Batch

Overview: Batch

class Batch(items: Iterator[Tuple[Hashable, Union[static_frame.core.frame.Frame, static_frame.core.series.Series]]], *, name: Optional[Hashable] = None, config: Union[static_frame.core.store.StoreConfig, Mapping[Any, static_frame.core.store.StoreConfig], None, static_frame.core.store.StoreConfigMap] = None, max_workers: Optional[int] = None, chunksize: int = 1, use_threads: bool = False)[source]

A lazy, sequentially evaluated container of Frame that broadcasts operations on contained Frame by return new Batch instances. Full evaluation of operations only occurs when iterating or calling an exporter.

Batch: Constructor

Overview: Batch: Constructor

Batch.__init__(items: Iterator[Tuple[Hashable, Union[static_frame.core.frame.Frame, static_frame.core.series.Series]]], *, name: Optional[Hashable] = None, config: Union[static_frame.core.store.StoreConfig, Mapping[Any, static_frame.core.store.StoreConfig], None, static_frame.core.store.StoreConfigMap] = None, max_workers: Optional[int] = None, chunksize: int = 1, use_threads: bool = False)[source]

Default constructor of a Batch.

Parameters
  • name – A hashable object to label the container.

  • config – A StoreConfig, or a mapping of label ot StoreConfig

  • max_workers – Number of parallel executors, as passed to the Thread- or ProcessPoolExecutor; None defaults to the max number of machine processes.

  • chunksize – Units of work per executor, as passed to the Thread- or ProcessPoolExecutor.

  • use_threads – Use the ThreadPoolExecutor instead of the ProcessPoolExecutor.

classmethod Batch.from_frames(frames: Iterable[static_frame.core.frame.Frame], *, name: Optional[Hashable] = None, config: Union[static_frame.core.store.StoreConfig, Mapping[Any, static_frame.core.store.StoreConfig], None, static_frame.core.store.StoreConfigMap] = None, max_workers: Optional[int] = None, chunksize: int = 1, use_threads: bool = False) static_frame.core.batch.Batch[source]

Return a Batch from an iterable of Frame; labels will be drawn from Frame.name.

classmethod Batch.from_hdf5(fp: Union[str, os.PathLike], *, config: Union[static_frame.core.store.StoreConfig, Mapping[Any, static_frame.core.store.StoreConfig], None, static_frame.core.store.StoreConfigMap] = None, max_workers: Optional[int] = None, chunksize: int = 1, use_threads: bool = False) static_frame.core.batch.Batch[source]

Given a file path to a HDF5 Batch store, return a Batch instance.

Parameters
  • fp – A string file path or Path instance.

  • config – A StoreConfig, or a mapping of label ot StoreConfig

  • max_workers – Number of parallel executors, as passed to the Thread- or ProcessPoolExecutor; None defaults to the max number of machine processes.

  • chunksize – Units of work per executor, as passed to the Thread- or ProcessPoolExecutor.

  • use_threads – Use the ThreadPoolExecutor instead of the ProcessPoolExecutor.

classmethod Batch.from_sqlite(fp: Union[str, os.PathLike], *, config: Union[static_frame.core.store.StoreConfig, Mapping[Any, static_frame.core.store.StoreConfig], None, static_frame.core.store.StoreConfigMap] = None, max_workers: Optional[int] = None, chunksize: int = 1, use_threads: bool = False) static_frame.core.batch.Batch[source]

Given a file path to an SQLite Batch store, return a Batch instance.

Parameters
  • fp – A string file path or Path instance.

  • config – A StoreConfig, or a mapping of label ot StoreConfig

  • max_workers – Number of parallel executors, as passed to the Thread- or ProcessPoolExecutor; None defaults to the max number of machine processes.

  • chunksize – Units of work per executor, as passed to the Thread- or ProcessPoolExecutor.

  • use_threads – Use the ThreadPoolExecutor instead of the ProcessPoolExecutor.

classmethod Batch.from_xlsx(fp: Union[str, os.PathLike], *, config: Union[static_frame.core.store.StoreConfig, Mapping[Any, static_frame.core.store.StoreConfig], None, static_frame.core.store.StoreConfigMap] = None, max_workers: Optional[int] = None, chunksize: int = 1, use_threads: bool = False) static_frame.core.batch.Batch[source]

Given a file path to an XLSX Batch store, return a Batch instance.

Parameters
  • fp – A string file path or Path instance.

  • config – A StoreConfig, or a mapping of label ot StoreConfig

  • max_workers – Number of parallel executors, as passed to the Thread- or ProcessPoolExecutor; None defaults to the max number of machine processes.

  • chunksize – Units of work per executor, as passed to the Thread- or ProcessPoolExecutor.

  • use_threads – Use the ThreadPoolExecutor instead of the ProcessPoolExecutor.

classmethod Batch.from_zip_csv(fp: Union[str, os.PathLike], *, config: Union[static_frame.core.store.StoreConfig, Mapping[Any, static_frame.core.store.StoreConfig], None, static_frame.core.store.StoreConfigMap] = None, max_workers: Optional[int] = None, chunksize: int = 1, use_threads: bool = False) static_frame.core.batch.Batch[source]

Given a file path to zipped CSV Batch store, return a Batch instance.

Parameters
  • fp – A string file path or Path instance.

  • config – A StoreConfig, or a mapping of label ot StoreConfig

  • max_workers – Number of parallel executors, as passed to the Thread- or ProcessPoolExecutor; None defaults to the max number of machine processes.

  • chunksize – Units of work per executor, as passed to the Thread- or ProcessPoolExecutor.

  • use_threads – Use the ThreadPoolExecutor instead of the ProcessPoolExecutor.

classmethod Batch.from_zip_npz(fp: Union[str, os.PathLike], *, config: Union[static_frame.core.store.StoreConfig, Mapping[Any, static_frame.core.store.StoreConfig], None, static_frame.core.store.StoreConfigMap] = None, max_workers: Optional[int] = None, chunksize: int = 1, use_threads: bool = False) static_frame.core.batch.Batch[source]

Given a file path to zipped NPZ Batch store, return a Batch instance.

Parameters
  • fp – A string file path or Path instance.

  • config – A StoreConfig, or a mapping of label ot StoreConfig

  • max_workers – Number of parallel executors, as passed to the Thread- or ProcessPoolExecutor; None defaults to the max number of machine processes.

  • chunksize – Units of work per executor, as passed to the Thread- or ProcessPoolExecutor.

  • use_threads – Use the ThreadPoolExecutor instead of the ProcessPoolExecutor.

classmethod Batch.from_zip_parquet(fp: Union[str, os.PathLike], *, config: Union[static_frame.core.store.StoreConfig, Mapping[Any, static_frame.core.store.StoreConfig], None, static_frame.core.store.StoreConfigMap] = None, max_workers: Optional[int] = None, chunksize: int = 1, use_threads: bool = False) static_frame.core.batch.Batch[source]

Given a file path to zipped parquet Batch store, return a Batch instance.

Parameters
  • fp – A string file path or Path instance.

  • config – A StoreConfig, or a mapping of label ot StoreConfig

  • max_workers – Number of parallel executors, as passed to the Thread- or ProcessPoolExecutor; None defaults to the max number of machine processes.

  • chunksize – Units of work per executor, as passed to the Thread- or ProcessPoolExecutor.

  • use_threads – Use the ThreadPoolExecutor instead of the ProcessPoolExecutor.

classmethod Batch.from_zip_pickle(fp: Union[str, os.PathLike], *, config: Union[static_frame.core.store.StoreConfig, Mapping[Any, static_frame.core.store.StoreConfig], None, static_frame.core.store.StoreConfigMap] = None, max_workers: Optional[int] = None, chunksize: int = 1, use_threads: bool = False) static_frame.core.batch.Batch[source]

Given a file path to zipped pickle Batch store, return a Batch instance.

