VantaViz Documentation

Everything you need to create beautiful, privacy-first data visualizations — starting with the 6 free chart types.

Quick Start

1

Sign Up

Create a free account at app.vantaviz.com. No credit card required.

2

Upload Data

Drag and drop a CSV, Excel (.xlsx), or JSON file. Data is processed locally in your browser.

3

Preview & Clean

Review detected columns, check data types, search rows, and filter out nulls before charting.

4

Choose a Chart

Pick one of the 6 free chart types from Free Essentials, then map your data columns.

5

Style & Export

Apply a theme, adjust labels and grid, then export as PNG (free plan includes watermark).

6

Save Project

Your chart is auto-saved as a project. Reopen anytime from the dashboard to continue editing.

Start for Free Compare Plans

Recommended Workflow

Follow this workflow to go from raw data to a polished chart in under 5 minutes:

  1. Prepare your data. Keep one row = one record. Group or aggregate in Excel or a spreadsheet tool before uploading. VantaViz does not currently support pivot transformations inside the app.
  2. Upload the file. Drag your .csv, .xlsx, or .json onto the drop zone. You can also use the Try with sample data buttons (Sales, Population, Temperature) to explore without your own data.
  3. Review columns in Preview. Check the detected data type for each column (text, number, date). Use the row search and Hide Nulls toggle to spot data quality issues quickly.
  4. Select a chart type. Open Free Essentials in the Chart Type panel and pick the chart that matches your goal (see the guide below).
  5. Map your data. Drag or select column names into the X Axis, Y Axis, and optional Group/Color fields. The preview updates in real time.
  6. Style and label. Choose a theme (Cyan, Warm, Mono, Colorful), toggle grid lines and value labels, adjust font size and bar corner radius.
  7. Export. Click Export to download as PNG. Upgrade to Personal or Business for watermark-free PDF, SVG, and PPT exports.

Data Requirements

Supported File Formats

VantaViz accepts CSV, Excel (.xlsx / .xls), and JSON files. All parsing runs inside your browser — your file is never uploaded to a server.

  • CSV: UTF-8 or UTF-16 encoding, comma or semicolon delimiter. The first row should be column headers.
  • Excel: First sheet is read by default. Keep one header row at the top of the sheet.
  • JSON: Must be an array of objects — e.g., [{"month":"Jan","sales":120}, ...].

Column Types

VantaViz auto-detects column types on import. You can override types if needed in the Preview step.

Type Examples Used For
Text / Category "Q1", "Germany", "Product A" X axis labels, group/color dimension
Number 1250.5, -3.14, 0 Y axis values, X axis in scatter/histogram
Date / Time "2024-01-15", "Jan 2024" X axis for time-series line and area charts

Free Essentials — 6 Chart Types

Every VantaViz account (including Free) has full access to the following 6 chart types. No time limit, no row cap on rendering.

Chart Best For Minimum Columns
Bar Comparing values across discrete categories 1 category + 1 number
Line Showing trends and changes over time 1 date/category + 1 number
Area Emphasizing volume/magnitude over time 1 date/category + 1 number
Pie Showing part-to-whole proportions 1 category + 1 number
Scatter Revealing correlations between two numeric variables 2 numbers (X & Y)
Histogram Visualizing frequency distributions of a single variable 1 number (auto-binned)

Bar Chart

Compare values across categories using bar length
Free

A bar chart uses the length of rectangular bars to represent the magnitude of values across distinct categories. It is the most versatile chart for categorical comparison and works equally well in vertical (column) and horizontal orientations.

Best For
Ranking, comparing, and contrasting categories
X Axis (required)
Category column (text)
Y Axis (required)
Numeric value column
Color/Group (optional)
Second category for grouped bars

How to Create a Bar Chart

  1. Upload your file and click Next: Create Chart.
  2. In Chart Type, open Free Essentials and click Bar.
  3. Under Data Mapping, set X Axis to your category column (e.g., Region, Product, Month).
  4. Set Y Axis to your numeric column (e.g., Revenue, Count, Score). You can add multiple Y columns to overlay series.
  5. Optionally set Color/Group to split bars by a second category (e.g., Quarter).
  6. Under Style, choose Bar direction: Vertical (default, column chart) or Horizontal (good for long labels).
  7. Adjust X Axis Labels rotation (0°, 45°, 90°) if labels overlap.
Tips
  • Use Horizontal orientation when category names are long to avoid overlapping labels.
  • Sort your data by value before uploading so the chart automatically shows a ranked order (highest to lowest).
  • Keep bar charts to 12 or fewer categories — too many bars make comparison difficult.
  • Turn on Show labels in Style to display exact values on each bar.
  • Corner Radius (Advanced Style) adds a modern, rounded look to your bars.

