If default values are used as index values in Series, they can be accessed using indexing. If the index values are customized, they are passed as index values and displayed on the console.
Let us understand it with the help of an example.
Example
import pandas as pd
my_data = [34, 56, 78, 90, 123, 45]
my_index = ['ab', 'mn' ,'gh','kl', 'wq', 'az']
my_series = pd.Series(my_data, index = my_index)
print("The series contains following elements")
print(my_series)
print("Accessing elements using customized index")
print(my_series['mn'])
print("Accessing elements using customized index")
print(my_series['az'])Output
The series contains following elements ab 34 mn 56 gh 78 kl 90 wq 123 az 45 dtype: int64 Accessing elements using customized index 56 Accessing elements using customized index 45
Explanation
The required libraries are imported, and given alias names for ease of use.
A list of data values is created, that is later passed as a parameter to the ‘Series’ function present in the ‘pandas’ library
Next, customized index values (that are passed as parameter later) are stored in a list.
The series is created and index list and data are passed as parameters to it.
The series is printed on the console.
Since the index values are customized, they are used to access the values in the series like series_name[‘index_name’].
It is then printed on the console.