Python | Pandas Series.nlargest() Last Updated : 11 Feb, 2019 Comments Improve Suggest changes Like Article Like Report 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. Python3 # 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. Python3 # 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. Python3 # 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. Python3 # 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. Comment More infoAdvertise with us Next Article Python | Pandas Series.nlargest() S Shubham__Ranjan Follow Improve Article Tags : Python Pandas Python-pandas Python pandas-series-methods AI-ML-DS With Python +1 More Practice Tags : python Similar Reads Python | Pandas Series.last() 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.last() function is a convenie 2 min read Python | Pandas Series.argsort() 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.argsort() function returns th 3 min read Python | Pandas Series.argsort() With the help of Pandas Series.argsort(), one can sort the elements of series in pandas. But the main thing in pandas series is we get the output as index values of the sorted elements in series. In the later code demonstration, we will explain that how we get the output as sorted index values. Synt 3 min read Python | Pandas Series.nsmallest() 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.nsmallest() function return t 2 min read Python | Pandas Series.le() Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric Python packages. Pandas is one of those packages and makes importing and analyzing data much easier. Pandas series.le() is used to compare every element of Caller series with passed serie 3 min read Like