How-to · Table Formatter

How to Build a No-Code Data Pipeline to Join, VLOOKUP, and Filter CSV Files

Step-by-step tutorial: load sheets into Node Editor, wire Join, VLookup, and Filter nodes on the visual canvas, execute graphs with live Web Workers, and build output tables.

Open Table Formatter Add to VS Code
Free · runs in your browser · your files are never uploaded
How to Build a No-Code Data Pipeline to Join, VLOOKUP, and Filter CSV Files demonstration
Table Formatter — How to Build a No-Code Data Pipeline to Join, VLOOKUP, and Filter CSV Files

TLDR

Switch Table Formatter to Node Editor via the diagram icon in the left rail, click Load Sheet to bring your spreadsheet datasets onto the canvas, and use Add Node ▾ to connect Join, VLookup, Filter, or Formula nodes. Configure parameters in the sliding config panel on the right, click Run to execute the graph in a local Web Worker, and click Build Table to output your merged dataset into a fresh sheet.

Before you start

You need two or more tabular datasets to merge or cross-reference (such as Sales_Log.csv and Employee_Directory.csv) and a web browser.

Node Editor executes pipelines in client-side Web Workers, handling thousands of rows without spreadsheet freezes or cloud server dependencies.

Step 1 — Load source datasets into Sheet Manager

In Table Formatter:

  1. Click the Folder Icon (#loadFileBtn) in the left icon rail to load your first file (Sales_Transactions.csv). It opens as Sheet 1.
  2. Click + Add Sheet in the bottom Sheet Manager tab bar (#sheetTabBar).
  3. Click the Folder Icon again to load your second file (Employee_Directory.csv) into Sheet 2.
Step 1 — Load source datasets into Sheet Manager

Step 2 — Switch to Node Editor Mode

Click the Node Editor icon (#nodeEditorToggle with the project-diagram icon) in the left rail.

The center area transforms into an interactive graph canvas featuring a top action bar, a visual minimap in the bottom right (#neMinimapCanvas), and an offscreen canvas rendering pipeline.

Step 2 — Switch to Node Editor Mode

Step 3 — Load sheets as data source nodes

In the top Node Editor header bar:

  1. Click Load Sheet (#neAddFromSheet). A source node representing Sheet 1 appears on the canvas showing its detected column list and row count.
  2. Switch active sheet in the bottom tab bar to Sheet 2 and click Load Sheet again to create the second source node.
  3. Drag the nodes to position them on the left side of your canvas.

Step 4 — Add and wire operator nodes (Join / VLookup)

Click Add Node ▾ (#neAddNode) to open the palette flyout (#nePalette):

To wire connections: click the circular output port on Sheet 1 and drag a connector wire to the input port of the Join Node. Drag a second wire from Sheet 2 to the second input port.

Step 5 — Configure node parameters in the Config Panel

Click on the Join Node on the canvas:

Add a downstream Filter Node connected to the Join output, click it, and configure: Column: Region, Operator: Equals, Value: West.

Step 6 — Run the graph and build the output table

  1. In the top action bar, click Run (#neRunGraph). The topological engine executes nodes in sequence. Connected nodes glow green upon completion.
  2. Select the final node (or Join Node) and click Build Table (#neBuildTable).
  3. A brand-new sheet containing your joined and filtered dataset is generated in the Sheet Manager.
  4. Click Exit (#neExit) to switch to Table Mode and export your results as CSV, Markdown, or SQL.

Pro tip: graph minimap and fit view

Working with large pipelines containing six or more nodes?

Click Fit (#neFitView) in the header to zoom and center all nodes into view. You can also click and drag inside the interactive minimap in the bottom-right corner to pan across large execution graphs.

Next steps

Table Formatter — Clean, reshape, and convert tabular data between HTML, CSV, TSV, SQL, and Markdown.

Open Table Formatter Add to VS Code Source

More for Table Formatter

Use case
Visual Data Pipelines and Multi-Spreadsheet Merging for Data Operations
How operations leads and business analysts merge CRM logs, billing exports, and rosters without writing complex Excel VLOOKUP formulas or Python scripts.
Use case
Local CSV Data Validation and Anomaly Auditing for Data QA Engineers
How data QA leads and compliance auditors detect missing values, flag duplicate records, and clean CSV datasets locally using Lab Mode recipes.
Use case
Parsing Raw Delimited Text and Generating SQL Migrations for DBAs
How database administrators and ETL engineers convert unstructured pipe, tab, or comma-delimited text dumps into normalized tables and executable SQL INSERT scripts.
Use case
Interactive Financial Reporting and Matrix Transposing for Finance Leads
How finance directors, FP&A analysts, and executive report authors format multi-tab earnings reports, freeze headers, highlight KPI variances, and flip table axes.