When the index values are customized, they are accessed using series_name[‘index_value’]. The ‘index_value’ passed to series is tried to be matched to the original series. If it is found, that corresponding data is also displayed on the console.
When the index that is tried to be accessed is not present in the series, it throws an error. It has been shown below.
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['mm'])
The series contains following elements ab 34 mn 56 gh 78 kl 90 wq 123 az 45 dtype: int64 Accessing elements using customized index Traceback (most recent call last): KeyError: 'mm'
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 searched for in the series but when it is not found, it throws a ‘KeyError’.
It is then printed on the console.