Parameters
  • fp – A string file path or Path instance.

  • config – A StoreConfig, or a mapping of label ot StoreConfig

  • max_workers – Number of parallel executors, as passed to the Thread- or ProcessPoolExecutor; None defaults to the max number of machine processes.

  • chunksize – Units of work per executor, as passed to the Thread- or ProcessPoolExecutor.

  • use_threads – Use the ThreadPoolExecutor instead of the ProcessPoolExecutor.

classmethod Batch.from_zip_tsv(fp: Union[str, os.PathLike], *, config: Union[static_frame.core.store.StoreConfig, Mapping[Any, static_frame.core.store.StoreConfig], None, static_frame.core.store.StoreConfigMap] = None, max_workers: Optional[int] = None, chunksize: int = 1, use_threads: bool = False) static_frame.core.batch.Batch[source]

Given a file path to zipped TSV Batch store, return a Batch instance.

Parameters
  • fp – A string file path or Path instance.

  • config – A StoreConfig, or a mapping of label ot StoreConfig

  • max_workers – Number of parallel executors, as passed to the Thread- or ProcessPoolExecutor; None defaults to the max number of machine processes.

  • chunksize – Units of work per executor, as passed to the Thread- or ProcessPoolExecutor.

  • use_threads – Use the ThreadPoolExecutor instead of the ProcessPoolExecutor.

Batch: Constructor | Exporter | Attribute | Method | Dictionary-Like | Display | Selector | Operator Binary | Operator Unary | Accessor Datetime | Accessor String | Accessor Transpose | Accessor Fill Value | Accessor Regular Expression

Batch: Exporter

Overview: Batch: Exporter

Batch.to_bus(*, index_constructor: Optional[Callable[[...], static_frame.core.index_base.IndexBase]] = None) static_frame.core.bus.Bus[source]

Realize the Batch as an Bus. Note that, as a Bus must have all labels (even if Frame are loaded lazily), this Batch will be exhausted.

Batch.to_frame(*, axis: int = 0, union: bool = True, index: Optional[Union[static_frame.core.index_base.IndexBase, Iterable[Hashable], Iterable[Sequence[Hashable]], Type[static_frame.core.index_auto.IndexAutoFactory]]] = None, columns: Optional[Union[static_frame.core.index_base.IndexBase, Iterable[Hashable], Iterable[Sequence[Hashable]], Type[static_frame.core.index_auto.IndexAutoFactory]]] = None, name: Optional[Hashable] = None, fill_value: object = nan, consolidate_blocks: bool = False) static_frame.core.frame.Frame[source]

Consolidate stored Frame into a new Frame using the stored labels as the index on the provided axis using Frame.from_concat. This assumes that that the contained Frame have been reduced to a single dimension along the provided axis.

Batch.to_hdf5(fp: Union[str, os.PathLike], *, config: Union[static_frame.core.store.StoreConfig, Mapping[Any, static_frame.core.store.StoreConfig], None, static_frame.core.store.StoreConfigMap] = None) None

Write the complete Bus as an HDF5 table.

Parameters
Batch.to_series(*, dtype: Optional[Union[str, numpy.dtype, type]] = None, name: Optional[Hashable] = None, index_constructor: Optional[Callable[[...], static_frame.core.index_base.IndexBase]] = None) static_frame.core.series.Series[source]

Consolidate stored values into a new Series using the stored labels as the index.

Batch.to_sqlite(fp: Union[str, os.PathLike], *, config: Union[static_frame.core.store.StoreConfig, Mapping[Any, static_frame.core.store.StoreConfig], None, static_frame.core.store.StoreConfigMap] = None) None

Write the complete Bus as an SQLite database file.

Parameters
Batch.to_visidata() None

Open an interactive VisiData session.

Batch.to_xlsx(fp: Union[str, os.PathLike], *, config: Union[static_frame.core.store.StoreConfig, Mapping[Any, static_frame.core.store.StoreConfig], None, static_frame.core.store.StoreConfigMap] = None) None

Write the complete Bus as a XLSX workbook.

Parameters
Batch.to_zip_csv(fp: Union[str, os.PathLike], *, config: Union[static_frame.core.store.StoreConfig, Mapping[Any, static_frame.core.store.StoreConfig], None, static_frame.core.store.StoreConfigMap] = None) None

Write the complete Bus as a zipped archive of CSV files.

Parameters
Batch.to_zip_npz(fp: Union[str, os.PathLike], *, config: Union[static_frame.core.store.StoreConfig, Mapping[Any, static_frame.core.store.StoreConfig], None, static_frame.core.store.StoreConfigMap] = None) None

Write the complete Bus as a zipped archive of NPZ files.

Parameters
Batch.to_zip_parquet(fp: Union[str, os.PathLike], *, config: Union[static_frame.core.store.StoreConfig, Mapping[Any, static_frame.core.store.StoreConfig], None, static_frame.core.store.StoreConfigMap] = None) None

Write the complete Bus as a zipped archive of parquet files.

Parameters
Batch.to_zip_pickle(fp: Union[str, os.PathLike], *, config: Union[static_frame.core.store.StoreConfig, Mapping[Any, static_frame.core.store.StoreConfig], None, static_frame.core.store.StoreConfigMap] = None) None

Write the complete Bus as a zipped archive of pickles.

Parameters
Batch.to_zip_tsv(fp: Union[str, os.PathLike], *, config: Union[static_frame.core.store.StoreConfig, Mapping[Any, static_frame.core.store.StoreConfig], None, static_frame.core.store.StoreConfigMap] = None) None

Write the complete Bus as a zipped archive of TSV files.

Parameters

Batch: Constructor | Exporter | Attribute | Method | Dictionary-Like | Display | Selector | Operator Binary | Operator Unary | Accessor Datetime | Accessor String | Accessor Transpose | Accessor Fill Value | Accessor Regular Expression

Batch: Attribute

Overview: Batch: Attribute

Batch.STATIC: bool = True
Batch.T

Transpose. Return a Frame with index as columns and vice versa.

Batch.name

A hashable label attached to this container.

Returns

Hashable

Batch.shapes

A Series describing the shape of each iterated Frame.

Returns

tp.Tuple[int]

Batch.via_container

Return a new Batch with all values wrapped in either a Frame or Series.

Batch: Constructor | Exporter | Attribute | Method | Dictionary-Like | Display | Selector | Operator Binary | Operator Unary | Accessor Datetime | Accessor String | Accessor Transpose | Accessor Fill Value | Accessor Regular Expression

Batch: Method

Overview: Batch: Method

Batch.__array__(dtype: Optional[numpy.dtype] = None) numpy.ndarray

Support the __array__ interface, returning a 1D array of values.

Batch.__array_ufunc__(ufunc: Callable[[...], numpy.ndarray], method: str, *args: Any, **kwargs: Any) static_frame.core.container.ContainerOperand

Support for NumPy elements or arrays on the left hand of binary operators.

Batch.__bool__() bool

Raises ValueError to prohibit ambiguous use of truethy evaluation.

Batch.__round__(decimals: int = 0) static_frame.core.batch.Batch[source]

Return a Batch with contained Frame rounded to the given decimals. Negative decimals round to the left of the decimal point.

Parameters

decimals – number of decimals to round to.

Batch.all(axis: int = 0, skipna: bool = True, out: Optional[numpy.ndarray] = None) Any

Logical and over values along the specified axis.

Parameters
  • axis – Axis, defaulting to axis 0.

  • skipna – Skip missing (NaN) values, defaulting to True.

Batch.any(axis: int = 0, skipna: bool = True, out: Optional[numpy.ndarray] = None) Any

Logical or over values along the specified axis.

Parameters
  • axis – Axis, defaulting to axis 0.

  • skipna – Skip missing (NaN) values, defaulting to True.

Batch.apply(func: Callable[[...], Any]) static_frame.core.batch.Batch[source]

Apply a function to each Frame contained in this Frame, where a function is given the Frame as an argument.