Example Use Cases

  • Monthly sales revenue by product category
  • Survey response distribution across options
  • Country-by-country GDP comparison
  • Task completion count per team member

Line Chart

Track trends and changes over a continuous dimension
Free

A line chart connects data points with a continuous line, making it ideal for showing how a value evolves over time or along an ordered sequence. Dots at each point help readers identify precise values.

Best For
Trends, time-series, sequential data
X Axis (required)
Date, time, or ordered category column
Y Axis (required)
Numeric value column(s)
Color/Group (optional)
Category for multiple lines

How to Create a Line Chart

  1. Upload a file where one column is a date, month, quarter, or sequential number.
  2. Select Line from Free Essentials.
  3. Set X Axis to your time or sequence column (e.g., Date, Week, Year).
  4. Set Y Axis to one or more numeric columns. Each additional Y column appears as a separate line.
  5. Optionally set Color/Group to split one Y column into multiple lines by category.
  6. Use X Axis Labels → Show every to thin out dense date labels (e.g., "Every 4th" for daily data over months).
  7. Adjust Stroke Width in Advanced Style for thicker or thinner lines.
Tips
  • Sort your data by date/time before uploading to ensure the line connects points in the correct order.
  • For dense data (hundreds of points), use Show every N-th label to prevent label collisions on the X axis.
  • Limit to 4–5 lines on a single chart — more lines reduce legibility; use a Group/Color field only if categories are clearly distinguishable.
  • Enable Show grid to help readers trace values horizontally across the chart.

Example Use Cases

  • Monthly website traffic over 12 months
  • Stock price or KPI trend over time
  • Temperature readings throughout the day
  • Multiple product lines' sales compared over quarters

Area Chart

Highlight volume and cumulative magnitude over a sequence
Free

An area chart is a line chart with the region below the line filled with a semi-transparent color. The fill draws attention to the total volume or magnitude of the metric, not just the trend direction. It is particularly effective when you want to convey "how much" in addition to "how it changed."

Best For
Volume over time, cumulative totals
X Axis (required)
Date, time, or ordered category
Y Axis (required)
Numeric value (should be non-negative)
Color/Group (optional)
Category for overlapping areas

How to Create an Area Chart

  1. Upload data with a sequential or date-based X column and at least one numeric Y column.
  2. Select Area from Free Essentials.
  3. Map X Axis to your time or category column.
  4. Map Y Axis to your numeric column. Multiple Y columns render as overlapping filled areas.
  5. Adjust Opacity in Advanced Style — lower opacity (e.g., 50–65%) prevents overlapping areas from obscuring each other.
  6. Toggle Show labels off for area charts with many data points to avoid visual clutter.
Tips
  • Area charts work best when your values are always positive (zero-based). If data crosses zero, consider a Line chart instead.
  • When overlapping multiple areas, reduce opacity (40–60%) so all areas remain visible.
  • Use area charts to show "filled-under" quantities: page views, revenue, energy consumption — where total size matters.
  • For comparing multiple groups with no overlap concern, upgrade to the Stacked Area chart (Personal plan).

Example Use Cases

  • Total monthly revenue over a fiscal year
  • Daily active users trend
  • Cumulative rainfall by month
  • Energy usage over 24 hours

Pie Chart

Show proportional share of each category in a whole
Free

A pie chart divides a circle into slices, where the arc length of each slice represents that category's share of the total. It answers the question "What fraction of the whole does each part represent?" most intuitively when there are only a few distinct categories.

