Visidata — a powerful tool for working with tabular data directly in the terminal. If you often deal with large datasets or files in formats like CSV, TSV, XLS/XLSX, SQLite, or JSON (and more — the full list of supported formats is here), this tool might become your best friend. In this article, I’ll share 10 reasons why I consider VisiData indispensable.

Key Benefits of VisiData

  1. Support for Multiple Data Formats
    VisiData supports popular data formats like CSV, TSV, Excel (XLS/XLSX), SQLite, and even Apache Arrow. You can also quickly and efficiently convert data between formats using bash pipelines.

    Visidata default view

  2. Speed and Performance
    Even when working with large files, VisiData remains fast and responsive. It can open any file that fits into your system’s RAM. On a modern analyst’s computer with 32GB of RAM, you can open files up to 20–25GB. However, it’s more comfortable to work with files in the 5–10GB range. For anything larger, you might want to consider pandas, polars, or DuckDB.

  3. Terminal-Based Workflow
    If you’re accustomed to working in the terminal, prefer keeping your hands on the keyboard, and your mouse is gathering dust under your desk, this tool is for you. It’s incredibly convenient — all actions are performed using hotkeys, allowing you to focus on understanding the data rather than hunting for buttons in an interface. The downside? You’ll need to memorize the hotkeys, but they’re fairly easy to learn.

  4. Powerful Filtering and Sorting
    Sorting and filtering are done with a single keystroke. It’s much more intuitive than in other tools. Simply press [ to sort a column in ascending order or ] for descending. Filtering works with both regular expressions and Python expressions. For example, you can type year >= 2024 and popularity > 10 to quickly extract what you need — faster than writing the equivalent in pandas.

  5. Advanced Aggregation Tools
    VisiData also shines with its aggregation features. You can group data by any column just by pressing Shift+F. By default, it will display a count aggregation with percentages and a histogram, but you can add nearly any aggregation function you need. You can even create a pivot table with the Shift+W shortcut:


    Here, we’ve quickly calculated the number of singles released by each artist per year. For example, you can see Bruno Mars and Coldplay had notable comebacks after 10 and 6 years, respectively.

  6. Table Joins
    VisiData lets you open multiple CSV/TSV files and perform JOIN and UNION operations on them. If you’re working with xlsx or sqlite3 files, you can immediately access these features since these formats often contain multiple tables. This is an incredibly powerful tool.

  7. A Range of Additional Features for Data Manipulation
    VisiData allows you to work with various data types using Python-specific methods, like str.replace. If you’re dealing with nested structures, such as JSON, you can easily flatten them into the main table. Need to deduplicate your data? There’s a built-in function for that, too.

  8. Extendable via Python
    VisiData is a Python-based application and library. It leverages additional Python libraries to offer enhanced features. For instance, if you want to open Arrow files, you’ll need to install pyarrow. While there are many installation options on the official site, I recommend using pip install to easily manage extensions and versions.

  9. Cross-Platform Compatibility
    VisiData works on Linux, macOS, and Windows (via WSL), making it accessible to virtually everyone.

  10. Open Source with an Active Community
    VisiData is an open-source project under active development. The community continuously adds new features. You can also propose your own enhancements or write custom plugins if you feel something is missing.

Consultation

VisiData is one of my favorite tools for data analysis. While it’s not suited for every task, I always try to use it where possible. It speeds up the discovery of patterns in data and supports many types of ad-hoc analyses, which make up a significant part of an analyst’s work.

In future articles, I’ll dive deeper into specific use cases for VisiData in practice.