Overview: Batch: Method

Detail: Batch: Method

Detail	`Batch.__array__(dtype)`	Support the __array__ interface, returning an array of values.
Detail	`Batch.__array_ufunc__(ufunc, method, args, *kwargs)`	Support for NumPy elements or arrays on the left hand of binary operators.
Detail	`Batch.__bool__()`	Raises ValueError to prohibit ambiguous use of truthy evaluation.
Detail	`Batch.__round__(decimals)`	Return a Batch with contained Frame rounded to the given decimals. Negative deci…
Detail	`Batch.all(axis, skipna, out)`	Logical and over values along the specified axis. Args: axis: Axis, defaulting t…
Detail	`Batch.any(axis, skipna, out)`	Logical or over values along the specified axis. Args: axis: Axis, defaulting to…
Detail	`Batch.apply(func)`	Apply a function to each Frame contained in this Frame, where a function is give…
Detail	`Batch.apply_except(func, exception)`	Apply a function to each Frame contained in this Frame, where a function is give…
Detail	`Batch.apply_items(func)`	Apply a function to each Frame contained in this Frame, where a function is give…
Detail	`Batch.apply_items_except(func, exception)`	Apply a function to each Frame contained in this Frame, where a function is give…
Detail	`Batch.astype[key](dtypes, *, consolidate_blocks)`	Selector of columns by label. Args: key: A loc selector, either a label, a list…
Detail	`Batch.astype(dtype)`	Apply a single dtype to all columns.
Detail	`Batch.clip(*, lower, upper, axis)`	Apply a clip operation to this Batch. Note that clip operations can be applied t…
Detail	`Batch.corr(*, axis)`	Compute a correlation matrix. Args: axis: if 0, each row represents a variable,…
Detail	`Batch.count(*, skipna, skipfalsy, unique, axis)`	Apply count on contained Frames.
Detail	`Batch.cov(*, axis, ddof)`	Compute a covariance matrix. Args: axis: if 0, each row represents a variable, w…
Detail	`Batch.cumprod(axis, skipna)`	Return the cumulative product over the specified axis. Args: axis: Axis, default…
Detail	`Batch.cumsum(axis, skipna)`	Return the cumulative sum over the specified axis. Args: axis: Axis, defaulting…
Detail	`Batch.drop_duplicated(*, axis, exclude_first, exclude_last)`	Return a Batch with contained Frame with duplicated rows (axis 0) or columns (ax…
Detail	`Batch.dropfalsy(axis, condition)`	Return a Batch with contained Frame after removing rows (axis 0) or columns (axi…
Detail	`Batch.dropna(axis, condition)`	Return a Batch with contained Frame after removing rows (axis 0) or columns (axi…
Detail	`Batch.duplicated(*, axis, exclude_first, exclude_last)`	Return an axis-sized Boolean Series that shows True for all rows (axis 0) or col…
Detail	`Batch.equals(other, *, compare_name, compare_dtype, compare_class, skipna)`
Detail	`Batch.fillfalsy(value)`	Return a new Batch with contained Frame after filling falsy values with the prov…
Detail	`Batch.fillfalsy_backward(limit, *, axis)`	Return a new Batch with contained Frame after filling backward falsy values with…
Detail	`Batch.fillfalsy_forward(limit, axis)`	Return a new Batch with contained Frame after filling forward falsy values with…
Detail	`Batch.fillfalsy_leading(value, *, axis)`	Return a new Batch with contained Frame after filling leading (and only leading)…
Detail	`Batch.fillfalsy_trailing(value, *, axis)`	Return a new Batch with contained Frame after filling trailing (and only trailin…
Detail	`Batch.fillna(value)`	Return a new Batch with contained Frame after filling null (NaN or None) with th…
Detail	`Batch.fillna_backward(limit, *, axis)`	Return a new Batch with contained Frame after filling backward null (NaN or None…
Detail	`Batch.fillna_forward(limit, *, axis)`	Return a new Batch with contained Frame after filling forward null (NaN or None)…
Detail	`Batch.fillna_leading(value, *, axis)`	Return a new Batch with contained Frame after filling leading (and only leading)…
Detail	`Batch.fillna_trailing(value, *, axis)`	Return a new Batch with contained Frame after filling trailing (and only trailin…
Detail	`Batch.head(count)`	Return a Batch consisting only of the top elements as specified by count. Args:…