Best For
Part-to-whole relationships, market share, composition
Category (required)
Text column — each unique value = one slice
Value (required)
Numeric column — determines slice size
Ideal # of Slices
2–7 categories

How to Create a Pie Chart

  1. Prepare a summary table: one row per category, one column for the category name, one column for the value (e.g., count or total).
  2. Select Pie from Free Essentials.
  3. Under Data Mapping, set Category to your label column (e.g., Channel, Product).
  4. Set Value to your numeric column (e.g., Revenue, Users).
  5. Enable Show labels in Style to show percentage and/or values on each slice.
  6. Toggle Show legend to display the color-to-category key beside the chart.
Tips
  • Use pie charts only when all values are positive and sum to a meaningful whole (100%).
  • Limit to 6 categories or fewer. Group small slices into an "Other" bucket before uploading if you have many categories.
  • Avoid pie charts for comparing near-equal slices — human eyes struggle to judge slice angles accurately. Use a Bar chart instead.
  • For a more modern look with a center metric, upgrade to the Donut chart (Personal plan).

Example Use Cases

  • Marketing channel contribution to total leads
  • Budget allocation by department
  • Operating system market share
  • Survey: "Which feature do you use most?"

Scatter Plot

Reveal correlations and distributions between two numeric variables
Free

A scatter plot positions each data point as a dot using two numeric values — one on the X axis and one on the Y axis. The resulting pattern of dots reveals whether two variables are positively correlated, negatively correlated, or unrelated. It is the go-to chart for exploratory data analysis.

Best For
Correlation, clustering, outlier detection
X Axis (required)
Numeric column (independent variable)
Y Axis (required)
Numeric column (dependent variable)
Color/Group (optional)
Category column to color-code points

How to Create a Scatter Plot

  1. Your dataset needs at least two numeric columns — one will be the X axis and one the Y axis. Each row is one dot.
  2. Select Scatter from Free Essentials.
  3. Set X Axis to the first numeric column (e.g., Ad Spend, Height, Temperature).
  4. Set Y Axis to the second numeric column (e.g., Sales, Weight, Energy Use).
  5. Optionally set Color/Group to a category column (e.g., Region, Species) to color-code the points and reveal group-level patterns.
  6. Adjust Opacity in Advanced Style — lower opacity helps visualize overlapping dense clusters.
Tips
  • Scatter plots require at least 20–30 data points to be meaningful; with very few points, a table or bar chart is clearer.
  • Use the Color/Group field to test whether different groups follow the same or different correlations.
  • Outliers stand out naturally in scatter plots — hover over dots (in the app) to see the underlying row values.
  • To add a third numeric dimension (dot size), upgrade to the Bubble chart (Personal plan).

Example Use Cases

  • Marketing spend vs. conversion rate across campaigns
  • Height vs. weight for a population dataset
  • Study hours vs. exam score by student
  • House price vs. square footage by neighborhood

Histogram

Visualize the frequency distribution of a single numeric variable
Free

A histogram groups continuous numeric data into contiguous intervals called "bins" and displays the count of values that fall in each bin as a bar. Unlike a bar chart, there is no gap between bars because the data is continuous. It is the standard tool for understanding the shape, spread, and central tendency of a distribution.

Best For
Distribution shape, skewness, outliers
Value (required)
One numeric column (auto-binned)
Color/Group (optional)
Category for overlaid distributions
Axis Note
X = value range, Y = frequency count

How to Create a Histogram

  1. Your dataset needs a single numeric column with many individual observations (ideally 30+ rows for a meaningful distribution).
  2. Select Histogram from Free Essentials.
  3. Under Data Mapping, set Value to the numeric column you want to analyze (e.g., Age, Price, Response Time).
  4. VantaViz automatically calculates bin ranges and counts. The X axis shows the value range; the Y axis shows the frequency (count of rows in each bin).
  5. Optionally set Color/Group to overlay distributions from different categories on the same chart.
  6. Adjust Opacity in Advanced Style if overlapping distributions are hard to distinguish.
Tips
  • More data points = more reliable histogram. Aim for at least 30 rows; 100+ rows reveal the shape most clearly.
  • Look for bell curves (normal distribution), right/left skew, or bimodal patterns — these are key insights from the histogram shape.
  • A histogram is NOT the same as a bar chart: the X axis represents a continuous numeric range, not discrete categories.
  • For a smoother continuous distribution curve, upgrade to the Density chart (Personal plan).

Example Use Cases

  • Age distribution of survey respondents
  • Order value distribution for an e-commerce store
  • API response time distribution
  • Student exam score distribution in a class

Themes & Style Options

Color Themes

All free charts support 4 built-in color themes:

◆ Cyan (Default)
Teal-to-cyan gradient. Clean and professional — ideal for business reports.
◆ Warm
Amber to red. Conveys energy and urgency; good for marketing and sales charts.
◆ Mono
Gray scale. Print-friendly and accessibility-conscious for black-and-white documents.
◆ Colorful
Purple to pink. Vibrant and expressive — great for presentations and dashboards.

