Access Top N Elements from Series Data Structure in Python

We have previously used slicing with the help of operator ‘:’, which is used in the case of extracting top ‘n’ elements from series structure. It helps assign a range to the series elements that will later be displayed.

Let us see an example −

Example

 Live Demo

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)
n = 3
print("Top 3 elements are :")
print(my_series[:n])

Output

The series contains following elements
ab  34
mn  56
gh  78
kl  90
wq  123
az  45
dtype: int64
Top 3 elements are :
ab  34
mn  56
gh  78
dtype: int64

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.

• A specific range of values can be accessed from the series using indexing ‘:’ operator in Python.

• The ‘:’ operator can be used between the lower range value and higher range value: [lower range : higher range].

• This will include the lower range value but exclude the higher range value.

• If no value is provided for lower range, it is taken as 0.

• If no value is provided for higher range, it is taken as len(data structure)-1.

• Here, it indicates that the lower range is 0 and higher range is 3.

• It is then printed on the console.