Summary  
This chapter explains how to use a membership check method to filter rows in a dataset by selecting entries whose column values are contained in a provided list, and printing the filtered results.

General domain of usage  
Data analysis

In this section, we will continue extracting data using specific conditions. Here, you will become familiar with the helpful method called `.isin()`. But firstly, you need to examine the dataset. Look at the first five rows:

import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/cars.csv', index_col = 0)
print(data.head())

Now, take a look at the example and the explanation below:

import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/cars.csv', index_col = 0)
models = ['HONDA', 'FORD', 'MERCEDES-BENZ', 'HYUNDAI']
data_extracted = data.loc[data['Manufacturer'].isin(models)]
print(data_extracted.head())

**Explanation:**

If you remember, we always put the conditions inside the `.loc[]` attribute. Here, we do the same. The `.isin(list)` method checks if the values from the column are in the array. In our case, we check if values from the column `'Manufacturer'` are in the list `models`.

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. 

Is Data in ...?

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Is Data in ...?

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