Batch.apply_except(func: Callable[[...], Any], exception: Type[Exception]) static_frame.core.batch.Batch[source]

Apply a function to each Frame contained in this Frame, where a function is given the Frame as an argument. Exceptions raised that matching the except argument will be silenced.

Batch.apply_items(func: Callable[[...], Any]) static_frame.core.batch.Batch[source]

Apply a function to each Frame contained in this Frame, where a function is given the pair of label, Frame as an argument.

Batch.apply_items_except(func: Callable[[...], Any], exception: Type[Exception]) static_frame.core.batch.Batch[source]

Apply a function to each Frame contained in this Frame, where a function is given the pair of label, Frame as an argument. Exceptions raised that matching the except argument will be silenced.

Batch.clip(*, lower: Optional[Union[float, static_frame.core.series.Series, static_frame.core.frame.Frame]] = None, upper: Optional[Union[float, static_frame.core.series.Series, static_frame.core.frame.Frame]] = None, axis: Optional[int] = None) static_frame.core.batch.Batch[source]

Apply a clip operation to this Batch. Note that clip operations can be applied to object types, but cannot be applied to non-numerical objects (e.g., strings, None)

Parameters
Batch.count(*, skipna: bool = True, axis: int = 0) static_frame.core.batch.Batch[source]

Apply count on contained Frames.

Batch.cov(*, axis: int = 1, ddof: int = 1) static_frame.core.batch.Batch[source]

Compute a covariance matrix.

Parameters
  • axis – if 0, each row represents a variable, with observations as columns; if 1, each column represents a variable, with observations as rows. Defaults to 1.

  • ddof – Delta degrees of freedom, defaults to 1.

Batch.cumprod(axis: int = 0, skipna: bool = True) Any

Return the cumulative product over the specified axis.

Parameters
  • axis – Axis, defaulting to axis 0.

  • skipna – Skip missing (NaN) values, defaulting to True.

Batch.cumsum(axis: int = 0, skipna: bool = True) Any

Return the cumulative sum over the specified axis.

Parameters
  • axis – Axis, defaulting to axis 0.

  • skipna – Skip missing (NaN) values, defaulting to True.

Batch.drop_duplicated(*, axis: int = 0, exclude_first: bool = False, exclude_last: bool = False) static_frame.core.batch.Batch[source]

Return a Batch with contained Frame with duplicated rows (axis 0) or columns (axis 1) removed. All values in the row or column are compared to determine duplication.

Parameters
  • axis – Integer specifying axis, where 0 is rows and 1 is columns. Axis 0 is set by default.

  • exclude_first – Boolean to select if the first duplicated value is excluded.

  • exclude_last – Boolean to select if the last duplicated value is excluded.

Batch.dropfalsy(axis: int = 0, condition: Callable[[numpy.ndarray], bool] = <function all>) static_frame.core.batch.Batch[source]

Return a Batch with contained Frame after removing rows (axis 0) or columns (axis 1) where any or all values are NA (NaN or None). The condition is determined by a NumPy ufunc that process the Boolean array returned by isna(); the default is np.all.

Parameters
  • axis

  • condition

Batch.dropna(axis: int = 0, condition: Callable[[numpy.ndarray], bool] = <function all>) static_frame.core.batch.Batch[source]

Return a Batch with contained Frame after removing rows (axis 0) or columns (axis 1) where any or all values are NA (NaN or None). The condition is determined by a NumPy ufunc that process the Boolean array returned by isna(); the default is np.all.

Parameters
  • axis

  • condition

Batch.duplicated(*, axis: int = 0, exclude_first: bool = False, exclude_last: bool = False) static_frame.core.batch.Batch[source]

Return an axis-sized Boolean Series that shows True for all rows (axis 0) or columns (axis 1) duplicated.

Parameters
  • axis – Integer specifying axis, where 0 is rows and 1 is columns. Axis 0 is set by default.

  • exclude_first – Boolean to select if the first duplicated value is excluded.

  • exclude_last – Boolean to select if the last duplicated value is excluded.

Batch.equals(other: Any, *, compare_name: bool = False, compare_dtype: bool = False, compare_class: bool = False, skipna: bool = True) bool
Batch.fillfalsy(value: Any) static_frame.core.batch.Batch[source]

Return a new Batch with contained Frame after filling falsy values with the provided value.

Batch.fillfalsy_backward(limit: int = 0, *, axis: int = 0) static_frame.core.batch.Batch[source]

Return a new Batch with contained Frame after filling backward falsy values with the first observed value.

Parameters
  • {limit}

  • {axis}

Batch.fillfalsy_forward(limit: int = 0, axis: int = 0) static_frame.core.batch.Batch[source]

Return a new Batch with contained Frame after filling forward falsy values with the last observed value.

Parameters
  • {limit}

  • {axis}

Batch.fillfalsy_leading(value: Any, *, axis: int = 0) static_frame.core.batch.Batch[source]

Return a new Batch with contained Frame after filling leading (and only leading) falsy values with the provided value.

Parameters
  • {value}

  • {axis}

Batch.fillfalsy_trailing(value: Any, *, axis: int = 0) static_frame.core.batch.Batch[source]

Return a new Batch with contained Frame after filling trailing (and only trailing) falsy values with the provided value.

Parameters
  • {value}

  • {axis}

Batch.fillna(value: Any) static_frame.core.batch.Batch[source]

Return a new Batch with contained Frame after filling null (NaN or None) with the provided value.

Batch.fillna_backward(limit: int = 0, *, axis: int = 0) static_frame.core.batch.Batch[source]

Return a new Batch with contained Frame after filling backward null (NaN or None) with the first observed value.

Parameters
  • {limit}

  • {axis}

Batch.fillna_forward(limit: int = 0, *, axis: int = 0) static_frame.core.batch.Batch[source]

Return a new Batch with contained Frame after filling forward null (NaN or None) with the last observed value.

Parameters
  • {limit}

  • {axis}

Batch.fillna_leading(value: Any, *, axis: int = 0) static_frame.core.batch.Batch[source]

Return a new Batch with contained Frame after filling leading (and only leading) null (NaN or None) with the provided value.

Parameters
  • {value}

  • {axis}

Batch.fillna_trailing(value: Any, *, axis: int = 0) static_frame.core.batch.Batch[source]

Return a new Batch with contained Frame after filling trailing (and only trailing) null (NaN or None) with the provided value.

Parameters
  • {value}

  • {axis}

Batch.head(count: int = 5) static_frame.core.batch.Batch[source]

Return a Batch consisting only of the top elements as specified by count.

Parameters

count – Number of elements to be returned from the top of the Batch

Batch.iloc_max(*, skipna: bool = True, axis: int = 0) static_frame.core.batch.Batch[source]

Return the integer indices corresponding to the maximum values found.

Parameters
  • skipna – if True, NaN or None values will be ignored; if False, a found NaN will propagate.

  • axis – Axis upon which to evaluate contiguous missing values, where 0 is vertically (between row values) and 1 is horizontally (between column values).

Batch.iloc_min(*, skipna: bool = True, axis: int = 0) static_frame.core.batch.Batch[source]

Return the integer indices corresponding to the minimum values found.

Parameters
  • skipna – if True, NaN or None values will be ignored; if False, a found NaN will propagate.

  • axis – Axis upon which to evaluate contiguous missing values, where 0 is vertically (between row values) and 1 is horizontally (between column values).

Batch.isfalsy() static_frame.core.batch.Batch[source]

Return a Batch with contained, same-indexed Frame indicating True which values are Falsy.

Batch.isin(other: Any) static_frame.core.batch.Batch[source]

Return a new Batch with contained Frame as a same-sized Boolean Frame that shows if the same-positioned element is in the passed iterable.

