Summary  
Demonstrates using the nlargest() method to select the top N rows from a dataset by specified columns, with options to include all duplicate values.

General domain of usage  
Data analysis

In the last chapter, you learned how to output the smallest values; you can definitely do the same with the largest ones. To do so, you will use a very similar method with the same argument as the previous one: `.nlargest()`. Look at the example of how to output the 10 newest cars, also sorted by `'Engine_volume'` - all duplicates included:

```python
data.nlargest(10, ['Year', 'Engine_volume'], keep = 'all')
```

Choose the CORRECT way to get the top 100 the most expensive cars sorted, firstly by `'Price'` and then by `'Year'`, not including duplicates -  just the first 100 values.

This course contains a lot of useful functions for a future data analyst. You will learn different ways of extracting data and even set conditions on it. After it, you will be familiar with the methods of grouping data. Also, you will learn how to preprocess data. Each section has its data set so that the course will be gripping.

This section will teach you how to output specific columns by their titles or indices. Also, you will get acquainted with the ways you can select rows  by indices.

Here, you will learn how to extract data that has specific conditions. Also, you will learn how to combine them and even create your own.

In this section, you will expand your knowledge on setting different data conditions. You will learn to check if your data is in a defined list of values or between two values. You will also learn how to find the largest and smallest values.

This section is one of the most fascinating of the course. Here, you will learn how to group data in different ways. It will help you work as a data analyst to find out information on specific data groups.

This section is one of the most significant for a data analyst because if the data contains missing data values in the incorrect format, it will be impossible to work with. Thus, you will learn how to deal with such inappropriate values here. 

Finding the Largest Values of a Column