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Feat: Fix broken DataFrame documentation link (#5035)
* Fix dead link: Update DataFrame getting started URL Replace broken dataframe/gettingstarted.html link with dataframe/quickstart.html * fix(docs): update DataFrame link (quickstart → home) * fix(docs): fix last commit typo
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docs/topics/data-analysis/data-analysis-connect-to-db.md

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[Kotlin Notebook](kotlin-notebook-overview.md) offers capabilities for connecting to and retrieving data from various types of SQL databases, such as
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MariaDB, PostgreSQL, MySQL, and SQLite.
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Utilizing the [Kotlin DataFrame library](https://kotlin.github.io/dataframe/gettingstarted.html), Kotlin Notebook can establish
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Utilizing the [Kotlin DataFrame library](https://kotlin.github.io/dataframe/home.html), Kotlin Notebook can establish
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connections to databases, execute SQL queries, and import the results for further operations.
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For a detailed example, see the [Notebook in the KotlinDataFrame SQL Examples GitHub repository](https://github.com/zaleslaw/KotlinDataFrame-SQL-Examples/blob/master/notebooks/imdb.ipynb).
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## Connect to database
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You can connect to and interact with an SQL database using specific functions from the [Kotlin DataFrame library](https://kotlin.github.io/dataframe/gettingstarted.html).
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You can connect to and interact with an SQL database using specific functions from the [Kotlin DataFrame library](https://kotlin.github.io/dataframe/home.html).
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You can use `DatabaseConfiguration` to establish a connection to your database and `getSchemaForAllSqlTables()` to retrieve
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the schema of all tables within it.
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## Analyze data in Kotlin Notebook
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After [establishing a connection to an SQL database](#connect-to-database), you can use Kotlin Notebook for in-depth data analysis
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utilizing the [Kotlin DataFrame library](https://kotlin.github.io/dataframe/gettingstarted.html). This includes functions for
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utilizing the [Kotlin DataFrame library](https://kotlin.github.io/dataframe/home.html). This includes functions for
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grouping, sorting, and aggregating data, helping you to uncover and understand patterns within your data.
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Let's dive into an example that involves analyzing actor data from a movie database, focusing on the most frequently

docs/topics/data-analysis/data-analysis-notebooks-output-formats.md

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With Kotlin Notebook, you can visualize structured data with data frames:
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1. Add the [Kotlin DataFrame](https://kotlin.github.io/dataframe/gettingstarted.html) library to your notebook:
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1. Add the [Kotlin DataFrame](https://kotlin.github.io/dataframe/home.html) library to your notebook:
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```none
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%use dataframe

docs/topics/data-analysis/data-analysis-visualization.md

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before diving into complex models.
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This tutorial demonstrates how to create different chart types in IntelliJ IDEA using [Kotlin Notebook](kotlin-notebook-overview.md) with
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the [Kandy](https://kotlin.github.io/kandy/welcome.html) and [Kotlin DataFrame](https://kotlin.github.io/dataframe/gettingstarted.html) libraries.
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the [Kandy](https://kotlin.github.io/kandy/welcome.html) and [Kotlin DataFrame](https://kotlin.github.io/dataframe/home.html) libraries.
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## Before you start
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docs/topics/data-analysis/data-analysis-work-with-api.md

