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The Create Chart node creates interactive charts and visualizations in Google Sheets workbooks. Perfect for automated reporting, data visualization, and dashboard creation. This is an AI-powered node that can understand natural language instructions.

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When to Use It

  • Automate chart creation for reports and dashboards
  • Visualize data trends and patterns
  • Create interactive business intelligence charts
  • Generate charts from dynamic data ranges
  • Build automated visualization workflows
  • Create professional presentations with data charts

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Inputs

FieldTypeRequiredDescription
SpreadsheetTextYesGoogle Sheets spreadsheet URL or ID
Sheet NameTextYesName of the sheet to create the chart in
Data RangeTextYesCell range containing the data to chart
Chart TypeDropdownYesType of chart to create
Chart TitleTextNoTitle to display on the chart
Alt TextTextNoAlternative text for accessibility and identification

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Spreadsheet Input Options

URL Format: 
https://docs.google.com/spreadsheets/d/1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms/edit
Spreadsheet ID Format: 
1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms

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Data Range Format

A1 Notation Examples: 
A1:C10        # Simple range
Sales!A1:D50  # Specific sheet and range
A:C           # Entire columns A through C
1:5           # Entire rows 1 through 5

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Chart Type Options

TypeBest ForDescription
COLUMNComparisonsVertical bar charts for comparing categories
LINETrendsLine charts showing data over time
AREACumulativeArea charts showing volume and trends
BARRankingsHorizontal bar charts for rankings
PIEProportionsPie charts showing parts of a whole

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Output

Returns information about the created chart: 
{
  "chart_id": 1234567890,
  "chart_title": "Monthly Sales Performance",
  "chart_type": "COLUMN",
  "spreadsheet_id": "1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms",
  "sheet_name": "Dashboard",
  "data_range": "A1:C12",
  "alt_text": "sales_chart_q4",
  "position": {
    "row": 15,
    "column": 5,
    "width": 600,
    "height": 400
  },
  "chart_url": "https://docs.google.com/spreadsheets/d/1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms/edit#gid=0&range=A15:I32"
}

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Output Fields:

FieldDescription
chart_idUnique identifier for the created chart
chart_titleTitle displayed on the chart
chart_typeType of chart created
spreadsheet_idGoogle Sheets spreadsheet ID
sheet_nameSheet where chart was created
data_rangeCell range used for chart data
alt_textAlternative text for identification
positionChart position and dimensions
chart_urlDirect link to view the chart

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Credit Cost

  • Cost per run: 2 credits

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Common Workflows

Automated Dashboard Creation: 
[Read Sheet Data] → [Process/Clean Data] → [Create Chart] → [Position Charts] → [Share Dashboard]
Reporting Automation: 
[Get Latest Data] → [Calculate Metrics] → [Create Multiple Charts] → [Generate Report]
Trend Analysis: 
[Historical Data] → [Time Series Processing] → [Create Line Charts] → [Add Trend Lines]
Comparative Analysis: 
[Multi-Source Data] → [Normalize Data] → [Create Column Charts] → [Add Comparisons]

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Chart Type Guide

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Column Charts (COLUMN)

Best for: Comparing categories, showing discrete data points 
Use Case: Monthly sales by product
Data Structure: Categories in column A, values in column B
Example Range: A1:B12 (months and sales figures)

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Line Charts (LINE)

Best for: Showing trends over time, continuous data 
Use Case: Website traffic over time
Data Structure: Time periods in column A, metrics in column B
Example Range: A1:B365 (daily traffic data)

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Area Charts (AREA)

Best for: Showing volume and cumulative trends 
Use Case: Revenue growth by quarter
Data Structure: Time periods in column A, cumulative values in column B
Example Range: A1:B16 (quarterly cumulative revenue)

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Bar Charts (BAR)

Best for: Rankings, horizontal comparisons 
Use Case: Top 10 products by sales
Data Structure: Items in column A, values in column B
Example Range: A1:B10 (product names and sales)

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Pie Charts (PIE)

Best for: Showing parts of a whole, percentages 
Use Case: Market share by competitor
Data Structure: Categories in column A, percentages in column B
Example Range: A1:B6 (companies and market share)

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Data Preparation Tips

Structure Your Data: 
Row 1: Headers (Category, Value)
Row 2+: Data points
Clean Data: No empty cells in range
Consistent Types: Numbers as numbers, not text
Example Data Layout: 
     A          B
1   Month     Sales
2   Jan       15000
3   Feb       18000
4   Mar       22000
5   Apr       19000
Range Selection:
  • Include headers for automatic labeling
  • Ensure data continuity (no gaps)
  • Use absolute ranges for consistent results
  • Consider data growth when selecting ranges

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Use Cases

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Sales Dashboard

Create monthly performance charts: 
- Data: Monthly sales figures
- Chart Type: COLUMN
- Title: "Monthly Sales Performance"
- Alt Text: "monthly_sales_chart"

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Trend Analysis

Track metrics over time: 
- Data: Daily/weekly metrics
- Chart Type: LINE
- Title: "Growth Trend Analysis"
- Alt Text: "trend_chart"

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Portfolio Breakdown

Show investment allocation: 
- Data: Asset categories and percentages
- Chart Type: PIE
- Title: "Portfolio Allocation"
- Alt Text: "portfolio_pie_chart"

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Performance Comparison

Compare team performance: 
- Data: Team names and scores
- Chart Type: BAR
- Title: "Team Performance Rankings"
- Alt Text: "team_comparison"

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Tips

Data Quality:
  • Clean your data before creating charts
  • Use consistent formatting for dates and numbers
  • Remove empty rows/columns from data range
  • Sort data appropriately for the chart type
Chart Design:
  • Choose meaningful titles that explain the chart
  • Use alt text for chart identification in workflows
  • Consider your audience when selecting chart types
  • Keep data ranges focused for clear visualizations
Workflow Integration:
  • Create charts after data processing for best results
  • Use chart_id to reference charts in subsequent operations
  • Position charts strategically for dashboard layouts
  • Test with sample data before automating large datasets
Performance:
  • Limit data range size for faster chart creation
  • Consider chart complexity vs. performance needs
  • Use appropriate chart types for your data volume
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