Class Index (1.0.0)

Index(data=None, dtype=None, *, name=None, session=None)

Immutable sequence used for indexing and alignment.

The basic object storing axis labels for all objects.

Properties

T

Return the transpose, which is by definition self.

dtype

Return the dtype object of the underlying data.

dtypes

Return the dtypes as a Series for the underlying MultiIndex.

empty

Returns True if the Index is empty, otherwise returns False.

has_duplicates

Check if the Index has duplicate values.

is_monotonic_decreasing

Return a boolean if the values are equal or decreasing.

is_monotonic_increasing

Return a boolean if the values are equal or increasing.

is_unique

Return if the index has unique values.

name

Returns Index name.

names

Returns the names of the Index.

ndim

API documentation for ndim property.

nlevels

Number of levels.

query_job

BigQuery job metadata for the most recent query.

shape

Return a tuple of the shape of the underlying data.

size

Returns the size of the Index.

values

Return an array representing the data in the Index.

Methods

all

all() -> bool

Return whether all elements are Truthy.

Returns
Type	Description
`bool`	A single element array-like may be converted to bool.

any

any() -> bool

Return whether any element is Truthy.

Returns
Type	Description
`bool`	A single element array-like may be converted to bool.

argmax

argmax() -> int

Return int position of the largest value in the Series.

If the maximum is achieved in multiple locations, the first row position is returned.

Returns
Type	Description
`int`	Row position of the maximum value.

argmin

argmin() -> int

Return int position of the smallest value in the Series.

If the minimum is achieved in multiple locations, the first row position is returned.

Returns
Type	Description
`int`	Row position of the minimum value.

astype

astype(
    dtype: typing.Union[
        typing.Literal[
            "boolean",
            "Float64",
            "Int64",
            "int64[pyarrow]",
            "string",
            "string[pyarrow]",
            "timestamp[us, tz=UTC][pyarrow]",
            "timestamp[us][pyarrow]",
            "date32[day][pyarrow]",
            "time64[us][pyarrow]",
            "decimal128(38, 9)[pyarrow]",
            "decimal256(76, 38)[pyarrow]",
            "binary[pyarrow]",
        ],
        pandas.core.arrays.boolean.BooleanDtype,
        pandas.core.arrays.floating.Float64Dtype,
        pandas.core.arrays.integer.Int64Dtype,
        pandas.core.arrays.string_.StringDtype,
        pandas.core.dtypes.dtypes.ArrowDtype,
        geopandas.array.GeometryDtype,
    ]
) -> bigframes.core.indexes.index.Index

Create an Index with values cast to dtypes.

The class of a new Index is determined by dtype. When conversion is impossible, a TypeError exception is raised.

Returns
Type	Description
`Index`	Index with values cast to specified dtype.

copy

copy(name: typing.Optional[typing.Hashable] = None)

Make a copy of this object.

Name is set on the new object.

Parameter
Name	Description
`name`	`Label, optional` Set name for new object.

Returns
Type	Description
`Index`	Index refer to new object which is a copy of this object.

drop

drop(labels: typing.Any) -> bigframes.core.indexes.index.Index

Make new Index with passed list of labels deleted.

Returns
Type	Description
`Index`	Will be same type as self

drop_duplicates

drop_duplicates(*, keep: str = "first") -> bigframes.core.indexes.index.Index

Return Index with duplicate values removed.

Parameter
Name	Description
`keep`	`{'first', 'last', False}, default 'first'` One of: 'first' : Drop duplicates except for the first occurrence. 'last' : Drop duplicates except for the last occurrence. `False` : Drop all duplicates.

dropna

dropna(how: str = "any") -> bigframes.core.indexes.index.Index

Return Index without NA/NaN values.

Parameter
Name	Description
`how`	`{'any', 'all'}, default 'any'` If the Index is a MultiIndex, drop the value when any or all levels are NaN.

fillna

fillna(value=None) -> bigframes.core.indexes.index.Index

Fill NA/NaN values with the specified value.

