You are already familiar with the functions that can output the dataset, but imagine you want to output only a specific column. Firstly, let's get acquainted with the dataset for this section. By the way, it is inconvenient to output the whole data set, so data analysts usually output a part of it to examine. In this course, we will usually output the first 5 rows.

> Note
>
> Some tables in the course, such as the one below, contain numerous columns. Therefore, you may need to scroll horizontally to see all the columns.

This table will help you understand how to output specific columns:

<div class="custom-table-wrapper">
    <table>
        <tbody>
        <tr>
            <th><strong>Function's Purpose</strong></th>
            <th><strong>Syntax</strong></th>
            <th><strong>Output</strong></th>
        </tr>
        <tr>
            <td>Extract one column by title</td>
            <td><code>data['Director']</code></td>
            <td>All values from column 'Director'</td>
        </tr>
        <tr>
            <td>Extract several columns by title</td>
            <td><code>data[['Title', 'Stars']]</code></td>
            <td>All values from column 'Title' and relevant values from the column 'Stars'</td>
        </tr>
        </tbody>
    </table>
</div>


We want to output 'Category' and 'IMDb-Rating' columns; choose the correct way to do so.

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. 

Function's Purpose	Syntax	Output
Extract one column by title	`data['Director']`	All values from column 'Director'
Extract several columns by title	`data[['Title', 'Stars']]`	All values from column 'Title' and relevant values from the column 'Stars'

Advanced Techniques in pandas

Output Columns by Title

We want to output 'Category' and 'IMDb-Rating' columns; choose the correct way to do so.

Title	Director	Stars	IMDb-Rating	Category	Duration	Censor-board-rating	ReleaseYear
Top Gun: Maverick	Joseph Kosinski	Tom Cruise, Jennifer Connelly, Miles Teller, Val Kilmer...	8.6	Action, Drama	130min	UA	2022
Everything Everywhere All at Once	Dan Kwan,	Michelle Yeoh, Stephanie Hsu, Ke Huy Quan, James Hong...	8.3	Action, Adventure, Comedy	139min	R	2022
The Batman	Matt Reeves	Robert Pattinson, Zoë Kravitz, Jeffrey Wright, Colin Farrell...	7.9	Action, Crime, Drama	176min	UA	2022
Jurassic Park	Steven Spielberg	Sam Neill, Laura Dern, Jeff Goldblum, Richard Attenborough...	8.2	Action, Adventure, Sci-Fi	127min	UA	1993
The Godfather	Francis Ford Coppola	Marlon Brando, Al Pacino, James Caan, Diane Keaton	9.2	Crime, Drama	175min	A	1972