Batch.isna() static_frame.core.batch.Batch[source]

Return a Batch with contained, same-indexed Frame indicating True which values are NaN or None.

Batch.loc_max(*, skipna: bool = True, axis: int = 0) static_frame.core.batch.Batch[source]

Return the labels corresponding to the maximum values found.

Parameters
  • skipna – if True, NaN or None values will be ignored; if False, a found NaN will propagate.

  • axis – Axis upon which to evaluate contiguous missing values, where 0 is vertically (between row values) and 1 is horizontally (between column values).

Batch.loc_min(*, skipna: bool = True, axis: int = 0) static_frame.core.batch.Batch[source]

Return the labels corresponding to the minimum value found.

Parameters
  • skipna – if True, NaN or None values will be ignored; if False, a found NaN will propagate.

  • axis – Axis upon which to evaluate contiguous missing values, where 0 is vertically (between row values) and 1 is horizontally (between column values).

Batch.max(axis: int = 0, skipna: bool = True) Any

Return the maximum along the specified axis.

Parameters
  • axis – Axis, defaulting to axis 0.

  • skipna – Skip missing (NaN) values, defaulting to True.

Batch.mean(axis: int = 0, skipna: bool = True, out: Optional[numpy.ndarray] = None) Any

Return the mean along the specified axis.

Parameters
  • axis – Axis, defaulting to axis 0.

  • skipna – Skip missing (NaN) values, defaulting to True.

Batch.median(axis: int = 0, skipna: bool = True, out: Optional[numpy.ndarray] = None) Any

Return the median along the specified axis.

Parameters
  • axis – Axis, defaulting to axis 0.

  • skipna – Skip missing (NaN) values, defaulting to True.

Batch.min(axis: int = 0, skipna: bool = True, out: Optional[numpy.ndarray] = None) Any

Return the minimum along the specified axis.

Parameters
  • axis – Axis, defaulting to axis 0.

  • skipna – Skip missing (NaN) values, defaulting to True.

Batch.notfalsy() static_frame.core.batch.Batch[source]

Return a Batch with contained, same-indexed Frame indicating True which values are not Falsy.

Batch.notna() static_frame.core.batch.Batch[source]

Return a Batch with contained, same-indexed Frame indicating True which values are not NaN or None.

Batch.prod(axis: int = 0, skipna: bool = True, out: Optional[numpy.ndarray] = None) Any

Return the product along the specified axis.

Parameters
  • axis – Axis, defaulting to axis 0.

  • skipna – Skip missing (NaN) values, defaulting to True.

Batch.rank_dense(*, axis: int = 0, skipna: bool = True, ascending: Union[bool, Iterable[bool]] = True, start: int = 0, fill_value: Any = nan) static_frame.core.batch.Batch[source]
Batch.rank_max(*, axis: int = 0, skipna: bool = True, ascending: Union[bool, Iterable[bool]] = True, start: int = 0, fill_value: Any = nan) static_frame.core.batch.Batch[source]
Batch.rank_mean(*, axis: int = 0, skipna: bool = True, ascending: Union[bool, Iterable[bool]] = True, start: int = 0, fill_value: Any = nan) static_frame.core.batch.Batch[source]
Batch.rank_min(*, axis: int = 0, skipna: bool = True, ascending: Union[bool, Iterable[bool]] = True, start: int = 0, fill_value: Any = nan) static_frame.core.batch.Batch[source]
Batch.rank_ordinal(*, axis: int = 0, skipna: bool = True, ascending: Union[bool, Iterable[bool]] = True, start: int = 0, fill_value: Any = nan) static_frame.core.batch.Batch[source]
Batch.reindex(index: Optional[Union[static_frame.core.index_base.IndexBase, Iterable[Hashable], Iterable[Sequence[Hashable]]]] = None, columns: Optional[Union[static_frame.core.index_base.IndexBase, Iterable[Hashable], Iterable[Sequence[Hashable]]]] = None, *, fill_value: object = nan, own_index: bool = False, own_columns: bool = False, check_equals: bool = True) static_frame.core.batch.Batch[source]
Batch.relabel(index: Optional[Union[Callable[[...], Any], Mapping[Hashable, Any], static_frame.core.series.Series, Type[static_frame.core.index_auto.IndexAutoFactory], static_frame.core.index_base.IndexBase, Iterable[Hashable], Iterable[Sequence[Hashable]]]] = None, columns: Optional[Union[Callable[[...], Any], Mapping[Hashable, Any], static_frame.core.series.Series, Type[static_frame.core.index_auto.IndexAutoFactory], static_frame.core.index_base.IndexBase, Iterable[Hashable], Iterable[Sequence[Hashable]]]] = None, *, index_constructor: Optional[Callable[[...], static_frame.core.index_base.IndexBase]] = None, columns_constructor: Optional[Callable[[...], static_frame.core.index_base.IndexBase]] = None) static_frame.core.batch.Batch[source]
Batch.relabel_flat(index: bool = False, columns: bool = False) static_frame.core.batch.Batch[source]
Batch.relabel_level_add(index: Optional[Hashable] = None, columns: Optional[Hashable] = None, *, index_constructor: Optional[Callable[[...], static_frame.core.index_base.IndexBase]] = None, columns_constructor: Optional[Callable[[...], static_frame.core.index_base.IndexBase]] = None) static_frame.core.batch.Batch[source]
Batch.relabel_level_drop(index: int = 0, columns: int = 0) static_frame.core.batch.Batch[source]
Batch.relabel_shift_in(key: Union[int, numpy.integer, slice, List[Any], None, Index, Series, numpy.ndarray], *, axis: int = 0) Batch[source]
Batch.rename(name: Optional[Hashable]) static_frame.core.batch.Batch[source]

Return a new Batch with an updated name attribute.

Batch.roll(index: int = 0, columns: int = 0, include_index: bool = False, include_columns: bool = False) static_frame.core.batch.Batch[source]

Roll columns and/or rows by positive or negative integer counts, where columns and/or rows roll around the axis.

Parameters
  • include_index – Determine if index is included in index-wise rotation.

  • include_columns – Determine if column index is included in index-wise rotation.

Batch.sample(index: Optional[int] = None, columns: Optional[int] = None, *, seed: Optional[int] = None) static_frame.core.batch.Batch[source]

Apply sample on contained Frames.

Parameters
  • index. (Number of labels to select from the) –

  • columns. (Number of labels to select from the) –

  • selection. (Initial state of random) –

Batch.shift(index: int = 0, columns: int = 0, fill_value: Any = nan) static_frame.core.batch.Batch[source]

Shift columns and/or rows by positive or negative integer counts, where columns and/or rows fall of the axis and introduce missing values, filled by fill_value.

Batch.sort_columns(*, ascending: bool = True, kind: str = 'mergesort') static_frame.core.batch.Batch[source]

Return a new Batch with contained Frame ordered by the sorted columns.

Batch.sort_index(*, ascending: bool = True, kind: str = 'mergesort') static_frame.core.batch.Batch[source]

Return a new Batch with contained :obj;`Frame` ordered by the sorted index.

Batch.sort_values(label: Union[Hashable, Iterable[Hashable]], *, ascending: bool = True, axis: int = 1, kind: str = 'mergesort') static_frame.core.batch.Batch[source]

Return a new Batch with contained Frame ordered by the sorted values, where values are given by single column or iterable of columns.

Parameters

label – a label or iterable of keys.

Batch.std(axis: int = 0, skipna: bool = True, ddof: int = 0, out: Optional[numpy.ndarray] = None) Any

Return the standard deviaton along the specified axis.

Parameters
  • axis – Axis, defaulting to axis 0.

  • skipna – Skip missing (NaN) values, defaulting to True.

Batch.sum(axis: int = 0, skipna: bool = True, out: Optional[numpy.ndarray] = None) Any

Sum values along the specified axis.

Parameters
  • axis – Axis, defaulting to axis 0.

