Data Methods API

These methods allow you to retrieve and manipulate the underlying dataset in your Tuva Data Tool.

getRawData

Retrieve the complete dataset as a 2D array.

getRawData(): any[][]

Returns

Type	Description
any[][]	Two-dimensional array where each inner array represents a row

Example

const data = tuvaDataTools.actions.getRawData();
console.log(data);
// [
//   [1, 'Alice', '12', '85'],
//   [2, 'Bob', '13', '90'],
//   [3, 'Charlie', '12', '88']
// ]

Try It Out

JavaScript Editor

// Setup data const columnIds = ['id', 'name', 'age', 'score']; const columnNames = ['Case', 'Name', 'Age', 'Score']; const rowData = [ [1, 'Alice', '12', '85'], [2, 'Bob', '13', '90'], [3, 'Charlie', '12', '88'], [4, 'David', '11', '92'], [5, 'Eve', '13', '87'] ]; const metaData = { fields: [ { id: 'id', name: 'Case' }, { id: 'name', name: 'Name' }, { id: 'age', name: 'Age', type: 'numeric' }, { id: 'score', name: 'Score', type: 'numeric' } ] }; // Render component const tuvaDataTools = ReactDOM.render( React.createElement(TuvaDataTools, { columnIds: columnIds, columnNames: columnNames, rowData: rowData, metaData: metaData }), root ); // Get and display raw data setTimeout(() => { if (tuvaDataTools && tuvaDataTools.actions) { const rawData = tuvaDataTools.actions.getRawData(); console.log('Raw Data:', JSON.stringify(rawData, null, 2)); console.log('Total rows:', rawData.length); console.log('First row:', rawData[0]); } }, 1000);

Result / Preview

---

getColumnIds

Get the unique identifiers for each column.

getColumnIds(): string[]

Returns

Type	Description
string[]	Array of column ID strings

Example

const columnIds = tuvaDataTools.actions.getColumnIds();
console.log(columnIds);
// ['id', 'name', 'age', 'score']

---

getColumnNames

Get the human-readable display names for each column.

getColumnNames(): string[]

Returns

Type	Description
string[]	Array of column name strings

Example

const columnNames = tuvaDataTools.actions.getColumnNames();
console.log(columnNames);
// ['Case', 'Name', 'Age', 'Score']

Try It Out

JavaScript Editor

// Setup data const columnIds = ['id', 'name', 'age', 'score']; const columnNames = ['Case', 'Name', 'Age', 'Score']; const rowData = [ [1, 'Alice', '12', '85'], [2, 'Bob', '13', '90'], [3, 'Charlie', '12', '88'] ]; const metaData = { fields: [ { id: 'id', name: 'Case' }, { id: 'name', name: 'Name' }, { id: 'age', name: 'Age', type: 'numeric' }, { id: 'score', name: 'Score', type: 'numeric' } ] }; // Render component const tuvaDataTools = ReactDOM.render( React.createElement(TuvaDataTools, { columnIds: columnIds, columnNames: columnNames, rowData: rowData, metaData: metaData }), root ); // Display column information setTimeout(() => { if (tuvaDataTools && tuvaDataTools.actions) { const ids = tuvaDataTools.actions.getColumnIds(); const names = tuvaDataTools.actions.getColumnNames(); console.log('Column IDs:', ids); console.log('Column Names:', names); // Create a mapping const mapping = ids.map((id, i) => ({ id, name: names[i] })); console.log('Column Mapping:', JSON.stringify(mapping, null, 2)); } }, 1000);

Result / Preview

---

appendRawData

Add new rows to the existing dataset.

appendRawData(rows: any[][]): void

Parameters

Name	Type	Description
rows	any[][]	Array of rows to append, each row matching the column structure

Example

// Each row supplies values for the non-Case columns in column order.
// Case numbers are auto-assigned by appendRawData — do not include them.

// Add a single row
tuvaDataTools.actions.appendRawData([
  ['David', '14', '95']
]);

// Add multiple rows
tuvaDataTools.actions.appendRawData([
  ['Eve',   '13', '87'],
  ['Frank', '12', '91'],
  ['Grace', '14', '89']
]);

WARNING

Ensure the new rows match the existing column structure. Mismatched columns may cause rendering issues.

Try It Out

JavaScript Editor

// Setup initial data const columnIds = ['id', 'name', 'age', 'score']; const columnNames = ['Case', 'Name', 'Age', 'Score']; const rowData = [ [1, 'Alice', '12', '85'], [2, 'Bob', '13', '90'], [3, 'Charlie', '12', '88'] ]; const metaData = { fields: [ { id: 'id', name: 'Case' }, { id: 'name', name: 'Name' }, { id: 'age', name: 'Age', type: 'numeric' }, { id: 'score', name: 'Score', type: 'numeric' } ] }; // Render component const tuvaDataTools = ReactDOM.render( React.createElement(TuvaDataTools, { columnIds: columnIds, columnNames: columnNames, rowData: rowData, metaData: metaData }), root ); // Add button to append data setTimeout(() => { const btn = document.createElement('button'); btn.textContent = 'Add New Row'; btn.onclick = () => { if (tuvaDataTools && tuvaDataTools.actions) { // Each row contains values for non-Case columns; the Case number is auto-assigned. const newRow = ['New Student', '12', String(Math.floor(Math.random() * 20) + 80)]; tuvaDataTools.actions.appendRawData([newRow]); console.log('Added row:', newRow); console.log('Total rows now (incl. header):', tuvaDataTools.actions.getRawData().length); } }; btn.style.cssText = 'margin: 10px 0; padding: 8px 16px;'; root.parentElement.insertBefore(btn, root); }, 1000);

Result / Preview

---

setRawData

Replace the entire row dataset in place, preserving the current column schema and plot state.

setRawData(rows: any[][]): void

Parameters

Name	Type	Description
rows	any[][]	Replacement rows. Each row should match the existing column count and omit the Case column — case numbers are reassigned automatically.