Detail	`Batch.iloc_max(*, skipna, axis)`	Return the integer indices corresponding to the maximum values found. Args: skip…
Detail	`Batch.iloc_min(*, skipna, axis)`	Return the integer indices corresponding to the minimum values found. Args: skip…
Detail	`Batch.isfalsy()`	Return a Batch with contained, same-indexed Frame indicating True which values a…
Detail	`Batch.isin(other)`	Return a new Batch with contained Frame as a same-sized Boolean Frame that shows…
Detail	`Batch.isna()`	Return a Batch with contained, same-indexed Frame indicating True which values a…
Detail	`Batch.loc_max(*, skipna, axis)`	Return the labels corresponding to the maximum values found. Args: skipna: if Tr…
Detail	`Batch.loc_min(*, skipna, axis)`	Return the labels corresponding to the minimum value found. Args: skipna: if Tru…
Detail	`Batch.max(axis, skipna)`	Return the maximum along the specified axis. Args: axis: Axis, defaulting to axi…
Detail	`Batch.mean(axis, skipna, out)`	Return the mean along the specified axis. Args: axis: Axis, defaulting to axis 0…
Detail	`Batch.median(axis, skipna, out)`	Return the median along the specified axis. Args: axis: Axis, defaulting to axis…
Detail	`Batch.min(axis, skipna, out)`	Return the minimum along the specified axis. Args: axis: Axis, defaulting to axi…
Detail	`Batch.notfalsy()`	Return a Batch with contained, same-indexed Frame indicating True which values a…
Detail	`Batch.notna()`	Return a Batch with contained, same-indexed Frame indicating True which values a…
Detail	`Batch.prod(axis, skipna, allna, out)`	Return the product along the specified axis. Args: axis: Axis, defaulting to axi…
Detail	`Batch.rank_dense(*, axis, skipna, ascending, start, fill_value)`
Detail	`Batch.rank_max(*, axis, skipna, ascending, start, fill_value)`
Detail	`Batch.rank_mean(*, axis, skipna, ascending, start, fill_value)`
Detail	`Batch.rank_min(*, axis, skipna, ascending, start, fill_value)`
Detail	`Batch.rank_ordinal(*, axis, skipna, ascending, start, fill_value)`
Detail	`Batch.reindex(index, columns, *, fill_value, own_index, own_columns, check_equals)`
Detail	`Batch.relabel(index, columns, *, index_constructor, columns_constructor)`
Detail	`Batch.relabel_flat(index, columns)`
Detail	`Batch.relabel_level_add(index, columns, *, index_constructor, columns_constructor)`
Detail	`Batch.relabel_level_drop(index, columns)`
Detail	`Batch.relabel_shift_in(key, *, axis)`
Detail	`Batch.rename(name, *, index, columns)`	Return a new Batch with an updated name attribute.
Detail	`Batch.roll(index, columns, *, include_index, include_columns)`	Roll columns and/or rows by positive or negative integer counts, where columns a…
Detail	`Batch.sample(index, columns, *, seed)`	Apply sample on contained Frames. Args: Number of labels to select from the inde…
Detail	`Batch.shift(index, columns, fill_value)`	Shift columns and/or rows by positive or negative integer counts, where columns…
Detail	`Batch.sort_columns(*, ascending, kind)`	Return a new Batch with contained Frame ordered by the sorted columns.
Detail	`Batch.sort_index(*, ascending, kind)`	Return a new Batch with contained :obj;Frame ordered by the sorted index.
Detail	`Batch.sort_values(label, *, ascending, axis, kind)`	Return a new Batch with contained Frame ordered by the sorted values, where valu…
Detail	`Batch.std(axis, skipna, ddof, out)`	Return the standard deviaton along the specified axis. Args: axis: Axis, default…
Detail	`Batch.sum(axis, skipna, allna, out)`	Sum values along the specified axis. Args: axis: Axis, defaulting to axis 0. ski…
Detail	`Batch.tail(count)`	Return a Batch consisting only of the bottom elements as specified by count. Arg…
Detail	`Batch.transpose()`	Transpose. Return a Frame with index as columns and vice versa.
Detail	`Batch.unique(*, axis)`	Return a NumPy array of unqiue values. If the axis argument is provied, uniquene…
Detail	`Batch.unset_index(*, names, consolidate_blocks, columns_constructors)`
Detail	`Batch.var(axis, skipna, ddof, out)`	Return the variance along the specified axis. Args: axis: Axis, defaulting to ax…