Index(data[, dtype, name])
Index
Koalas Index that corresponds to pandas Index logically.
Index.is_monotonic
Return boolean if values in the object are monotonically increasing.
Index.is_monotonic_increasing
Index.is_monotonic_decreasing
Return boolean if values in the object are monotonically decreasing.
Index.has_duplicates
If index has duplicates, return True, otherwise False.
Index.hasnans
Return True if it has any missing values.
Index.dtype
Return the dtype object of the underlying data.
Index.is_all_dates
Return if all data types of the index are datetime.
Index.shape
Return a tuple of the shape of the underlying data.
Index.name
Return name of the Index.
Index.names
Return names of the Index.
Index.ndim
Return an int representing the number of array dimensions.
Index.size
Return an int representing the number of elements in this object.
Index.nlevels
Number of levels in Index & MultiIndex.
Index.empty
Returns true if the current object is empty.
Index.T
Return the transpose, For index, It will be index itself.
Index.values
Return an array representing the data in the Index.
Index.all([axis])
Index.all
Return whether all elements are True.
Index.any([axis])
Index.any
Return whether any element is True.
Index.argmin()
Index.argmin
Return a minimum argument indexer.
Index.argmax()
Index.argmax
Return a maximum argument indexer.
Index.copy([name, deep])
Index.copy
Make a copy of this object.
Index.delete(loc)
Index.delete
Make new Index with passed location(-s) deleted.
Index.equals(other)
Index.equals
Determine if two Index objects contain the same elements.
Index.identical(other)
Index.identical
Similar to equals, but check that other comparable attributes are also equal.
Index.is_boolean()
Index.is_boolean
Return if the current index type is a boolean type.
Index.is_categorical()
Index.is_categorical
Return if the current index type is a categorical type.
Index.is_floating()
Index.is_floating
Return if the current index type is a floating type.
Index.is_integer()
Index.is_integer
Return if the current index type is a integer type.
Index.is_interval()
Index.is_interval
Return if the current index type is an interval type.
Index.is_numeric()
Index.is_numeric
Return if the current index type is a numeric type.
Index.is_object()
Index.is_object
Return if the current index type is a object type.
Index.drop(labels)
Index.drop
Make new Index with passed list of labels deleted.
Index.drop_duplicates()
Index.drop_duplicates
Return Index with duplicate values removed.
Index.min()
Index.min
Return the minimum value of the Index.
Index.max()
Index.max
Return the maximum value of the Index.
Index.rename(name[, inplace])
Index.rename
Alter Index or MultiIndex name.
Index.repeat(repeats)
Index.repeat
Repeat elements of a Index/MultiIndex.
Index.take(indices)
Index.take
Return the elements in the given positional indices along an axis.
Index.unique([level])
Index.unique
Return unique values in the index.
Index.nunique([dropna, approx, rsd])
Index.nunique
Return number of unique elements in the object.
Index.value_counts([normalize, sort, …])
Index.value_counts
Return a Series containing counts of unique values.
Index.set_names(names[, level, inplace])
Index.set_names
Set Index or MultiIndex name.
Index.droplevel(level)
Index.droplevel
Return index with requested level(s) removed.
Index.fillna(value)
Index.fillna
Fill NA/NaN values with the specified value.
Index.dropna()
Index.dropna
Return Index or MultiIndex without NA/NaN values
Index.isna()
Index.isna
Detect existing (non-missing) values.
Index.notna()
Index.notna
Index.astype(dtype)
Index.astype
Cast a Koalas object to a specified dtype dtype.
dtype
Index.to_series([name])
Index.to_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.
Index.to_frame([index, name])
Index.to_frame
Create a DataFrame with a column containing the Index.
Index.to_numpy([dtype, copy])
Index.to_numpy
A NumPy ndarray representing the values in this Index or MultiIndex.
Index.spark provides features that does not exist in pandas but in Spark. These can be accessed by Index.spark.<function/property>.
Index.spark
Index.spark.<function/property>
Index.spark.data_type
Returns the data type as defined by Spark, as a Spark DataType object.
