Line Chart Generator Free Online Tool 2026

Last updated March 22, 2026

Monthly Sales Trend Chart

Create a line chart showing monthly sales figures for the year. Input data (CSV format):

Month,Sales
Jan,42000
Feb,38000
Mar,51000
Apr,47000
May,63000
Jun,71000
Jul,68000
Aug,74000
Sep,82000
Oct,79000
Nov,91000
Dec,105000

Chart settings:

• Title: "Monthly Sales 2024"
• X-axis label: "Month"
• Y-axis label: "Revenue ($)"
• Line color: #3b82f6 (blue)
• Show data points: yes
• Fill area under line: yes (light blue)

The resulting chart clearly shows the upward sales trend with a strong Q4 performance.

Comparing Multiple Data Series

Compare sales across three product lines on the same chart:

Month,Product A,Product B,Product C
Jan,12000,8000,22000
Feb,11000,9500,17500
Mar,15000,11000,25000
Apr,14000,10500,22500
May,18000,13000,32000
Jun,21000,15500,34500

Chart settings:

• Series colors: Product A = #3b82f6, Product B = #ef4444, Product C = #10b981
• Legend position: top-right
• Line style: solid for all series
• Show grid lines: yes

The multi-series chart immediately shows that Product C consistently outsells the others, while Product A and B track closely together.

Website Traffic Over Time

Visualize daily website visitors over a 30-day period:

Date,Visitors,Page Views
2024-01-01,1250,3800
2024-01-02,1180,3500
2024-01-03,980,2900
2024-01-04,1050,3100
2024-01-05,1420,4200
...
2024-01-30,2100,6300

Chart settings:

• X-axis: date format (auto-detected)
• Dual Y-axis: Visitors on left, Page Views on right
• Smooth curves: cubic spline interpolation
• Annotation: vertical line on Jan 15 labeled "Campaign Launch"

The dual Y-axis allows comparing two metrics with different scales on the same chart.

Actual vs. Projected Performance

Show actual results against projections with different line styles:

Quarter,Actual,Projected
Q1 2023,145000,150000
Q2 2023,162000,155000
Q3 2023,158000,165000
Q4 2023,189000,175000
Q1 2024,201000,190000
Q2 2024,215000,205000

Chart settings:

• Actual: solid blue line with circle markers
• Projected: dashed gray line with no markers
• Reference line: horizontal at 200,000 labeled "Annual Target"

The dashed line for projections is a standard convention that makes it immediately clear which series is actual data and which is forecast.

Temperature Data with Logarithmic Scale

For data spanning multiple orders of magnitude, use a logarithmic Y-axis:

Year,Bacteria Count
Day 1,100
Day 2,320
Day 3,1024
Day 4,3277
Day 5,10486
Day 6,33554
Day 7,107374

Chart settings:

• Y-axis scale: logarithmic
• Title: "Bacterial Growth (Log Scale)"
• Line color: #ef4444 (red)

On a linear scale, the early values would be invisible. The log scale shows the exponential growth pattern as a straight line, making the growth rate immediately apparent.

Adding Annotations to Highlight Events

Mark significant events on a stock price chart:

Date,Price
2024-01-02,145.20
2024-01-15,152.80
2024-02-01,148.30
2024-02-14,161.50
2024-03-01,158.90
2024-03-15,172.40

Annotations added:

• Vertical line at 2024-01-15: "Earnings Report"
• Vertical line at 2024-02-14: "Product Launch"
• Horizontal reference line at 160: "Analyst Target Price"
• Shaded region from 2024-02-01 to 2024-02-14: "Pre-launch Period"

Annotations transform a plain price chart into a narrative that explains why the price moved.

Exporting for Different Use Cases

The generator offers multiple export formats:

PNG Export:
- Resolution: 1920×1080 (for presentations)
- Background: white
- Use for: PowerPoint slides, Word documents, email attachments

SVG Export:
- Vector format, scales to any size
- File size: ~15 KB (vs ~200 KB for PNG)
- Use for: web pages, responsive designs, print publications

PDF Export:
- Print-ready format
- Embedded fonts
- Use for: reports, academic papers, formal documents

Smooth vs. Angular Lines

Choose between smooth curves and sharp angular lines based on your data type:

Angular lines (default):
- Best for: discrete data points, stock prices, exact measurements
- Shows: exact values at each data point
- Appearance: straight lines connecting each point

Smooth curves (cubic spline):
- Best for: continuous phenomena, temperature trends, growth curves
- Shows: smooth interpolation between points
- Appearance: flowing curves that suggest continuity

Setting: Line style → Smooth (cubic spline interpolation)

Use smooth curves when the underlying phenomenon is continuous (like temperature or population growth) and angular lines when the data represents discrete measurements or exact values at specific points.