The nlargest method is used to return the first n rows in descending order, with the largest values in columns. The columns that aren’t provided are also returned, but they’re not used for sorting.
Note: Refer to What is pandas in Python? to learn more about pandas.
DataFrame.nlargest(n, columns, keep='first')
This method takes the following parameters:
n: This is the number of rows to return.
columns: This is the column label to order by. This parameter can be a list specifying multiple columns.
keep: This parameter handles duplicate values. There are three possible values for this attribute that are as follows:
first: It picks the first occurrences of the duplicates. This is the default value for keep.last: It picks the last occurrences of the duplicates.all: It does not drop any duplicates, even if it involves choosing more than “n” items.Let’s look at an example below:
import pandas as pddf= pd.DataFrame({'Name':['Dom', 'Celeste', 'Abhi', 'Gaby', 'Rachel', 'Sam'],'Age': [20,25,30,18,25,20]})print("Dataframe---")print(df)print("\n")print("Top 2 people by seniority:")print(df.nlargest(2,'Age'))
pandas module.df.df.Age column using the nlargest method.The value of the keep argument of the nlargest method is by default first. Hence, though there are two records with Age as 25, the first occurring record, 1 Celeste 25, is considered.
Let’s look at another example:
import pandas as pddf= pd.DataFrame({'Name':['Dom', 'Celeste', 'Abhi', 'Gaby', 'Rachel', 'Sam'],'Age': [20,25,30,18,25,20]})print("Dataframe---")print(df)print("\n")print("Top 2 people by seniority:")print(df.nlargest(2,'Age', keep='last'))
pandas module.df.df.Age column using the nlargest method with the keep value as last.Here, the value of the keep argument of the nlargest method is last. Hence, though there were two records with Age as 25, the last occurring record, 4 Rachel 25, is considerered.