Overview: Series: Method

Detail: Series: Method

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Series.__array__(dtype)

Support the __array__ interface, returning an array of values.

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Series.__array_ufunc__(ufunc, method, *args, **kwargs)

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

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Series.__bool__()

Raises ValueError to prohibit ambiguous use of truethy evaluation.

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Series.__deepcopy__(memo)

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Series.__len__()

Length of values.

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Series.__round__(decimals)

Return a Series rounded to the given decimals. Negative decimals round to the le…

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Series.all(axis, skipna, out)

Logical and over values along the specified axis. Args: axis: Axis, defaulting t…

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Series.any(axis, skipna, out)

Logical or over values along the specified axis. Args: axis: Axis, defaulting to…

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Series.astype(dtype)

Return a Series with type determined by dtype argument. Note that for Series, th…

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Series.clip(*, lower, upper)

Apply a clip operation to this Series. Note that clip operations can be applied…

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Series.corr(other)

Return the index-aligned correlation to the supplied Series. Args: other: Series…

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Series.count(*, skipna, skipfalsy, unique, axis)

Return the count of non-NA, non-falsy, and/or unique elements. Args: skipna: ski…

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Series.cov(other, *, ddof)

Return the index-aligned covariance to the supplied Series. Args: ddof: Delta de…

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Series.cumprod(axis, skipna)

Return the cumulative product over the specified axis. Args: axis: Axis, default…

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Series.cumsum(axis, skipna)

Return the cumulative sum over the specified axis. Args: axis: Axis, defaulting…

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Series.drop_duplicated(*, exclude_first, exclude_last)

Return a Series with duplicated values removed. Args: exclude_first: Boolean to…

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Series.dropfalsy()

Return a new Series after removing values of falsy.

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Series.dropna()

Return a new Series after removing values of NaN or None.

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Series.duplicated(*, exclude_first, exclude_last)

Return a same-sized Boolean Series that shows True for all values that are dupli…

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Series.equals(other, *, compare_name, compare_dtype, compare_class, skipna)

Return a bool from comparison to any other object. Args: compare_name: Include e…

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Series.fillfalsy(value)

Return a new Series after replacing falsy values with the supplied value. The va…

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Series.fillfalsy_backward(limit)

Return a new Series after feeding backward the last non-falsy observation across…

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Series.fillfalsy_forward(limit)

Return a new Series after feeding forward the last non-falsy observation across…

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Series.fillfalsy_leading(value)

Return a new Series after filling leading (and only leading) falsy values with t…

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Series.fillfalsy_trailing(value)

Return a new Series after filling trailing (and only trailing) falsy values with…

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Series.fillna(value)

Return a new Series after replacing NA (NaN or None) with the supplied value. Th…

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Series.fillna_backward(limit)

Return a new Series after feeding backward the last non-null (NaN or None) obser…

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Series.fillna_forward(limit)

Return a new Series after feeding forward the last non-null (NaN or None) observ…

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Series.fillna_leading(value)

Return a new Series after filling leading (and only leading) null (NaN or None)…

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Series.fillna_trailing(value)

Return a new Series after filling trailing (and only trailing) null (NaN or None…

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Series.head(count)

Return a Series consisting only of the top elements as specified by count. Args:…

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Series.iloc_max(*, skipna)

Return the integer index corresponding to the maximum value. Args: skipna: if Tr…

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Series.iloc_min(*, skipna)

Return the integer index corresponding to the minimum value found. Args: skipna:…

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Series.iloc_notfalsy_first(*, fill_value)

Return the position corresponding to the first non-falsy (including nan) value f…

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Series.iloc_notfalsy_last(*, fill_value)

Return the position corresponding to the last non-falsy (including nan) value fo…

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Series.iloc_notna_first(*, fill_value)

Return the position corresponding to the first not NA (None or nan) value found….

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Series.iloc_notna_last(*, fill_value)

Return the position corresponding to the last not NA (None or nan) value found….

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Series.iloc_searchsorted(values, *, side_left)

Given a sorted Series, return the iloc (integer) position(s) at which insertion…

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Series.insert_after(key, container)

Create a new Series by inserting a Series at the position after the label specif…

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Series.insert_before(key, container)

Create a new Series by inserting a Series at the position before the label speci…

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Series.isfalsy()

Return a same-indexed, Boolean Series indicating which values are falsy.

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Series.isin(other)

Return a same-sized Boolean Series that shows if the same-positioned element is…

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Series.isna()

Return a same-indexed, Boolean Series indicating which values are NaN or None.

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Series.loc_max(*, skipna)

Return the label corresponding to the maximum value found. Args: skipna: if True…

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Series.loc_min(*, skipna)

Return the label corresponding to the minimum value found. Args: skipna: if True…

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Series.loc_notfalsy_first(*, fill_value)

Return the label corresponding to the first non-falsy (including nan) value foun…

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Series.loc_notfalsy_last(*, fill_value)

Return the label corresponding to the last non-falsy (including nan) value found…

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Series.loc_notna_first(*, fill_value)

Return the label corresponding to the first not NA (None or nan) value found. Ar…

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Series.loc_notna_last(*, fill_value)

Return the label corresponding to the last not NA (None or nan) value found. Arg…

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Series.loc_searchsorted(values, *, side_left, fill_value)

Given a sorted Series, return the loc (label) position(s) at which insertion in…

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Series.max(axis, skipna)

Return the maximum along the specified axis. Args: axis: Axis, defaulting to axi…

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Series.mean(axis, skipna, out)

Return the mean along the specified axis. Args: axis: Axis, defaulting to axis 0…

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Series.median(axis, skipna, out)

Return the median along the specified axis. Args: axis: Axis, defaulting to axis…

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Series.min(axis, skipna, out)

Return the minimum along the specified axis. Args: axis: Axis, defaulting to axi…

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Series.notfalsy()

Return a same-indexed, Boolean Series indicating which values are falsy.

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Series.notna()

Return a same-indexed, Boolean Series indicating which values are NaN or None.

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Series.prod(axis, skipna, out)

Return the product along the specified axis. Args: axis: Axis, defaulting to axi…

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Series.rank_dense(*, skipna, ascending, start, fill_value)

Rank values as compactly as possible, where ties get the same value, and ranks a…

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Series.rank_max(*, skipna, ascending, start, fill_value)

Rank values where tied values are assigned the maximum ordinal rank; ranks are p…

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Series.rank_mean(*, skipna, ascending, start, fill_value)

Rank values where tied values are assigned the mean of the ordinal ranks; ranks…

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Series.rank_min(*, skipna, ascending, start, fill_value)

Rank values where tied values are assigned the minimum ordinal rank; ranks are p…

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Series.rank_ordinal(*, skipna, ascending, start, fill_value)

Rank values distinctly, where ties get distinct values that maintain their order…

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Series.rehierarch(depth_map, *, index_constructors)

Return a new Series with new a hierarchy based on the supplied depth_map.

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Series.reindex(index, *, fill_value, own_index, check_equals)

Return a new Series with labels defined by the provided index. The size and orde…

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Series.relabel(index, *, index_constructor)

Return a new Series with transformed labels on the index. The size and ordering…

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Series.relabel_flat()

Return a new Series, where an IndexHierarchy (if defined) is replaced with a fla…

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Series.relabel_level_add(level)

Return a new Series, adding a new root level to an existing IndexHierarchy, or c…

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Series.relabel_level_drop(count)

Return a new Series, dropping one or more levels from a either the root or the l…

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Series.rename(name, *, index)

Return a new Series with an updated name attribute.

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Series.roll(shift, *, include_index)

Return a Series with values rotated forward and wrapped around the index (with a…

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Series.sample(count, *, seed)

Randomly (optionally made deterministic with a fixed seed) extract items from th…

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Series.shift(shift, *, fill_value)

Return a Series with values shifted forward on the index (with a positive shift)…

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Series.sort_index(*, ascending, kind, key)

Return a new Series ordered by the sorted Index. Args: * ascendings: Boolean, or…

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Series.sort_values(*, ascending, kind, key)

Return a new Series ordered by the sorted values. Args: * ascending: If True, so…

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Series.std(axis, skipna, ddof, out)

Return the standard deviaton along the specified axis. Args: axis: Axis, default…

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Series.sum(axis, skipna, out)

Sum values along the specified axis. Args: axis: Axis, defaulting to axis 0. ski…

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Series.tail(count)

Return a Series consisting only of the bottom elements as specified by count. s…

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Series.transpose()

Transpose. For a 1D immutable container, this returns a reference to self. Retur…

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Series.unique()

Return a NumPy array of unique values. Returns: numpy.ndarray

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Series.var(axis, skipna, ddof, out)

Return the variance along the specified axis. Args: axis: Axis, defaulting to ax…

Series: Constructor | Exporter | Attribute | Method | Dictionary-Like | Display | Assignment | Selector | Iterator | Operator Binary | Operator Unary | Accessor Values | Accessor Datetime | Accessor String | Accessor Fill Value | Accessor Regular Expression | Accessor Hashlib