Paid accounts can customize color themes.

Style Controls

  • Show grid: Toggle horizontal reference lines on the chart canvas.
  • Show labels: Display numeric values directly on bars, line points, or pie slices.
  • Show legend: Show or hide the color-to-series key beside the chart.
  • X Axis Label Rotation: Rotate labels 0° (horizontal), 45° (diagonal), or 90° (vertical) to prevent overlap.
  • X Axis Show Every N-th: Reduce label density for charts with many X categories.
  • Label Size (Advanced): Font size for axis labels and data labels, from 8 px to 18 px.
  • Stroke Width (Advanced): Line thickness for line and area charts (1–6).
  • Opacity (Advanced): Transparency of bars and filled areas (20–100%).
  • Corner Radius (Advanced): Rounded corners on bar chart bars (0–12 px).

Export Options

Format Free Plan Personal Business
PNG ✓ With watermark ✓ No watermark ✓ No watermark
SVG — ✓ ✓
PDF ✓ With watermark ✓ ✓
PPT (PowerPoint) ✓ With watermark ✓ ✓
.vviz Project File ✓ ✓ ✓

The .vviz project file saves your entire chart configuration (data, mappings, style). Re-import it later using the Import .vviz button in the app to continue editing.

See Plan Details

Best Practices for Better Charts

Choose the Right Chart for Your Data

  • Comparing categories? Use a Bar chart. Horizontal bars work best when labels are long.
  • Showing a trend over time? Use a Line or Area chart. Make sure data is sorted by date.
  • Showing proportions? Use a Pie chart — but only if you have 2–7 slices and they sum to a meaningful whole.
  • Exploring a correlation? Use a Scatter plot. Add a Color/Group field to reveal group-level patterns.
  • Analyzing a distribution? Use a Histogram. Check for skewness or bimodal patterns in the shape.

Data Preparation Tips

  • Keep one row = one record. Do not use merged cells in Excel.
  • Pre-aggregate data when needed. For example, sum sales by region in Excel before uploading — VantaViz plots what it receives.
  • Remove or correct obvious outliers before charting if they skew the visual scale unfairly.
  • Name columns descriptively: Revenue (USD) is clearer than col_3 when it appears as an axis label.

Visual Design Principles

  • One chart = one message. Do not try to show too many metrics on a single chart.
  • Always include axis labels and units. "Revenue" alone is ambiguous — "Revenue (USD, thousands)" is clear.
  • Use consistent colors for the same concept across multiple charts in a report.
  • Start your Y axis at zero for bar charts to avoid exaggerating differences.
  • Export at a sufficiently high resolution for your final destination (slide deck vs. web vs. print).

Frequently Asked Questions

Is my csv data uploaded to VantaViz servers?

No. All file parsing and chart rendering happens directly in your browser. Your data never leaves your device. This is the core privacy-first design of VantaViz.

How large a file can I upload on the Free plan?

VantaViz does not enforce a strict file size limit on the Free plan. Performance depends on your device. Files up to several MB (tens of thousands of rows) typically work well. Very large files may take longer to parse in-browser.

Why does my chart not look right after mapping columns?

Common causes: (1) The column type was auto-detected incorrectly — go back to Preview and verify each column's type. (2) Data is not sorted by date for time-series charts — sort before uploading. (3) There are null/empty values in key columns — use Hide nulls in Preview to identify them.

Can I edit a chart after saving?

Yes. All projects auto-save to your dashboard. Click any project card to re-open it in the editor. You can also export the .vviz project file and re-import it later — even on a different device.

What chart types are available beyond the 6 free ones?

Personal and Business plans unlock additional chart types across four categories: Comparison & Trends (Bubble, Spline, Stacked Bar, Radar, and more), Composition & Flow (Donut, Treemap, Funnel, Waterfall, and more), Statistical & Research (Box Plot, Violin, Density, and more), and Geographic (Map). See the Pricing page for a full feature comparison.

How do I remove the watermark from exports?

Watermark-free exports (PNG, SVG, PDF, PPT) are available on the Personal and Business plans. Compare plans →

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