Index.spark.column
Spark Column object representing the Series/Index.
Index.spark.transform(func)
Index.spark.transform
Applies a function that takes and returns a Spark column.
Index.sort_values([ascending])
Index.sort_values
Return a sorted copy of the index.
Index.shift([periods, fill_value])
Index.shift
Shift Series/Index by desired number of periods.
Index.append(other)
Index.append
Append a collection of Index options together.
Index.union(other[, sort])
Index.union
Form the union of two Index objects.
Index.difference(other[, sort])
Index.difference
Return a new Index with elements from the index that are not in other.
Index.symmetric_difference(other[, …])
Index.symmetric_difference
Compute the symmetric difference of two Index objects.
Index.asof(label)
Index.asof
Return the label from the index, or, if not present, the previous one.
Index.isin(values)
Index.isin
Check whether values are contained in Series.
MultiIndex(kdf)
MultiIndex
Koalas MultiIndex that corresponds to pandas MultiIndex logically.
MultiIndex.from_arrays(arrays[, sortorder, …])
MultiIndex.from_arrays
Convert arrays to MultiIndex.
MultiIndex.from_tuples(tuples[, sortorder, …])
MultiIndex.from_tuples
Convert list of tuples to MultiIndex.
MultiIndex.from_product(iterables[, …])
MultiIndex.from_product
Make a MultiIndex from the cartesian product of multiple iterables.
MultiIndex.has_duplicates
MultiIndex.hasnans
MultiIndex.is_all_dates
is_all_dates always returns False for MultiIndex
MultiIndex.shape
MultiIndex.names
MultiIndex.ndim
MultiIndex.empty
MultiIndex.T
MultiIndex.size
MultiIndex.nlevels
MultiIndex.levshape
A tuple with the length of each level.
MultiIndex.values
MultiIndex.swaplevel([i, j])
MultiIndex.swaplevel
Swap level i with level j.
MultiIndex.droplevel(level)
MultiIndex.droplevel
MultiIndex.fillna(value)
MultiIndex.fillna
MultiIndex.dropna()
MultiIndex.dropna
MultiIndex.equals(other)
MultiIndex.equals
MultiIndex.identical(other)
MultiIndex.identical
MultiIndex.drop(codes[, level])
MultiIndex.drop
Make new MultiIndex with passed list of labels deleted
MultiIndex.copy([deep])
MultiIndex.copy
MultiIndex.delete(loc)
MultiIndex.delete
MultiIndex.rename(name[, inplace])
MultiIndex.rename
MultiIndex.repeat(repeats)
MultiIndex.repeat
MultiIndex.take(indices)
MultiIndex.take
MultiIndex.unique([level])
MultiIndex.unique
MultiIndex.min()
MultiIndex.min
MultiIndex.max()
MultiIndex.max
MultiIndex.value_counts([normalize, sort, …])
MultiIndex.value_counts
MultiIndex.append(other)
MultiIndex.append
MultiIndex.union(other[, sort])
MultiIndex.union
MultiIndex.difference(other[, sort])
MultiIndex.difference
MultiIndex.symmetric_difference(other[, …])
MultiIndex.symmetric_difference
Compute the symmetric difference of two MultiIndex objects.
MultiIndex.astype(dtype)
MultiIndex.astype
MultiIndex.to_series([name])
MultiIndex.to_series
MultiIndex.to_frame([index, name])
MultiIndex.to_frame
Create a DataFrame with the levels of the MultiIndex as columns.
MultiIndex.to_numpy([dtype, copy])
MultiIndex.to_numpy
MultiIndex.spark provides features that does not exist in pandas but in Spark. These can be accessed by MultiIndex.spark.<function/property>.
MultiIndex.spark
MultiIndex.spark.<function/property>
MultiIndex.spark.data_type
MultiIndex.spark.column
MultiIndex.spark.transform(func)
MultiIndex.spark.transform
MultiIndex.sort_values([ascending])
MultiIndex.sort_values