I am looking for a solution to find the row number of the nth largest value in a Pandas DataFrame. I need help from the community to find alternative ways to solve this problem efficiently. Suppose I have a DataFrame with two columns and I want to find the row number of the nth largest value in a specific column. One approach could be to sort the DataFrame by that column and then use the `iloc`

function to retrieve the nth largest value and its corresponding row number. However, this can be computationally expensive for large datasets. I would like to explore alternative solutions that are more efficient and scalable. I welcome any suggestions or code snippets that can help me accomplish this task in a more efficient manner.

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Hello @nimrah , I have a solution to your query. You can use the `nlargest()`

and `index()`

methods of Pandas. The `nlargest()`

method returns the n-largest values from a column in descending order and the `index()`

method is to get the index labels of those values. Let me show you below how can we utilize them: