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nlargest()

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Let’s read the budget.xlsx workbook into a DataFrame:

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import pandas as pd\n\nbudget = pd.read_excel("budget.xlsx")\n\nbudget
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Output:

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Our DataFrame has duplicate rows. We will remove them using the drop_duplicates() method.

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budget.drop_duplicates(inplace=True)
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Let’s say we want to find out the top 3 stores with the highest July’19 budget.

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We can do so using the nlargest() method, which returns the first n rows ordered by columns in descending order.

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The first argument that we pass to the method is the no. of rows we want to extract. The second argument is the name of the column to order by.

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budget.nlargest(3, columns="July'19 Budget")
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Output:

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nsmallest()

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Returns the first n rows ordered by columns in ascending order.

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nsmallest() is the complementary method to nlargest().

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In the following code example, we find out the bottom 3 stores with the lowest July’19 budget.

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budget.nsmallest(3, columns="July'19 Budget")
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Output:

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\n","frontmatter":{"title":"Pandas nlargest() & nsmallest() Methods","date":"2021-08-10"}}},"pageContext":{"slug":"/pandas-nlargest-and-nsmallest-methods/","prev":{"fields":{"slug":"/find-values-within-a-range-in-a-pandas-series/"},"frontmatter":{"modules":null}},"next":{"fields":{"slug":"/pandas-set-index-and-reset-index-methods/"},"frontmatter":{"modules":null}}}}, "staticQueryHashes": ["3159585216"]}