  • skipna – Skip missing (NaN) values, defaulting to True.

Batch.tail(count: int = 5) static_frame.core.batch.Batch[source]

Return a Batch consisting only of the bottom elements as specified by count.

Parameters

count – Number of elements to be returned from the bottom of the Batch

Batch.transpose() static_frame.core.batch.Batch[source]

Transpose. Return a Frame with index as columns and vice versa.

Batch.unique(*, axis: Optional[int] = None) static_frame.core.batch.Batch[source]

Return a NumPy array of unqiue values. If the axis argument is provied, uniqueness is determined by columns or row.

Batch.unset_index(*, names: Iterable[Hashable] = (), consolidate_blocks: bool = False, columns_constructors: Union[Callable[[...], static_frame.core.index_base.IndexBase], None, Sequence[Optional[Callable[[...], static_frame.core.index_base.IndexBase]]]] = None) static_frame.core.batch.Batch[source]
Batch.var(axis: int = 0, skipna: bool = True, ddof: int = 0, out: Optional[numpy.ndarray] = None) Any

Return the variance along the specified axis.

Parameters
  • axis – Axis, defaulting to axis 0.

  • skipna – Skip missing (NaN) values, defaulting to True.

Batch: Constructor | Exporter | Attribute | Method | Dictionary-Like | Display | Selector | Operator Binary | Operator Unary | Accessor Datetime | Accessor String | Accessor Transpose | Accessor Fill Value | Accessor Regular Expression

Batch: Dictionary-Like

Overview: Batch: Dictionary-Like

Batch.__iter__() Iterator[Hashable][source]

Iterator of Frame labels, same as Batch.keys.

Batch.items() Iterator[Tuple[Hashable, Union[static_frame.core.frame.Frame, static_frame.core.series.Series]]][source]

Iterator of labels, Frame.

Batch.keys() Iterator[Hashable][source]

Iterator of Frame labels.

Batch: Constructor | Exporter | Attribute | Method | Dictionary-Like | Display | Selector | Operator Binary | Operator Unary | Accessor Datetime | Accessor String | Accessor Transpose | Accessor Fill Value | Accessor Regular Expression

Batch: Display

Overview: Batch: Display

Batch.interface

A Frame documenting the interface of this class.

Batch.__repr__() str[source]

Provide a display of the Batch that does not exhaust the generator.

Batch.__str__()

Return str(self).

Batch.display(config: Optional[static_frame.core.display_config.DisplayConfig] = None, *, style_config: Optional[static_frame.core.style_config.StyleConfig] = None) static_frame.core.display.Display[source]

Provide a Series-style display of the Batch. Note that if the held iterator is a generator, this display will exhaust the generator.

Batch.display_tall(config: Optional[static_frame.core.display_config.DisplayConfig] = None) static_frame.core.display.Display

Maximize vertical presentation. Return a static_frame.Display, capable of providing a string representation.

Parameters

config – A static_frame.DisplayConfig instance. If not provided, the static_frame.DisplayActive will be used.

Batch.display_wide(config: Optional[static_frame.core.display_config.DisplayConfig] = None) static_frame.core.display.Display

Maximize horizontal presentation. Return a static_frame.Display, capable of providing a string representation.

Parameters

config – A static_frame.DisplayConfig instance. If not provided, the static_frame.DisplayActive will be used.

Batch: Constructor | Exporter | Attribute | Method | Dictionary-Like | Display | Selector | Operator Binary | Operator Unary | Accessor Datetime | Accessor String | Accessor Transpose | Accessor Fill Value | Accessor Regular Expression

Batch: Selector

Overview: Batch: Selector

Batch.bloc[key]
Batch.bloc
Batch.drop[key]
Batch.drop
InterfaceSelectTrio.__getitem__(key: Union[int, numpy.integer, slice, List[Any], None, Index, Series, numpy.ndarray]) Any[source]

Label-based selection.

Batch.drop.iloc[key]
Batch.drop
InterfaceSelectTrio.iloc

Integer-position based selection.

Batch.drop.loc[key]
Batch.drop
InterfaceSelectTrio.loc

Label-based selection.

Batch[key]
Batch.__getitem__ = <function Batch.__getitem__>[source]
Batch.iloc[key]
Batch.iloc
Batch.loc[key]
Batch.loc

Batch: Constructor | Exporter | Attribute | Method | Dictionary-Like | Display | Selector | Operator Binary | Operator Unary | Accessor Datetime | Accessor String | Accessor Transpose | Accessor Fill Value | Accessor Regular Expression

Batch: Operator Binary

Overview: Batch: Operator Binary

Batch.__add__(other: Any) Any
Batch.__and__(other: Any) Any
Batch.__eq__(other: Any) Any

Return self==value.

Batch.__floordiv__(other: Any) Any
Batch.__ge__(other: Any) Any

Return self>=value.

Batch.__gt__(other: Any) Any

Return self>value.

Batch.__le__(other: Any) Any

Return self<=value.

Batch.__lt__(other: Any) Any

Return self<value.

Batch.__matmul__(other: Any) Any
Batch.__mod__(other: Any) Any
Batch.__mul__(other: Any) Any
Batch.__ne__(other: Any) Any

Return self!=value.

Batch.__or__(other: Any) Any
Batch.__pow__(other: Any) Any
Batch.__radd__(other: Any) Any
Batch.__rfloordiv__(other: Any) Any
Batch.__rmatmul__(other: Any) Any
Batch.__rmul__(other: Any) Any
Batch.__rshift__(other: Any) Any
Batch.__rsub__(other: Any) Any
Batch.__rtruediv__(other: Any) Any
Batch.__sub__(other: Any) Any
Batch.__truediv__(other: Any) Any
Batch.__xor__(other: Any) Any

Batch: Constructor | Exporter | Attribute | Method | Dictionary-Like | Display | Selector | Operator Binary | Operator Unary | Accessor Datetime | Accessor String | Accessor Transpose | Accessor Fill Value | Accessor Regular Expression

Batch: Operator Unary

Overview: Batch: Operator Unary

Batch.__abs__() static_frame.core.container.ContainerOperand
Batch.__invert__() static_frame.core.container.ContainerOperand
Batch.__neg__() static_frame.core.container.ContainerOperand
Batch.__pos__() static_frame.core.container.ContainerOperand

Batch: Constructor | Exporter | Attribute | Method | Dictionary-Like | Display | Selector | Operator Binary | Operator Unary | Accessor Datetime | Accessor String | Accessor Transpose | Accessor Fill Value | Accessor Regular Expression

Batch: Accessor Datetime

Overview: Batch: Accessor Datetime

Batch.via_dt.year
Batch.via_dt

Interface for applying datetime properties and methods to elements in this container.

InterfaceBatchDatetime.year

Return the year of each element.

Batch.via_dt.month
Batch.via_dt

Interface for applying datetime properties and methods to elements in this container.

InterfaceBatchDatetime.month

Return the month of each element, between 1 and 12 inclusive.

Batch.via_dt.day
Batch.via_dt

Interface for applying datetime properties and methods to elements in this container.

InterfaceBatchDatetime.day

Return the day of each element, between 1 and the number of days in the given month of the given year.

Batch.via_dt.hour
Batch.via_dt

Interface for applying datetime properties and methods to elements in this container.

InterfaceBatchDatetime.hour

Return the hour of each element, between 0 and 24.

Batch.via_dt.minute
Batch.via_dt

Interface for applying datetime properties and methods to elements in this container.

InterfaceBatchDatetime.minute

Return the minute of each element, between 0 and 60.

Batch.via_dt.second
Batch.via_dt

Interface for applying datetime properties and methods to elements in this container.

InterfaceBatchDatetime.second

Return the second of each element, between 0 and 60.

Batch.via_dt.weekday
Batch.via_dt

Interface for applying datetime properties and methods to elements in this container.