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It simplifies data extraction and analysis tasks by offering an iterative environment where every step can be visualized
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for clarity. This makes it particularly useful when exploring APIs you are not familiar with.
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When used in conjunction with the [Kotlin DataFrame library](https://kotlin.github.io/dataframe/gettingstarted.html), Kotlin Notebook not only enables you to connect to and fetch
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When used in conjunction with the [Kotlin DataFrame library](https://kotlin.github.io/dataframe/home.html), Kotlin Notebook not only enables you to connect to and fetch
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JSON data from APIs but also assists in reshaping this data for comprehensive analysis and visualization.
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> For Kotlin Notebook examples, see [DataFrame examples on GitHub](https://github.com/Kotlin/dataframe/blob/master/examples/notebooks/youtube/Youtube.ipynb).
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## Clean and refine data
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Cleaning and refining data are crucial steps in preparing your dataset for analysis. The [Kotlin DataFrame library](https://kotlin.github.io/dataframe/gettingstarted.html)
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Cleaning and refining data are crucial steps in preparing your dataset for analysis. The [Kotlin DataFrame library](https://kotlin.github.io/dataframe/home.html)
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offers powerful functionalities for these tasks. Methods like [`move`](https://kotlin.github.io/dataframe/move.html),
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[`concat`](https://kotlin.github.io/dataframe/concatdf.html), [`select`](https://kotlin.github.io/dataframe/select.html),
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[`parse`](https://kotlin.github.io/dataframe/parse.html), and [`join`](https://kotlin.github.io/dataframe/join.html)
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## Analyze data in Kotlin Notebook
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After you've successfully [fetched](#fetch-data-from-an-api) and [cleaned and refined your data](#clean-and-refine-data)
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using functions from the [Kotlin DataFrame library](https://kotlin.github.io/dataframe/gettingstarted.html), the next step
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using functions from the [Kotlin DataFrame library](https://kotlin.github.io/dataframe/home.html), the next step
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is to analyze this prepared dataset to extract meaningful insights.
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Methods such as [`groupBy`](https://kotlin.github.io/dataframe/groupby.html) for categorizing data,
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![Analysis results](kotlin-analysis.png){width=700}
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For more advanced techniques, see the [Kotlin DataFrame documentation](https://kotlin.github.io/dataframe/gettingstarted.html).
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For more advanced techniques, see the [Kotlin DataFrame documentation](https://kotlin.github.io/dataframe/home.html).
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## What's next
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docs/topics/data-analysis/data-analysis-work-with-data-sources.md

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[//]: # (title: Retrieve data from files)
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[Kotlin Notebook](kotlin-notebook-overview.md), coupled with the [Kotlin DataFrame library](https://kotlin.github.io/dataframe/gettingstarted.html), enables
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[Kotlin Notebook](kotlin-notebook-overview.md), coupled with the [Kotlin DataFrame library](https://kotlin.github.io/dataframe/home.html), enables
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you to work with both non-structured and structured data. This combination offers the flexibility to transform non-structured data,
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such as data found in TXT files, into structured datasets.
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docs/topics/data-analysis/kotlin-notebook-add-dependencies.md

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## Add Kotlin DataFrame and Kandy libraries to your Kotlin Notebook
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Let's add two popular Kotlin library dependencies to your Kotlin Notebook:
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* The [Kotlin DataFrame library](https://kotlin.github.io/dataframe/gettingstarted.html) gives you the power to manipulate data in your Kotlin projects.
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* The [Kotlin DataFrame library](https://kotlin.github.io/dataframe/home.html) gives you the power to manipulate data in your Kotlin projects.
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You can use it to retrieve data from [APIs](data-analysis-work-with-api.md), [SQL databases](data-analysis-connect-to-db.md), and [various file formats](data-analysis-work-with-data-sources.md), such as CSV or JSON.
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* The [Kandy library](https://kotlin.github.io/kandy/welcome.html) provides a powerful and flexible DSL for [creating charts](data-analysis-visualization.md).
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docs/topics/data-analysis/lets-plot.md

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![Lets-Plot](lets-plot-overview.png){width=700}
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This tutorial demonstrates how to create different plot types with
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the LPK and [Kotlin DataFrame](https://kotlin.github.io/dataframe/gettingstarted.html) libraries using Kotlin Notebook in IntelliJ IDEA.
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the LPK and [Kotlin DataFrame](https://kotlin.github.io/dataframe/home.html) libraries using Kotlin Notebook in IntelliJ IDEA.
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## Before you start
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