Convert Columns to Text

Column flattening converts multi-column text layouts (like ls output, PDFs, or terminal displays) into a single vertical list. You need this when you copy-paste data from formatted sources and want to extract individual items. For example, converting 'Apple Banana Cherry' (3 columns) into 'Apple\nBanana\nCherry' (3 lines). Common use cases include processing ls output, database exports, copied spreadsheet data, and extracted PDF tables.

The tool uses intelligent delimiter detection. For space-separated columns, it looks for gaps of multiple spaces (default: 2+ spaces) to distinguish between column separators and spaces within content (like 'New York'). You can choose from 4 delimiter types: Spaces (configurable gap), Tabs, Commas, or Pipes (|). The minimum gap setting only applies to space-separated columns—single spaces within content are preserved, while 2+ consecutive spaces trigger column splitting.

Yes! Click the Upload button to load .txt, .csv, or .tsv files directly. The tool will automatically process the file content. After flattening, you can download the result as a .txt file using the Save button. This is perfect for processing large datasets or automating workflows without manual copy-paste.

Batch Mode processes multiple column sets separated by blank lines independently. Enable it when your input contains multiple separate tables or lists. For example, if you have two separate ls outputs or multiple data blocks in one file, batch mode will flatten each block separately and preserve the separation in the output. Without batch mode, all content is treated as one continuous dataset.

The tool supports 4 delimiter types: (1) Spaces: Multi-space gaps (configurable threshold 2-10 spaces), perfect for ls output and terminal displays. (2) Tabs: Tab-separated values (TSV files). (3) Commas: CSV format or comma-delimited data. (4) Pipes: Pipe-separated values (|), common in databases and Markdown tables. Choose the delimiter that matches your source data format.

Names with single spaces like 'New York' are automatically preserved when using space delimiter because the tool only splits on multiple consecutive spaces (default: 2+). If 'New York' is splitting incorrectly, increase the Minimum Gap setting to 3 or 4 spaces. Alternatively, if your source data uses tabs, commas, or pipes, select the appropriate delimiter instead of spaces to avoid ambiguity.

Comparison Mode displays your original input and flattened output side-by-side, making it easy to verify the conversion. Toggle it on to see both versions simultaneously—original columns on top (blue theme) and flattened list below (green theme). This is useful for checking that names with spaces weren't split incorrectly or that the right delimiter was chosen.

Yes! The Case dropdown offers 4 options: (1) As-Is: Keep original case, (2) lowercase: Convert everything to lowercase, (3) UPPERCASE: Convert everything to uppercase, (4) Title Case: Capitalize the first letter of each word. This is useful for standardizing data before importing into databases or Excel.

The statistics section displays: (1) Input Chars: Total characters in your input text, (2) Items: Number of items extracted into the flattened list, (3) Columns: Number of columns detected (based on first line), (4) Lines: Number of lines or blocks processed (depends on batch mode). These metrics help verify the conversion worked correctly—if Items is too low, you may need to adjust the delimiter or gap setting.

Absolutely! All processing happens entirely in your browser using JavaScript—no data is sent to any server. Your text never leaves your computer. Files you upload are read locally, and downloads are generated client-side. We don't store, log, or have access to any of your data. This makes it safe for confidential information like employee lists, database exports, or sensitive documents.