pandas.Index — pandas 0.18.1 documentation (original) (raw)

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([axis])

return a ndarray of the maximum argument indexer

argmin([axis])

return a ndarray of the minimum argument indexer

argsort(*args, **kwargs)

Returns the indices that would sort the index and its underlying data.

asof(label)

For a sorted index, return the most recent label up to and including the passed label.

asof_locs(where, mask)

where : array of timestamps

astype(dtype)

copy([name, deep, dtype])

Make a copy of this object.

delete(loc)

Make new Index with passed location(-s) deleted

diff(*args, **kwargs)

difference(other)

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

drop(labels[, errors])

Make new Index with passed list of labels deleted

drop_duplicates(*args, **kwargs)

Return Index with duplicate values removed

duplicated(*args, **kwargs)

Return boolean np.array denoting duplicate values

equals(other)

Determines if two Index objects contain the same elements.

factorize([sort, na_sentinel])

Encode the object as an enumerated type or categorical variable

fillna([value, downcast])

Fill NA/NaN values with the specified value

format([name, formatter])

Render a string representation of the Index

get_duplicates()

get_indexer(target[, method, limit, tolerance])

Compute indexer and mask for new index given the current index.

get_indexer_for(target, **kwargs)

guaranteed return of an indexer even when non-unique

get_indexer_non_unique(target)

return an indexer suitable for taking from a non unique index

get_level_values(level)

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

get_loc(key[, method, tolerance])

Get integer location for requested label

get_slice_bound(label, side, kind)

Calculate slice bound that corresponds to given label.

get_value(series, key)

Fast lookup of value from 1-dimensional ndarray.

get_values()

return the underlying data as an ndarray

groupby(to_groupby)

Group the index labels by a given array of values.

holds_integer()

identical(other)

Similar to equals, but check that other comparable attributes are

insert(loc, item)

Make new Index inserting new item at location.

intersection(other)

Form the intersection of two Index objects.

is_(other)

More flexible, faster check like is but that works through views

is_boolean()

is_categorical()

is_floating()

is_integer()

is_lexsorted_for_tuple(tup)

is_mixed()

is_numeric()

is_object()

is_type_compatible(kind)

isin(values[, level])

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

item()

return the first element of the underlying data as a python

join(other[, how, level, return_indexers])

this is an internal non-public method

map(mapper)

Apply mapper function to its values.

max()

The maximum value of the object

memory_usage([deep])

Memory usage of my values

min()

The minimum value of the object

nunique([dropna])

Return number of unique elements in the object.

order([return_indexer, ascending])

Return sorted copy of Index

putmask(mask, value)

return a new Index of the values set with the mask

ravel([order])

return an ndarray of the flattened values of the underlying data

reindex(target[, method, level, limit, ...])

Create index with target’s values (move/add/delete values as necessary)

rename(name[, inplace])

Set new names on index.

repeat(n, *args, **kwargs)

Repeat elements of an Index.

searchsorted(key[, side, sorter])

Find indices where elements should be inserted to maintain order.

set_names(names[, level, inplace])

Set new names on index.

set_value(arr, key, value)

Fast lookup of value from 1-dimensional ndarray.

shift([periods, freq])

Shift Index containing datetime objects by input number of periods and

slice_indexer([start, end, step, kind])

For an ordered Index, compute the slice indexer for input labels and

slice_locs([start, end, step, kind])

Compute slice locations for input labels.

sort(*args, **kwargs)

sort_values([return_indexer, ascending])

Return sorted copy of Index

sortlevel([level, ascending, sort_remaining])

For internal compatibility with with the Index API

str

alias of StringMethods

summary([name])

sym_diff(*args, **kwargs)

symmetric_difference(other[, result_name])

Compute the sorted symmetric difference of two Index objects.

take(indices[, axis, allow_fill, fill_value])

return a new %(klass)s of the values selected by the indices

to_datetime([dayfirst])

For an Index containing strings or datetime.datetime objects, attempt

to_native_types([slicer])

slice and dice then format

to_series(**kwargs)

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

tolist()

return a list of the Index values

transpose(*args, **kwargs)

return the transpose, which is by definition self

union(other)

Form the union of two Index objects and sorts if possible.

unique()

Return array of unique values in the object.

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

Returns object containing counts of unique values.

view([cls])