Category: noteboook
Question: How to find notebooks on Kaggle?
Answer: In addition to being an interactive editing platform, you can find and use notebooks/codes that others in the community have shared public. Kagglers working with data across both the Datasets and Competitions platforms are constantly building cool things. Exploring and reading other Kagglers’ code is a great way to both learn new techniques and stay involved in the community.

There’s no better place than Kaggle Notebooks to discover such a huge repository of public, open-sourced, and reproducible code for data science and machine learning.

The latest and greatest from Notebooks is surfaced on Kaggle in several different places.

## Site Search

You can use the site search in the top bar of the website while on any page to look for not only Notebooks but Datasets, Competitions, Users, and more across Kaggle. Start typing a search query to get quick results and hit "Enter" to see a full page of results that you can drill down into. From the full page search results, you can filter just to "Notebooks" and add even more filter criteria using the filter options on the left-hand side of the page.

## Homepage

When you’re logged into your Kaggle account, the Kaggle homepage [Kaggle Homepage](https://kaggle.com/) provides a live newsfeed of what people are doing on the platform. While Discussion forum posts and new Datasets make up some of the contents of the homepage, most of it is dedicated to hot new Notebooks activity. By browsing down the page you can check out all the latest updates from your fellow Kagglers.

You can tweak your newsfeed to your liking by following other Kagglers. To follow someone, go to their profile page and click on “Follow User”. Content posted and upvotes made by users you have followed will show up more prominently.

The same is true of other users who choose to follow you. Post high-quality notebooks and datasets and you will soon find other users following along with what you are doing!

## Notebook Listing

A more structured way of accessing Notebooks is the Notebook listing [Notebook Listing](https://www.kaggle.com/notebooks), accessible from the “Notebooks” tab in the main menu bar.

The Notebook listing is sorted by [Hotness](https://www.kaggle.com/notebooks?sortBy=hotness&group=everyone&pageSize=20) by default. “Hotness” is what it sounds like: a way of measuring the interestingness of Notebooks on the platform. Notebooks which score highly in Hotness, and thus appear highly in this list, are usually either recently written Notebooks that are scoring highly in things like upvotes and views, or “all-time” greats that have been consistently popular on the platform for a long time.

Other methods of sorting are by

- [Most Votes](https://www.kaggle.com/code?sortBy=voteCount): Surfaces the most popular notebooks of all time
- [Most Comments](https://www.kaggle.com/code?sortBy=commentCount): Returns the most discussed notebooks of all time
- [Recently Created](https://www.kaggle.com/code?sortBy=dateCreated): A real-time stream of new Notebooks
- [Recently Run](https://www.kaggle.com/code?sortBy=dateRun): A real-time stream of activity
- [Relevance](https://www.kaggle.com/code?sortBy=relevance): Sorts the results based on their relevance to the query

Other filtering options, available from the navigation bar, are Categories (Datasets or Competitions?), Outputs, Languages (R or Python?), and Types (Script or Notebook?).

You can also use the Notebook listing to sort through your own Notebooks (“Your Work”), find Notebooks that others have shared with you ("Shared With You"), or to look at Notebooks you have previously upvoted (“Favorites”).

Finally, a Notebooks-specific search bar is available here. This is often the fastest way to find a specific Notebook that you are looking for.

## Datasets and Competitions

Data on Kaggle is available through either Datasets or our Competitions. Both prominently feature the best community-created Notebooks on the “Notebooks” tab. Browsing Notebooks on Datasets and Competitions provides a way to quickly get acquainted with a specific dataset. You can fork any existing public Notebook to make a copy of the code and start experimenting with changes.

The Iris Species dataset [Iris Species Dataset](https://www.kaggle.com/uciml/iris) and the Titanic competition [Titanic Competition](https://www.kaggle.com/c/titanic/notebooks) are two classic examples of Datasets and Competitions, respectively, hosting great Notebooks on their content.

## Tags and Tag Pages

Tags are the most advanced of the searching options available in the Notebook listing page. Tags are added by Notebook owners to indicate the topic of the Notebook, techniques you can use (e.g., “classification”), or the type of the data itself (e.g., “text data”). You can navigate to tag pages to browse more content sharing a tag either by clicking on a tag on a Notebook, or by searching by tag using the tag-specific search syntax: |tag:[TAG NAME]|.

Searching by tags allow you to search for Notebooks by topical area or technique. For example, if you are interested in learning new techniques for tackling classification problems you might try a search with the tag “classification” (|tag:classification|); if you are interested in an analysis of police records maybe a search with “crime” (|tag:crime|) would do the trick.

Alternatively, you can achieve the same thing by visiting the related tag pages. For example, the crime and classification tags live at [Crime Tag](https://www.kaggle.com/tags/crime) and [Classification Tag](https://www.kaggle.com/tags/classification), respectively.

Tag pages include a section listing the most popular pages with the given tag, making them a great way of searching for Notebooks by content.