Parameter
Name	Description
`value`	`scalar` Scalar value to use to fill holes (e.g. 0). This value cannot be a list-likes.

from_frame

from_frame(
    frame: typing.Union[bigframes.series.Series, bigframes.dataframe.DataFrame]
) -> bigframes.core.indexes.index.Index

API documentation for from_frame method.

get_level_values

get_level_values(level) -> bigframes.core.indexes.index.Index

Return an Index of values for requested level.

This is primarily useful to get an individual level of values from a MultiIndex, but is provided on Index as well for compatibility.

Parameter
Name	Description
`level`	`int or str` It is either the integer position or the name of the level.

Returns
Type	Description
`Index`	Calling object, as there is only one level in the Index.

isin

isin(values) -> bigframes.core.indexes.index.Index

Return a boolean array where the index values are in values.

Compute boolean array of whether each index value is found in the passed set of values. The length of the returned boolean array matches the length of the index.

Parameter
Name	Description
`values`	`set or list-like` Sought values.

Returns
Type	Description
`Series`	Series of boolean values.

max

max() -> typing.Any

Return the maximum value of the Index.

Returns
Type	Description
`scalar`	Maximum value.

min

min() -> typing.Any

Return the minimum value of the Index.

Returns
Type	Description
`scalar`	Minimum value.

nunique

nunique() -> int

Return number of unique elements in the object.

Excludes NA values by default.

rename

rename(
    name: typing.Union[str, typing.Sequence[str]]
) -> bigframes.core.indexes.index.Index

Alter Index or MultiIndex name.

Able to set new names without level. Defaults to returning new index. Length of names must match number of levels in MultiIndex.

Parameter
Name	Description
`name`	`label or list of labels` Name(s) to set.

Returns
Type	Description
`Index`	The same type as the caller.

sort_values

sort_values(*, ascending: bool = True, na_position: str = "last")

Return a sorted copy of the index.

Return a sorted copy of the index, and optionally return the indices that sorted the index itself.

Parameters
Name	Description
`ascending`	`bool, default True` Should the index values be sorted in an ascending order.
`na_position`	`{'first' or 'last'}, default 'last'` Argument 'first' puts NaNs at the beginning, 'last' puts NaNs at the end.

Returns
Type	Description
`pandas.Index`	Sorted copy of the index.

to_numpy

to_numpy(dtype=None, **kwargs) -> numpy.ndarray

A NumPy ndarray representing the values in this Series or Index.

to_pandas

to_pandas() -> pandas.core.indexes.base.Index

Gets the Index as a pandas Index.

Returns
Type	Description
`pandas.Index`	A pandas Index with all of the labels from this Index.

to_series

to_series(
    index: typing.Optional[bigframes.core.indexes.index.Index] = None,
    name: typing.Optional[typing.Hashable] = None,
) -> bigframes.series.Series

Create a Series with both index and values equal to the index keys.

Useful with map for returning an indexer based on an index.

Parameters
Name	Description
`index`	`Index, optional` Index of resulting Series. If None, defaults to original index.
`name`	`str, optional` Name of resulting Series. If None, defaults to name of original index.

Returns
Type	Description
`Series`	The dtype will be based on the type of the Index values.

transpose

transpose() -> bigframes.core.indexes.index.Index

Return the transpose, which is by definition self.

value_counts

value_counts(
    normalize: bool = False,
    sort: bool = True,
    ascending: bool = False,
    *,
    dropna: bool = True
)

Return a Series containing counts of unique values.

The resulting object will be in descending order so that the first element is the most frequently-occurring element. Excludes NA values by default.

Parameters
Name	Description
`normalize`	`bool, default False` If True then the object returned will contain the relative frequencies of the unique values.
`sort`	`bool, default True` Sort by frequencies.
`ascending`	`bool, default False` Sort in ascending order.
`dropna`	`bool, default True` Don't include counts of NaN.