InterfaceBatchDatetime.weekday() Batch[source]

Return the day of the week as an integer, where Monday is 0 and Sunday is 6.

Batch.via_dt.quarter
Batch.via_dt

Interface for applying datetime properties and methods to elements in this container.

InterfaceBatchDatetime.quarter() Batch[source]

Return the quarter of the year as an integer, where January through March is quarter 1.

Batch.via_dt.is_month_end
Batch.via_dt

Interface for applying datetime properties and methods to elements in this container.

InterfaceBatchDatetime.is_month_end() Batch[source]

Return Boolean indicators if the day is the month end.

Batch.via_dt.is_month_start
Batch.via_dt

Interface for applying datetime properties and methods to elements in this container.

InterfaceBatchDatetime.is_month_start() Batch[source]

Return Boolean indicators if the day is the month start.

Batch.via_dt.is_year_end
Batch.via_dt

Interface for applying datetime properties and methods to elements in this container.

InterfaceBatchDatetime.is_year_end() Batch[source]

Return Boolean indicators if the day is the year end.

Batch.via_dt.is_year_start
Batch.via_dt

Interface for applying datetime properties and methods to elements in this container.

InterfaceBatchDatetime.is_year_start() Batch[source]

Return Boolean indicators if the day is the year start.

Batch.via_dt.is_quarter_end
Batch.via_dt

Interface for applying datetime properties and methods to elements in this container.

InterfaceBatchDatetime.is_quarter_end() Batch[source]

Return Boolean indicators if the day is the quarter end.

Batch.via_dt.is_quarter_start
Batch.via_dt

Interface for applying datetime properties and methods to elements in this container.

InterfaceBatchDatetime.is_quarter_start() Batch[source]

Return Boolean indicators if the day is the quarter start.

Batch.via_dt.timetuple
Batch.via_dt

Interface for applying datetime properties and methods to elements in this container.

InterfaceBatchDatetime.timetuple() Batch[source]

Return a time.struct_time such as returned by time.localtime().

Batch.via_dt.isoformat(sep, timespec)
Batch.via_dt

Interface for applying datetime properties and methods to elements in this container.

InterfaceBatchDatetime.isoformat(sep: str = 'T', timespec: str = 'auto') Batch[source]

Return a string representing the date in ISO 8601 format, YYYY-MM-DD.

Batch.via_dt.fromisoformat
Batch.via_dt

Interface for applying datetime properties and methods to elements in this container.

InterfaceBatchDatetime.fromisoformat() Batch[source]

Return a datetime.date object from an ISO 8601 format.

Batch.via_dt.strftime(format)
Batch.via_dt

Interface for applying datetime properties and methods to elements in this container.

InterfaceBatchDatetime.strftime(format: str) Batch[source]

Return a string representing the date, controlled by an explicit format string.

Batch.via_dt.strptime(format)
Batch.via_dt

Interface for applying datetime properties and methods to elements in this container.

InterfaceBatchDatetime.strptime(format: str) Batch[source]

Return a Python datetime object from parsing a string defined with format.

Batch.via_dt.strpdate(format)
Batch.via_dt

Interface for applying datetime properties and methods to elements in this container.

InterfaceBatchDatetime.strpdate(format: str) Batch[source]

Return a Python date object from parsing a string defined with format.

Batch: Constructor | Exporter | Attribute | Method | Dictionary-Like | Display | Selector | Operator Binary | Operator Unary | Accessor Datetime | Accessor String | Accessor Transpose | Accessor Fill Value | Accessor Regular Expression

Batch: Accessor String

Overview: Batch: Accessor String

Batch.via_str.__getitem__(key)
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.__getitem__(key: Union[int, numpy.integer, slice, List[Any], None, Index, Series, numpy.ndarray]) Batch[source]

Return a container with the provided selection or slice of each element.

Batch.via_str.capitalize
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.capitalize() Batch[source]

Return a container with only the first character of each element capitalized.

Batch.via_str.center(width, fillchar)
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.center(width: int, fillchar: str = ' ') Batch[source]

Return a container with its elements centered in a string of length width.

Batch.via_str.count(sub, start, end)
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.count(sub: str, start: Optional[int] = None, end: Optional[int] = None) Batch[source]

Returns a container with the number of non-overlapping occurrences of substring sub in the optional range start, end.

Batch.via_str.decode(encoding, errors)
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.decode(encoding: Optional[str] = None, errors: Optional[str] = None) Batch[source]

Apply str.decode() to each element. Elements must be bytes.

Batch.via_str.encode(encoding, errors)
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.encode(encoding: Optional[str] = None, errors: Optional[str] = None) Batch[source]

Apply str.encode() to each element. Elements must be strings.

Batch.via_str.endswith(suffix, start, end)
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.endswith(suffix: Union[str, Iterable[str]], start: Optional[int] = None, end: Optional[int] = None) Batch[source]

Returns a container with the number of non-overlapping occurrences of substring suffix (or an interable of suffixes) in the optional range start, end.

Batch.via_str.find(sub, start, end)
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.find(sub: str, start: Optional[int] = None, end: Optional[int] = None) Batch[source]

For each element, return the lowest index in the string where substring sub is found.

Batch.via_str.index(sub, start, end)
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.index(sub: str, start: Optional[int] = None, end: Optional[int] = None) Batch[source]

Like find, but raises ValueError when the substring is not found.

Batch.via_str.isalnum
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.isalnum() Batch[source]

Returns true for each element if all characters in the string are alphanumeric and there is at least one character, false otherwise.

Batch.via_str.isalpha
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.isalpha() Batch[source]

Returns true for each element if all characters in the string are alphabetic and there is at least one character, false otherwise.

Batch.via_str.isdecimal
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.isdecimal() Batch[source]

For each element, return True if there are only decimal characters in the element.

Batch.via_str.isdigit
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.isdigit() Batch[source]

Returns true for each element if all characters in the string are digits and there is at least one character, false otherwise.

Batch.via_str.islower
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.islower() Batch[source]

Returns true for each element if all cased characters in the string are lowercase and there is at least one cased character, false otherwise.

Batch.via_str.isnumeric
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.isnumeric() Batch[source]

For each element in self, return True if there are only numeric characters in the element.

Batch.via_str.isspace
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.isspace() Batch[source]

Returns true for each element if there are only whitespace characters in the string and there is at least one character, false otherwise.

Batch.via_str.istitle
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.istitle() Batch[source]

Returns true for each element if the element is a titlecased string and there is at least one character, false otherwise.

Batch.via_str.isupper
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.isupper() Batch[source]

Returns true for each element if all cased characters in the string are uppercase and there is at least one character, false otherwise.

Batch.via_str.ljust(width, fillchar)
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.ljust(width: int, fillchar: str = ' ') Batch[source]

Return a container with its elements ljusted in a string of length width.

Batch.via_str.len
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.len() Batch[source]

Return the length of the string.

Batch.via_str.lower
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.lower() Batch[source]

Return an array with the elements of self converted to lowercase.

Batch.via_str.lstrip(chars)
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.lstrip(chars: Optional[str] = None) Batch[source]

For each element, return a copy with the leading characters removed.

Batch.via_str.partition(sep)
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.partition(sep: str) Batch[source]

Partition each element around sep.

Batch.via_str.replace(old, new, count)
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.replace(old: str, new: str, count: Optional[int] = None) Batch[source]

Return a container with its elements replaced in a string of length width.

Batch.via_str.rfind(sub, start, end)
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.rfind(sub: str, start: Optional[int] = None, end: Optional[int] = None) Batch[source]

For each element, return the highest index in the string where substring sub is found, such that sub is contained within start, end.

Batch.via_str.rindex(sub, start, end)
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.rindex(sub: str, start: Optional[int] = None, end: Optional[int] = None) Batch[source]

Like rfind, but raises ValueError when the substring sub is not found.

