# Code Studio

Code Studio allows you to unlock Data Science and Machine Learning (DSML) capabilities in Analytics Plus. You can build ML models and data transformations using Python code environment in Analytics Plus to make predictions and gain actionable insights.

The Data Scientists/Data Engineers commonly combine data from multiple sources, prepare/transform them for analysis, and create ML models to achieve advanced analytics features. For instance, IT administrators might combine request data across multiple sites or business units to get a consolidated view for reporting, or an analyst might build a model to forecast ticket volume trends based on historical request patterns.

The inbuilt advanced features in Analytics Plus use time and statistical historical data as factors to achieve predictive analysis, forecasting, clustering, and more. However, many modern scenarios involve multiple factors other than time and historical data, which could affect the accuracy of predictive insights gained from these traditional tools.

Code Studio comes in handy in these scenarios to transform data and build ML models designed to involve multiple factors. It serves two primary functions:

- **Data transformation** - Used to transform, filter, enrich, and reshape data for analysis.
- **ML Model** - Build ML models for classification, regression, forecasting, causal, time series, and custom ML.

Only the **Account Admin**, **Organization Admin**, and **Workspace Admin** can access Code Studio.

Code Studio uses **Python 3.9** and is available only in the **Enterprise** edition.

## Accessing Code Studio

Code Studio can be accessed in two ways:

1. **Code Studio icon** - Click the Code Studio icon on the left-side pane.
2. **Create icon** - Click the Create icon at the top of the left-side pane and select **Code / ML Model** from the menu that appears.

![Code Studio](https://cdn.manageengine.com/sites/meweb/images/analytics-plus/cloud-help/codestudio-ezgif.com-crop_1.gif)

The Code Studio editor page will open with the sample code and the following features:

1. **Code Editor:** The central section of the Code Studio Editor is a dedicated Python environment for writing, editing, and executing code to transform data and build ML models.
2. **Library:** Located on the left side of the Code Editor, this section includes default libraries. You can click the **+ Add** icon at the top to create a new file, upload a file, or add a library. Library acts as a file directory for all folders and their files.
3. **Insert Table/Column:** The right-side pane lists all tables and their respective columns. You can easily insert them into your code by clicking the desired table or column.

![Upload file](https://cdn.manageengine.com/sites/meweb/images/analytics-plus/cloud-help/uploadfile.png)

4. **Insert Code:** Available in the right-side pane, this feature provides a list of predefined Python functions that can be inserted directly into your code with a click.

![Insert code](https://cdn.manageengine.com/sites/meweb/images/analytics-plus/cloud-help/insertcode.png)

5. **Zia Code Suggester:** An AI-powered platform that offers code suggestions based on your query, which can be directly added to your code editor.

![Zia Code Suggester](https://cdn.manageengine.com/sites/meweb/images/analytics-plus/cloud-help/ziacodesuggester.png)

6. **Keyboard Shortcuts:** A list of basic keyboard shortcuts available for use in the Code Studio Editor.

![Keyboard shortcuts](https://cdn.manageengine.com/sites/meweb/images/analytics-plus/cloud-help/keyboardshortcuts-ezgif.com-crop_1.gif)

7. **Console:** A text-based interface used for debugging and troubleshooting, the console displays logs and errors of the Test Run.
8. **Output:** Displays a preview table with a sample response for the executed script over the sample data (first 100 rows).