index : bool, default True If True, return the index as the first element of the tuple. name : str or None, default "Pandas" The name of the returned namedtuples or None to return regular ...

Compute the matrix mutiplication between the DataFrame and other. This method computes the matrix product between the DataFrame and the values of an other Series, DataFrame or a numpy array. It can also be called using ``self @ other`` in Python >= 3.5. Parameters ---------- ...

Construct DataFrame from dict of array-like or dicts. Creates DataFrame object from dictionary by columns or by index allowing dtype specification. Parameters ---------- data : dict Of the form {field : array-like} or {field : dict}. orient : {'columns', 'in...

Convert the DataFrame to a NumPy array. .. versionadded:: 0.24.0 By default, the dtype of the returned array will be the common NumPy dtype of all types in the DataFrame. For example, if the dtypes are ``float16`` and ``float32``, the results dtype will be ``float32``. This may...

Convert the DataFrame to a dictionary. The type of the key-value pairs can be customized with the parameters (see below). Parameters ---------- orient : str {'dict', 'list', 'series', 'split', 'records', 'index'} Determines the type of the values of the dictionary. ...

Write a DataFrame to a Google BigQuery table. This function requires the `pandas-gbq package <https://pandas-gbq.readthedocs.io>`__. See the `How to authenticate with Google BigQuery <https://pandas-gbq.readthedocs.io/en/latest/howto/authentication.html>`__ guide for authentica...

Convert structured or record ndarray to DataFrame. Parameters ---------- data : ndarray (structured dtype), list of tuples, dict, or DataFrame index : string, list of fields, array-like Field of array to use as the index, alternately a specific set of input label...

Convert DataFrame to a NumPy record array. Index will be included as the first field of the record array if requested. Parameters ---------- index : bool, default True Include index in resulting record array, stored in 'index' field or using the index la...

Construct a DataFrame from a list of tuples. .. deprecated:: 0.23.0 `from_items` is deprecated and will be removed in a future version. Use :meth:`DataFrame.from_dict(dict(items)) <DataFrame.from_dict>` instead. :meth:`DataFrame.from_dict(OrderedDict(items)) <DataFrame.f...

Read CSV file. .. deprecated:: 0.21.0 Use :func:`read_csv` instead. It is preferable to use the more powerful :func:`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``), especiall...

Convert to SparseDataFrame. Implement the sparse version of the DataFrame meaning that any data matching a specific value it's omitted in the representation. The sparse DataFrame allows for a more efficient storage. Parameters ---------- fill_value : float, default None...

Export DataFrame object to Stata dta format. Writes the DataFrame to a Stata dataset file. "dta" files contain a Stata dataset. Parameters ---------- fname : str, buffer or path object String, path object (pathlib.Path or py._path.local.LocalPath) or obj...

Write out the binary feather-format for DataFrames. .. versionadded:: 0.20.0 Parameters ---------- fname : str string file path def to_feather(self, fname): """ Write out the binary feather-format for DataFrames. .. versionadded:: 0.20.0 P...

Write a DataFrame to the binary parquet format. .. versionadded:: 0.21.0 This function writes the dataframe as a `parquet file <https://parquet.apache.org/>`_. You can choose different parquet backends, and have the option of compression. See :ref:`the user guide <io.parquet>` ...

Render a DataFrame as an HTML table. %(shared_params)s bold_rows : bool, default True Make the row labels bold in the output. classes : str or list or tuple, default None CSS class(es) to apply to the resulting html table. escape : bool, default True C...

Print a concise summary of a DataFrame. This method prints information about a DataFrame including the index dtype and column dtypes, non-null values and memory usage. Parameters ---------- verbose : bool, optional Whether to print the full summary. By default, the ...

Return the memory usage of each column in bytes. The memory usage can optionally include the contribution of the index and elements of `object` dtype. This value is displayed in `DataFrame.info` by default. This can be suppressed by setting ``pandas.options.display.memory_usage`` to Fa...

Transpose index and columns. Reflect the DataFrame over its main diagonal by writing rows as columns and vice-versa. The property :attr:`.T` is an accessor to the method :meth:`transpose`. Parameters ---------- copy : bool, default False If True, the underly...

Quickly retrieve single value at passed column and index. .. deprecated:: 0.21.0 Use .at[] or .iat[] accessors instead. Parameters ---------- index : row label col : column label takeable : interpret the index/col as indexers, default False Returns ...

Put single value at passed column and index. .. deprecated:: 0.21.0 Use .at[] or .iat[] accessors instead. Parameters ---------- index : row label col : column label value : scalar takeable : interpret the index/col as indexers, default False ...

Parameters ---------- i : int, slice, or sequence of integers axis : int Notes ----- If slice passed, the resulting data will be a view. def _ixs(self, i, axis=0): """ Parameters ---------- i : int, slice, or sequence of integers ...

Query the columns of a DataFrame with a boolean expression. Parameters ---------- expr : str The query string to evaluate. You can refer to variables in the environment by prefixing them with an '@' character like ``@a + b``. .. versionadded:: 0...

Evaluate a string describing operations on DataFrame columns. Operates on columns only, not specific rows or elements. This allows `eval` to run arbitrary code, which can make you vulnerable to code injection if you pass user input to this function. Parameters ---------- ...

Return a subset of the DataFrame's columns based on the column dtypes. Parameters ---------- include, exclude : scalar or list-like A selection of dtypes or strings to be included/excluded. At least one of these parameters must be supplied. Returns -----...