docs/variable-explorer.md

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title: Variable explorer
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Deepnote provides an easy way to explore the current variables in a notebook. After you execute a cell that defines a variable, it appears in the **Variable explorer** in the left sidebar with information about its type and contents.

For all variable types, you can click on the variable to show the variable's contents from within the notebook itself:

<VideoLoop src="../assets/docs/ocP07hX7RmO2fzs5zyoQ.mp4" />

### Interactive DataFrame output

When displaying any **Pandas DataFrame**, Deepnote provides interactive controls that allow you explore your data without having to write any additional code:

- Add and combine filters and row sorting to examine subsets of your data
- Visualize ratios, distributions, and data types for each column (depending on the size of your DataFrame)
- Paginate through your DataFrame and download it as a CSV file by using the controls at the bottom
- Create a [no-code chart](/docs/chart-blocks) for the DataFrame by clicking the `visualize` button in the right-hand corner

<VideoLoop src="../assets/docs/nTbxtZv4R46eIJx61fUv.mp4" />