Example

// Replace all rows with a new set
tuvaDataTools.actions.setRawData([
  ['Alice',   '12', '85'],
  ['Bob',     '13', '90'],
  ['Charlie', '12', '88'],
]);

TIP

Use setRawData when the column schema (column IDs, names, metadata) is unchanged and you only need to swap the rows. If the schema also needs to change, re-mount the component with new props instead.

---

clearData

Remove all rows from the dataset, keeping the column schema and plot configuration intact.

clearData(): void

Example

// Wipe all rows
tuvaDataTools.actions.clearData();

// After clearData, you can stream rows in again with appendRawData
tuvaDataTools.actions.appendRawData([
  ['Alice', '12', '85'],
]);

---

getMetaData

Retrieve the metadata describing the dataset structure and field properties.

getMetaData(): MetaData

Returns

Type	Description
MetaData	Object containing field definitions and properties

MetaData Structure

interface MetaData {
  fields: Field[];
}

interface Field {
  id: string;        // Unique identifier
  name: string;      // Display name
  type?: string;     // Data type (numeric, categorical, etc.)
  unit?: string;     // Unit of measurement
  precision?: number; // Decimal precision for numeric fields
}

Example

const metaData = tuvaDataTools.actions.getMetaData();
console.log(metaData);
// {
//   fields: [
//     { id: 'id', name: 'Case' },
//     { id: 'name', name: 'Name' },
//     { id: 'age', name: 'Age', type: 'numeric' },
//     { id: 'score', name: 'Score', type: 'numeric' }
//   ]
// }

---

getDirtyRawData

Get the modified data that hasn't been persisted. Useful for tracking user edits.

getDirtyRawData(): any[][]

Returns

Type	Description
any[][]	Array of modified rows

Example

const unsavedChanges = tuvaDataTools.actions.getDirtyRawData();
if (unsavedChanges.length > 0) {
  console.log('There are unsaved changes:', unsavedChanges);
  // Prompt user to save or handle accordingly
}

---

Working with Data: Complete Examples

Exporting Data to CSV

function exportToCSV() {
  if (!tuvaDataTools || !tuvaDataTools.actions) return;
  
  const columnNames = tuvaDataTools.actions.getColumnNames();
  const data = tuvaDataTools.actions.getRawData();
  
  // Create CSV content
  let csv = columnNames.join(',') + '\n';
  data.forEach(row => {
    csv += row.map(cell => `"${cell}"`).join(',') + '\n';
  });
  
  // Download
  const blob = new Blob([csv], { type: 'text/csv' });
  const url = URL.createObjectURL(blob);
  const a = document.createElement('a');
  a.href = url;
  a.download = 'data-export.csv';
  a.click();
}

Real-time Data Updates

// Render component
const tuvaDataTools = ReactDOM.render(
  React.createElement(TuvaDataTools, {
    columnIds: columnIds,
    columnNames: columnNames,
    rowData: rowData,
    metaData: metaData
  }),
  document.getElementById('root')
);

// Poll for new data every 5 seconds
const interval = setInterval(async () => {
  const response = await fetch('/api/new-records');
  const newRows = await response.json();
  
  if (newRows.length > 0 && tuvaDataTools && tuvaDataTools.actions) {
    tuvaDataTools.actions.appendRawData(newRows);
  }
}, 5000);

// Clean up
// clearInterval(interval);

Data Validation Before Append

function validateAndAppend(newRows) {
  if (!tuvaDataTools || !tuvaDataTools.actions) return;
  
  const columnIds = tuvaDataTools.actions.getColumnIds();
  const expectedColumns = columnIds.length;
  
  const validRows = newRows.filter(row => {
    if (row.length !== expectedColumns) {
      console.warn('Row has incorrect number of columns:', row);
      return false;
    }
    return true;
  });
  
  if (validRows.length > 0) {
    tuvaDataTools.actions.appendRawData(validRows);
    console.log(`Added ${validRows.length} rows`);
  }
}

Comparing Original and Modified Data

function hasUnsavedChanges() {
  if (!tuvaDataTools || !tuvaDataTools.actions) return false;
  
  const original = tuvaDataTools.actions.getRawData();
  const dirty = tuvaDataTools.actions.getDirtyRawData();
  
  return dirty.length > 0;
}

function promptSaveBeforeLeave() {
  window.addEventListener('beforeunload', (e) => {
    if (hasUnsavedChanges()) {
      e.preventDefault();
      e.returnValue = 'You have unsaved changes. Are you sure you want to leave?';
    }
  });
}