Python | Pandas Series.nlargest()

Pandas series is a One-dimensional ndarray with axis labels. The labels need not be unique but must be a hashable type. The object supports both integer- and label-based indexing and provides a host of methods for performing operations involving the index.

Pandas Series.nlargest() function return the n largest element from the underlying data in the given series object.

Syntax: Series.nlargest(n=5, keep=’first’)

Parameter :
n : Return this many descending sorted values.
keep : {‘first’, ‘last’, ‘all’}, default ‘first’

Returns : Series

Example #1: Use Series.nlargest() function to return the first n largest element from the given series object.

# importing pandas as pd
import pandas as pd

# Creating the Series
sr = pd.Series([10, 25, 3, 11, 24, 6])

# Create the Index
index_ = ['Coca Cola', 'Sprite', 'Coke', 'Fanta', 'Dew', 'ThumbsUp']

# set the index
sr.index = index_

# Print the series
print(sr)

Output :

Now we will use Series.nlargest() function to find the first 2 largest value in the given series object.

# return the first 2 of the largest
# element
result = sr.nlargest(n = 2)

# Print the result
print(result)

Output :

As we can see in the output, the Series.nlargest() function has successfully returned the first 2 largest value in the given series object.

Example #2: Use Series.nlargest() function to return the first n largest element from the given series object.

# importing pandas as pd
import pandas as pd

# Creating the Series
sr = pd.Series([11, 21, 8, 18, 65, 84, 32, 10, 5, 24, 32])

# Print the series
print(sr)

Output :

Now we will use Series.nlargest() function to find the first 5 largest value in the given series object.

# return the first 5 of the largest
# element
result = sr.nlargest(n = 5)

# Print the result
print(result)

Output :

As we can see in the output, the Series.nlargest() function has successfully returned the first 5 largest value in the given series object.