databricks.koalas.MultiIndex

class databricks.koalas.MultiIndex(kdf: databricks.koalas.frame.DataFrame)[source]

Koalas MultiIndex that corresponds to pandas MultiIndex logically. This might hold Spark Column internally.

Variables
  • _kdf – The parent dataframe

  • _scol – Spark Column instance

See also

Index

A single-level Index.

Examples

>>> ks.DataFrame({'a': ['a', 'b', 'c']}, index=[[1, 2, 3], [4, 5, 6]]).index  
MultiIndex([(1, 4),
            (2, 5),
            (3, 6)],
           )
>>> ks.DataFrame({'a': [1, 2, 3]}, index=[list('abc'), list('def')]).index  
MultiIndex([('a', 'd'),
            ('b', 'e'),
            ('c', 'f')],
           )
__init__(kdf: databricks.koalas.frame.DataFrame)[source]

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__(kdf)

Initialize self.

all(*args, **kwargs)

Return whether all elements are True.

any(*args, **kwargs)

Return whether any element is True.

append(other)

Append a collection of Index options together.

argmax()

Return a maximum argument indexer.

argmin()

Return a minimum argument indexer.

asof(label)

Return the label from the index, or, if not present, the previous one.

astype(dtype)

Cast a Koalas object to a specified dtype dtype.

copy([deep])

Make a copy of this object.

delete(loc)

Make new Index with passed location(-s) deleted.

difference(other[, sort])

Return a new Index with elements from the index that are not in other.

drop(codes[, level])

Make new MultiIndex with passed list of labels deleted

drop_duplicates()

Return Index with duplicate values removed.

droplevel(level)

Return index with requested level(s) removed.

dropna()

Return Index or MultiIndex without NA/NaN values

equals(other)

Determine if two Index objects contain the same elements.

fillna(value)

Fill NA/NaN values with the specified value.

from_arrays(arrays[, sortorder, names])

Convert arrays to MultiIndex.

from_product(iterables[, sortorder, names])

Make a MultiIndex from the cartesian product of multiple iterables.

from_tuples(tuples[, sortorder, names])

Convert list of tuples to MultiIndex.

get_level_values(level)

Return vector of label values for requested level, equal to the length of the index.

holds_integer()

Whether the type is an integer type.

identical(other)

Similar to equals, but check that other comparable attributes are also equal.

is_boolean()

Return if the current index type is a boolean type.

is_categorical()

Return if the current index type is a categorical type.

is_floating()

Return if the current index type is a floating type.

is_integer()

Return if the current index type is a integer type.

is_interval()

Return if the current index type is an interval type.

is_numeric()

Return if the current index type is a numeric type.

is_object()

Return if the current index type is a object type.

isin(values)

Check whether values are contained in Series.

isna()

Detect existing (non-missing) values.

isnull()

Detect existing (non-missing) values.

max()

Return the maximum value of the Index.

min()

Return the minimum value of the Index.

notna()

Detect existing (non-missing) values.

notnull()

Detect existing (non-missing) values.

nunique([dropna])

Return number of unique elements in the object.

rename(name[, inplace])

Alter Index or MultiIndex name.

repeat(repeats)

Repeat elements of a Index/MultiIndex.

set_names(names[, level, inplace])

Set Index or MultiIndex name.

shift([periods, fill_value])

Shift Series/Index by desired number of periods.

sort(*args, **kwargs)

Use sort_values instead.

sort_values([ascending])

Return a sorted copy of the index.

swaplevel([i, j])

Swap level i with level j.

symmetric_difference(other[, result_name, sort])

Compute the symmetric difference of two MultiIndex objects.

take(indices)

Return the elements in the given positional indices along an axis.

toPandas()

Return a pandas MultiIndex.

to_frame([index, name])

Create a DataFrame with the levels of the MultiIndex as columns.

to_numpy([dtype, copy])

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

to_pandas()

Return a pandas MultiIndex.

to_series([name])

Create a Series with both index and values equal to the index keys useful with map for returning an indexer based on an index.

transpose()

Return the transpose, For index, It will be index itself.

union(other[, sort])

Form the union of two Index objects.

unique([level])

Return unique values in the index.

value_counts([normalize, sort, ascending, …])

Return a Series containing counts of unique values.

Attributes

T

Return the transpose, For index, It will be index itself.

dtype

Return the dtype object of the underlying data.

empty

Returns true if the current object is empty.

has_duplicates

If index has duplicates, return True, otherwise False.

hasnans

Return True if it has any missing values.

is_all_dates

is_all_dates always returns False for MultiIndex

is_monotonic

Return boolean if values in the object are monotonically increasing.

is_monotonic_decreasing

Return boolean if values in the object are monotonically decreasing.

is_monotonic_increasing

Return boolean if values in the object are monotonically increasing.

levshape

A tuple with the length of each level.

name

Return name of the Index.

names

Return names of the Index.

ndim

Return an int representing the number of array dimensions.

nlevels

Number of levels in Index & MultiIndex.

shape

Return a tuple of the shape of the underlying data.

size

Return an int representing the number of elements in this object.

spark_column

Spark Column object representing the Series/Index.

spark_type

Returns the data type as defined by Spark, as a Spark DataType object.

values

Return an array representing the data in the Index.