Overview: SeriesHE: Method

Detail: SeriesHE: Method

Detail	`SeriesHE.__array__(dtype)`	Support the __array__ interface, returning an array of values.
Detail	`SeriesHE.__array_ufunc__(ufunc, method, args, *kwargs)`	Support for NumPy elements or arrays on the left hand of binary operators.
Detail	`SeriesHE.__bool__()`	Raises ValueError to prohibit ambiguous use of truthy evaluation.
Detail	`SeriesHE.__deepcopy__(memo)`
Detail	`SeriesHE.__len__()`	Length of values.
Detail	`SeriesHE.__round__(decimals)`	Return a Series rounded to the given decimals. Negative decimals round to the le…
Detail	`SeriesHE.all(axis, skipna, out)`	Logical and over values along the specified axis. Args: axis: Axis, defaulting t…
Detail	`SeriesHE.any(axis, skipna, out)`	Logical or over values along the specified axis. Args: axis: Axis, defaulting to…
Detail	`SeriesHE.astype(dtype)`	Return a Series with type determined by dtype argument. Note that for Series, th…
Detail	`SeriesHE.clip(*, lower, upper)`	Apply a clip operation to this Series. Note that clip operations can be applied…
Detail	`SeriesHE.corr(other)`	Return the index-aligned correlation to the supplied Series. Args: other: Series…
Detail	`SeriesHE.count(*, skipna, skipfalsy, unique, axis)`	Return the count of non-NA, non-falsy, and/or unique elements. Args: skipna: ski…
Detail	`SeriesHE.cov(other, *, ddof)`	Return the index-aligned covariance to the supplied Series. Args: ddof: Delta de…
Detail	`SeriesHE.cumprod(axis, skipna)`	Return the cumulative product over the specified axis. Args: axis: Axis, default…
Detail	`SeriesHE.cumsum(axis, skipna)`	Return the cumulative sum over the specified axis. Args: axis: Axis, defaulting…
Detail	`SeriesHE.drop_duplicated(*, exclude_first, exclude_last)`	Return a Series with duplicated values removed. Args: exclude_first: Boolean to…
Detail	`SeriesHE.dropfalsy()`	Return a new Series after removing values of falsy.
Detail	`SeriesHE.dropna()`	Return a new Series after removing values of NaN or None.
Detail	`SeriesHE.duplicated(*, exclude_first, exclude_last)`	Return a same-sized Boolean Series that shows True for all values that are dupli…
Detail	`SeriesHE.equals(other, *, compare_name, compare_dtype, compare_class, skipna)`	Return a bool from comparison to any other object. Args: compare_name: Include e…
Detail	`SeriesHE.fillfalsy(value)`	Return a new Series after replacing falsy values with the supplied value. The va…
Detail	`SeriesHE.fillfalsy_backward(limit)`	Return a new Series after feeding backward the last non-falsy observation across…
Detail	`SeriesHE.fillfalsy_forward(limit)`	Return a new Series after feeding forward the last non-falsy observation across…
Detail	`SeriesHE.fillfalsy_leading(value)`	Return a new Series after filling leading (and only leading) falsy values with t…
Detail	`SeriesHE.fillfalsy_trailing(value)`	Return a new Series after filling trailing (and only trailing) falsy values with…
Detail	`SeriesHE.fillna(value)`	Return a new Series after replacing NA (NaN or None) with the supplied value. Th…
Detail	`SeriesHE.fillna_backward(limit)`	Return a new Series after feeding backward the last non-null (NaN or None) obser…
Detail	`SeriesHE.fillna_forward(limit)`	Return a new Series after feeding forward the last non-null (NaN or None) observ…
Detail	`SeriesHE.fillna_leading(value)`	Return a new Series after filling leading (and only leading) null (NaN or None)…
Detail	`SeriesHE.fillna_trailing(value)`	Return a new Series after filling trailing (and only trailing) null (NaN or None…
Detail	`SeriesHE.head(count)`	Return a Series consisting only of the top elements as specified by count. Args:…
Detail	`SeriesHE.iloc_max(*, skipna)`	Return the integer index corresponding to the maximum value. Args: skipna: if Tr…
Detail	`SeriesHE.iloc_min(*, skipna)`	Return the integer index corresponding to the minimum value found. Args: skipna:…
Detail	`SeriesHE.iloc_notfalsy_first(*, fill_value)`	Return the position corresponding to the first non-falsy (including nan) value f…
Detail	`SeriesHE.iloc_notfalsy_last(*, fill_value)`	Return the position corresponding to the last non-falsy (including nan) value fo…
Detail	`SeriesHE.iloc_notna_first(*, fill_value)`	Return the position corresponding to the first not NA (None or nan) value found….
Detail	`SeriesHE.iloc_notna_last(*, fill_value)`	Return the position corresponding to the last not NA (None or nan) value found….
Detail	`SeriesHE.iloc_searchsorted(values, *, side_left)`	Given a sorted Series, return the iloc (integer) position(s) at which insertion…
Detail	`SeriesHE.insert_after(key, container)`	Create a new Series by inserting a Series at the position after the label specif…
Detail	`SeriesHE.insert_before(key, container)`	Create a new Series by inserting a Series at the position before the label speci…
Detail	`SeriesHE.isfalsy()`	Return a same-indexed, Boolean Series indicating which values are falsy.