Batch.via_str.rjust(width, fillchar)
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.rjust(width: int, fillchar: str = ' ') Batch[source]

Return a container with its elements rjusted in a string of length width.

Batch.via_str.rpartition(sep)
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.rpartition(sep: str) Batch[source]

Partition (split) each element around the right-most separator.

Batch.via_str.rsplit(sep, maxsplit)
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.rsplit(sep: str, maxsplit: int = - 1) Batch[source]

For each element, return a tuple of the words in the string, using sep as the delimiter string.

Batch.via_str.rstrip(chars)
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.rstrip(chars: Optional[str] = None) Batch[source]

For each element, return a copy with the trailing characters removed.

Batch.via_str.split(sep, maxsplit)
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.split(sep: str, maxsplit: int = - 1) Batch[source]

For each element, return a tuple of the words in the string, using sep as the delimiter string.

Batch.via_str.startswith(prefix, start, end)
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.startswith(prefix: Union[str, Iterable[str]], start: Optional[int] = None, end: Optional[int] = None) Batch[source]

Returns a container with the number of non-overlapping occurrences of substring prefix (or an interable of prefixes) in the optional range start, end.

Batch.via_str.strip(chars)
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.strip(chars: Optional[str] = None) Batch[source]

For each element, return a copy with the leading and trailing characters removed.

Batch.via_str.swapcase
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.swapcase() Batch[source]

Return a container with uppercase characters converted to lowercase and vice versa.

Batch.via_str.title
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.title() Batch[source]

Return a container with uppercase characters converted to lowercase and vice versa.

Batch.via_str.upper
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.upper() Batch[source]

Return a container with uppercase characters converted to lowercase and vice versa.

Batch.via_str.zfill(width)
Batch.via_str

Interface for applying string methods to elements in this container.

InterfaceBatchString.zfill(width: int) Batch[source]

Return the string left-filled with zeros.

Batch: Constructor | Exporter | Attribute | Method | Dictionary-Like | Display | Selector | Operator Binary | Operator Unary | Accessor Datetime | Accessor String | Accessor Transpose | Accessor Fill Value | Accessor Regular Expression

Batch: Accessor Transpose

Overview: Batch: Accessor Transpose

Batch.via_T.via_fill_value(fill_value)
Batch.via_T

Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.

InterfaceBatchTranspose.via_fill_value(fill_value: object) InterfaceBatchFillValue[source]

Interface for using binary operators and methods with a pre-defined fill value.

Batch.via_T.__add__(other)
Batch.via_T

Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.

InterfaceBatchTranspose.__add__(other: Any) Batch[source]
Batch.via_T.__sub__(other)
Batch.via_T

Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.

InterfaceBatchTranspose.__sub__(other: Any) Batch[source]
Batch.via_T.__mul__(other)
Batch.via_T

Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.

InterfaceBatchTranspose.__mul__(other: Any) Batch[source]
Batch.via_T.__truediv__(other)
Batch.via_T

Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.

InterfaceBatchTranspose.__truediv__(other: Any) Batch[source]
Batch.via_T.__floordiv__(other)
Batch.via_T

Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.

InterfaceBatchTranspose.__floordiv__(other: Any) Batch[source]
Batch.via_T.__mod__(other)
Batch.via_T

Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.

InterfaceBatchTranspose.__mod__(other: Any) Batch[source]
Batch.via_T.__pow__(other)
Batch.via_T

Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.

InterfaceBatchTranspose.__pow__(other: Any) Batch[source]
Batch.via_T.__lshift__(other)
Batch.via_T

Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.

InterfaceBatchTranspose.__lshift__(other: Any) Batch[source]
Batch.via_T.__rshift__(other)
Batch.via_T

Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.

InterfaceBatchTranspose.__rshift__(other: Any) Batch[source]
Batch.via_T.__and__(other)
Batch.via_T

Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.

InterfaceBatchTranspose.__and__(other: Any) Batch[source]
Batch.via_T.__xor__(other)
Batch.via_T

Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.

InterfaceBatchTranspose.__xor__(other: Any) Batch[source]
Batch.via_T.__or__(other)
Batch.via_T

Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.

InterfaceBatchTranspose.__or__(other: Any) Batch[source]
Batch.via_T.__lt__(other)
Batch.via_T

Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.

InterfaceBatchTranspose.__lt__(other: Any) Batch[source]

Return self<value.

Batch.via_T.__le__(other)
Batch.via_T

Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.

InterfaceBatchTranspose.__le__(other: Any) Batch[source]

Return self<=value.

Batch.via_T.__eq__(other)
Batch.via_T

Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.

InterfaceBatchTranspose.__eq__(other: Any) Batch[source]

Return self==value.

Batch.via_T.__ne__(other)
Batch.via_T

Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.

InterfaceBatchTranspose.__ne__(other: Any) Batch[source]

Return self!=value.

Batch.via_T.__gt__(other)
Batch.via_T

Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.

InterfaceBatchTranspose.__gt__(other: Any) Batch[source]

Return self>value.

Batch.via_T.__ge__(other)
Batch.via_T

Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.

InterfaceBatchTranspose.__ge__(other: Any) Batch[source]

Return self>=value.

Batch.via_T.__radd__(other)
Batch.via_T

Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.

InterfaceBatchTranspose.__radd__(other: Any) Batch[source]
Batch.via_T.__rsub__(other)
Batch.via_T

Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.

InterfaceBatchTranspose.__rsub__(other: Any) Batch[source]
Batch.via_T.__rmul__(other)
Batch.via_T

Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.

InterfaceBatchTranspose.__rmul__(other: Any) Batch[source]
Batch.via_T.__rtruediv__(other)
Batch.via_T

Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.

InterfaceBatchTranspose.__rtruediv__(other: Any) Batch[source]
Batch.via_T.__rfloordiv__(other)
Batch.via_T

Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.

InterfaceBatchTranspose.__rfloordiv__(other: Any) Batch[source]

Batch: Constructor | Exporter | Attribute | Method | Dictionary-Like | Display | Selector | Operator Binary | Operator Unary | Accessor Datetime | Accessor String | Accessor Transpose | Accessor Fill Value | Accessor Regular Expression

Batch: Accessor Fill Value

Overview: Batch: Accessor Fill Value

Batch.via_fill_value(fill_value).loc
Batch.via_fill_value = <function Batch.via_fill_value>[source]
InterfaceFillValue.loc

Label-based selection where labels not specified will define a new container containing those labels filled with the fill value.

Batch.via_fill_value(fill_value).__getitem__(key)
via_fill_value = <function Batch.via_fill_value>[source]
InterfaceFillValue.__getitem__(key: Union[int, numpy.integer, slice, List[Any], None, Index, Series, numpy.ndarray]) Union[Frame, Series][source]

Label-based selection where labels not specified will define a new container containing those labels filled with the fill value.

Batch.via_fill_value(fill_value).via_T
Batch.via_fill_value = <function Batch.via_fill_value>[source]
InterfaceFillValue.via_T

Interface for using binary operators with one-dimensional sequences, where the opperand is applied column-wise.

