Pandas: Index Objects

Index Objects

• The index objects are responsible for labelling the axis. For example

Python program

import pandas as pd

data = [10,20,30,40]

x = pd.Series(data, index=["a","b","c","d"], dtype = float)

print(x)

index = x.index← index object

print(index)

Output

a     10.0

b     20.0

c    30.0

d    40.0

dtype: float64

Index(['a', 'b', 'c', 'd'], dtype='object')

The above output indicates that we can display the labels of indices using the index object.

Now if we want to change the label of some index then we get an error because the index objects are immutable

In [7]: index[1] = "w"

Traceback (most recent call last):

Cell In[7], line 1

index[1] = "w"

File ̰ \anaconda3\Lib\site‒packages\pandas\core\indexes\base.py:5157in_setitem_raise TypeError("Index does not support mutable operations")

TypeError: Index does not support mutable operations.

Index methods and properties

Method : Purpose

append ‒ The function is used to append a single or a collection of indices together. In the case of a collection of indices, all of them get appended to the original index in the same order as they are passed to the Index.append() function.

difference ‒ This function computes the set differences as an index.

intersection ‒ This function computes the set intersection as an index.

union ‒ Computes the set union.

delete ‒ This function computes the new index with the element at index i is deleted.

insert ‒ This function computes the new index by inserting element at index i

is_ unique ‒ This function returns true if the index has no duplicate values.

unique ‒ Computes the array of unique values in the index.