Detail	`SeriesHE.isin(other)`	Return a same-sized Boolean Series that shows if the same-positioned element is…
Detail	`SeriesHE.isna()`	Return a same-indexed, Boolean Series indicating which values are NaN or None.
Detail	`SeriesHE.loc_max(*, skipna)`	Return the label corresponding to the maximum value found. Args: skipna: if True…
Detail	`SeriesHE.loc_min(*, skipna)`	Return the label corresponding to the minimum value found. Args: skipna: if True…
Detail	`SeriesHE.loc_notfalsy_first(*, fill_value)`	Return the label corresponding to the first non-falsy (including nan) value foun…
Detail	`SeriesHE.loc_notfalsy_last(*, fill_value)`	Return the label corresponding to the last non-falsy (including nan) value found…
Detail	`SeriesHE.loc_notna_first(*, fill_value)`	Return the label corresponding to the first not NA (None or nan) value found. Ar…
Detail	`SeriesHE.loc_notna_last(*, fill_value)`	Return the label corresponding to the last not NA (None or nan) value found. Arg…
Detail	`SeriesHE.loc_searchsorted(values, *, side_left, fill_value)`	Given a sorted Series, return the loc (label) position(s) at which insertion in…
Detail	`SeriesHE.max(axis, skipna)`	Return the maximum along the specified axis. Args: axis: Axis, defaulting to axi…
Detail	`SeriesHE.mean(axis, skipna, out)`	Return the mean along the specified axis. Args: axis: Axis, defaulting to axis 0…
Detail	`SeriesHE.median(axis, skipna, out)`	Return the median along the specified axis. Args: axis: Axis, defaulting to axis…
Detail	`SeriesHE.min(axis, skipna, out)`	Return the minimum along the specified axis. Args: axis: Axis, defaulting to axi…
Detail	`SeriesHE.notfalsy()`	Return a same-indexed, Boolean Series indicating which values are falsy.
Detail	`SeriesHE.notna()`	Return a same-indexed, Boolean Series indicating which values are NaN or None.
Detail	`SeriesHE.prod(axis, skipna, allna, out)`	Return the product along the specified axis. Args: axis: Axis, defaulting to axi…
Detail	`SeriesHE.rank_dense(*, skipna, ascending, start, fill_value)`	Rank values as compactly as possible, where ties get the same value, and ranks a…
Detail	`SeriesHE.rank_max(*, skipna, ascending, start, fill_value)`	Rank values where tied values are assigned the maximum ordinal rank; ranks are p…
Detail	`SeriesHE.rank_mean(*, skipna, ascending, start, fill_value)`	Rank values where tied values are assigned the mean of the ordinal ranks; ranks…
Detail	`SeriesHE.rank_min(*, skipna, ascending, start, fill_value)`	Rank values where tied values are assigned the minimum ordinal rank; ranks are p…
Detail	`SeriesHE.rank_ordinal(*, skipna, ascending, start, fill_value)`	Rank values distinctly, where ties get distinct values that maintain their order…
Detail	`SeriesHE.rehierarch(depth_map, *, index_constructors)`	Return a new Series with new a hierarchy based on the supplied depth_map.
Detail	`SeriesHE.reindex(index, *, fill_value, own_index, check_equals)`	Return a new Series with labels defined by the provided index. The size and orde…
Detail	`SeriesHE.relabel(index, *, index_constructor)`	Return a new Series with transformed labels on the index. The size and ordering…
Detail	`SeriesHE.relabel_flat()`	Return a new Series, where an IndexHierarchy (if defined) is replaced with a fla…
Detail	`SeriesHE.relabel_level_add(level)`	Return a new Series, adding a new root level to an existing IndexHierarchy, or c…
Detail	`SeriesHE.relabel_level_drop(count)`	Return a new Series, dropping one or more levels from a either the root or the l…
Detail	`SeriesHE.rename(name, *, index)`	Return a new Series with an updated name attribute.
Detail	`SeriesHE.roll(shift, *, include_index)`	Return a Series with values rotated forward and wrapped around the index (with a…
Detail	`SeriesHE.sample(count, *, seed)`	Randomly (optionally made deterministic with a fixed seed) extract items from th…
Detail	`SeriesHE.shift(shift, *, fill_value)`	Return a Series with values shifted forward on the index (with a positive shift)…
Detail	`SeriesHE.sort_index(*, ascending, kind, key)`	Return a new Series ordered by the sorted Index. Args: * ascendings: Boolean, or…
Detail	`SeriesHE.sort_values(*, ascending, kind, key)`	Return a new Series ordered by the sorted values. Args: * ascending: If True, so…
Detail	`SeriesHE.std(axis, skipna, ddof, out)`	Return the standard deviaton along the specified axis. Args: axis: Axis, default…
Detail	`SeriesHE.sum(axis, skipna, allna, out)`	Sum values along the specified axis. Args: axis: Axis, defaulting to axis 0. ski…
Detail	`SeriesHE.tail(count)`	Return a Series consisting only of the bottom elements as specified by count. s…
Detail	`SeriesHE.transpose()`	Transpose. For a 1D immutable container, this returns a reference to self. Retur…
Detail	`SeriesHE.unique()`	Return a NumPy array of unique values. Returns: numpy.ndarray
Detail	`SeriesHE.unique_enumerated(*, retain_order, func)`	Given a collection of values, return two NumPy arrays: the first provides index…
Detail	`SeriesHE.var(axis, skipna, ddof, out)`	Return the variance along the specified axis. Args: axis: Axis, defaulting to ax…