Batch.via_fill_value(fill_value).__add__(other)
via_fill_value = <function Batch.via_fill_value>[source]
InterfaceFillValue.__add__(other: Any) Any[source]
Batch.via_fill_value(fill_value).__sub__(other)
via_fill_value = <function Batch.via_fill_value>[source]
InterfaceFillValue.__sub__(other: Any) Any[source]
Batch.via_fill_value(fill_value).__mul__(other)
via_fill_value = <function Batch.via_fill_value>[source]
InterfaceFillValue.__mul__(other: Any) Any[source]
Batch.via_fill_value(fill_value).__truediv__(other)
via_fill_value = <function Batch.via_fill_value>[source]
InterfaceFillValue.__truediv__(other: Any) Any[source]
Batch.via_fill_value(fill_value).__floordiv__(other)
via_fill_value = <function Batch.via_fill_value>[source]
InterfaceFillValue.__floordiv__(other: Any) Any[source]
Batch.via_fill_value(fill_value).__mod__(other)
via_fill_value = <function Batch.via_fill_value>[source]
InterfaceFillValue.__mod__(other: Any) Any[source]
Batch.via_fill_value(fill_value).__pow__(other)
via_fill_value = <function Batch.via_fill_value>[source]
InterfaceFillValue.__pow__(other: Any) Any[source]
Batch.via_fill_value(fill_value).__lshift__(other)
via_fill_value = <function Batch.via_fill_value>[source]
InterfaceFillValue.__lshift__(other: Any) Any[source]
Batch.via_fill_value(fill_value).__rshift__(other)
via_fill_value = <function Batch.via_fill_value>[source]
InterfaceFillValue.__rshift__(other: Any) Any[source]
Batch.via_fill_value(fill_value).__and__(other)
via_fill_value = <function Batch.via_fill_value>[source]
InterfaceFillValue.__and__(other: Any) Any[source]
Batch.via_fill_value(fill_value).__xor__(other)
via_fill_value = <function Batch.via_fill_value>[source]
InterfaceFillValue.__xor__(other: Any) Any[source]
Batch.via_fill_value(fill_value).__or__(other)
via_fill_value = <function Batch.via_fill_value>[source]
InterfaceFillValue.__or__(other: Any) Any[source]
Batch.via_fill_value(fill_value).__lt__(other)
via_fill_value = <function Batch.via_fill_value>[source]
InterfaceFillValue.__lt__(other: Any) Any[source]

Return self<value.

Batch.via_fill_value(fill_value).__le__(other)
via_fill_value = <function Batch.via_fill_value>[source]
InterfaceFillValue.__le__(other: Any) Any[source]

Return self<=value.

Batch.via_fill_value(fill_value).__eq__(other)
via_fill_value = <function Batch.via_fill_value>[source]
InterfaceFillValue.__eq__(other: Any) Any[source]

Return self==value.

Batch.via_fill_value(fill_value).__ne__(other)
via_fill_value = <function Batch.via_fill_value>[source]
InterfaceFillValue.__ne__(other: Any) Any[source]

Return self!=value.

Batch.via_fill_value(fill_value).__gt__(other)
via_fill_value = <function Batch.via_fill_value>[source]
InterfaceFillValue.__gt__(other: Any) Any[source]

Return self>value.

Batch.via_fill_value(fill_value).__ge__(other)
via_fill_value = <function Batch.via_fill_value>[source]
InterfaceFillValue.__ge__(other: Any) Any[source]

Return self>=value.

Batch.via_fill_value(fill_value).__radd__(other)
via_fill_value = <function Batch.via_fill_value>[source]
InterfaceFillValue.__radd__(other: Any) Any[source]
Batch.via_fill_value(fill_value).__rsub__(other)
via_fill_value = <function Batch.via_fill_value>[source]
InterfaceFillValue.__rsub__(other: Any) Any[source]
Batch.via_fill_value(fill_value).__rmul__(other)
via_fill_value = <function Batch.via_fill_value>[source]
InterfaceFillValue.__rmul__(other: Any) Any[source]
Batch.via_fill_value(fill_value).__rtruediv__(other)
via_fill_value = <function Batch.via_fill_value>[source]
InterfaceFillValue.__rtruediv__(other: Any) Any[source]
Batch.via_fill_value(fill_value).__rfloordiv__(other)
via_fill_value = <function Batch.via_fill_value>[source]
InterfaceFillValue.__rfloordiv__(other: Any) Any[source]

Batch: Constructor | Exporter | Attribute | Method | Dictionary-Like | Display | Selector | Operator Binary | Operator Unary | Accessor Datetime | Accessor String | Accessor Transpose | Accessor Fill Value | Accessor Regular Expression

Batch: Accessor Regular Expression

Overview: Batch: Accessor Regular Expression

Batch.via_re(pattern, flags).search(pos, endpos)
via_re = <function Batch.via_re>[source]
InterfaceRe.search(pos: int = 0, endpos: Optional[int] = None) static_frame.core.node_selector.TContainer[source]

Scan through string looking for the first location where this regular expression produces a match and return True, else False. Note that this is different from finding a zero-length match at some point in the string.

Parameters
  • pos – Gives an index in the string where the search is to start; it defaults to 0.

  • endpos – Limits how far the string will be searched; it will be as if the string is endpos characters long.

Batch.via_re(pattern, flags).match(pos, endpos)
via_re = <function Batch.via_re>[source]
InterfaceRe.match(pos: int = 0, endpos: Optional[int] = None) static_frame.core.node_selector.TContainer[source]

If zero or more characters at the beginning of string match this regular expression return True, else False. Note that this is different from a zero-length match.

Parameters
  • pos – Gives an index in the string where the search is to start; it defaults to 0.

  • endpos – Limits how far the string will be searched; it will be as if the string is endpos characters long.

Batch.via_re(pattern, flags).fullmatch(pos, endpos)
via_re = <function Batch.via_re>[source]
InterfaceRe.fullmatch(pos: int = 0, endpos: Optional[int] = None) static_frame.core.node_selector.TContainer[source]

If the whole string matches this regular expression, return True, else False. Note that this is different from a zero-length match.

Parameters
  • pos – Gives an index in the string where the search is to start; it defaults to 0.

  • endpos – Limits how far the string will be searched; it will be as if the string is endpos characters long.

Batch.via_re(pattern, flags).split(maxsplit)
via_re = <function Batch.via_re>[source]
InterfaceRe.split(maxsplit: int = 0) static_frame.core.node_selector.TContainer[source]

Split string by the occurrences of pattern. If capturing parentheses are used in pattern, then the text of all groups in the pattern are also returned as part of the resulting tuple.

Parameters

maxsplit – If nonzero, at most maxsplit splits occur, and the remainder of the string is returned as the final element of the tuple.

Batch.via_re(pattern, flags).findall(pos, endpos)
via_re = <function Batch.via_re>[source]
InterfaceRe.findall(pos: int = 0, endpos: Optional[int] = None) static_frame.core.node_selector.TContainer[source]

Return all non-overlapping matches of pattern in string, as a tuple of strings. The string is scanned left-to-right, and matches are returned in the order found. If one or more groups are present in the pattern, return a tuple of groups; this will be a tuple of tuples if the pattern has more than one group. Empty matches are included in the result.

Parameters
  • pos – Gives an index in the string where the search is to start; it defaults to 0.

  • endpos – Limits how far the string will be searched; it will be as if the string is endpos characters long.

Batch.via_re(pattern, flags).sub(repl, count)
via_re = <function Batch.via_re>[source]
InterfaceRe.sub(repl: str, count: int = 0) static_frame.core.node_selector.TContainer[source]

Return the string obtained by replacing the leftmost non-overlapping occurrences of pattern in string by the replacement repl. If the pattern is not found, the string is returned unchanged.

Parameters
  • repl – A string or a function; if it is a string, any backslash escapes in it are processed.

  • count – The optional argument count is the maximum number of pattern occurrences to be replaced; count must be a non-negative integer. If omitted or zero, all occurrences will be replaced.

Batch.via_re(pattern, flags).subn(repl, count)
via_re = <function Batch.via_re>[source]
InterfaceRe.subn(repl: str, count: int = 0) static_frame.core.node_selector.TContainer[source]

Perform the same operation as sub(), but return a tuple (new_string, number_of_subs_made).

Parameters
  • repl – A string or a function; if it is a string, any backslash escapes in it are processed.

  • count – The optional argument count is the maximum number of pattern occurrences to be replaced; count must be a non-negative integer. If omitted or zero, all occurrences will be replaced.

Batch: Constructor | Exporter | Attribute | Method | Dictionary-Like | Display | Selector | Operator Binary | Operator Unary | Accessor Datetime | Accessor String | Accessor Transpose | Accessor Fill Value | Accessor Regular Expression