Tracking one or two metrics over time
Daily active users, a stock price, monthly signups. A plain line chart shows the trend without any decoration competing for attention, and it's the easiest chart type for a reader to interpret at a glance.
Line, area, stream graph, bump chart: four templates for a number moving through time, distinguished mostly by what happens to the space under the line. Match the shape to what you're actually measuring, then start from a working template.
Uma visão rápida do que tem aqui. Clique para abrir qualquer um.
Line chart templates are built for one job: showing how a number moves over time, continuously, not just at a handful of checkpoints. Where a bar chart treats each period as a separate box to compare, a line chart draws the path between them, so the shape of the change (a steady climb, a sharp spike, a slow bleed) is the whole point. The four templates in this category share that time-axis foundation but disagree on what else they encode: individual series, cumulative volume, overlapping categories, or shifting rank.
The line-versus-area choice is the one decision worth getting right before you pick a template. A line chart plots values with nothing underneath, good for comparing several series at once since your eye reads relative height without extra ink in the way. An area chart fills the space below the line, and that fill isn't decorative. It visually implies volume or accumulation, so it reads as an amount even when your data is really just a rate. Stack several areas and you gain a sense of the total, but you lose the ability to read any single series cleanly; only the bottom layer sits on a flat baseline.
Stream graph and bump chart are the specialised cases. A stream graph is a stacked area chart with no fixed baseline. It flows symmetrically around a center line instead, trading precise reading for a shape that's easier to scan across many overlapping categories, like genre popularity across decades of music sales. A bump chart drops values entirely and plots rank instead, which is the right call when the story is who's in first place and when that changed, not how big the gap between them was.
Cada um abre seu próprio criador grátis com dados de amostra já carregados.
Daily active users, a stock price, monthly signups. A plain line chart shows the trend without any decoration competing for attention, and it's the easiest chart type for a reader to interpret at a glance.
iOS versus Android share by year, five products' sales over twelve months. Multi-line charts keep every series on the same flat baseline, so slopes stay comparable; filled areas would overlap and obscure each other well before five series.
Cumulative downloads, total rainfall, stacked cost categories over a budget year. An area chart's fill visually reinforces that you're looking at a quantity building up, which a bare line doesn't communicate on its own.
Premier League table position by matchweek, or a song's chart position over its run. A bump chart makes overtakes and drops the entire point, something a value-based line chart buries under noisy vertical movement.
De uma planilha a um gráfico publicado, passo a passo.
One or two series over time: plain line chart. Several series compared side by side: multi-line. Volume or accumulation: area. Rank over time: bump chart.
Each of the four template pages below comes with sample data already plotted, so you can check the date-and-value column layout against your own spreadsheet before importing anything.
Import a CSV or Excel file, paste rows directly, or connect a Google Sheet so the line redraws automatically whenever your source numbers change.
Publish an interactive version where hovering any point shows its exact value, or export a static PNG, SVG or PDF for a slide deck or write-up.
Abra o editor e comece com qualquer modelo nesta categoria. Já vem com dados de amostra.
Abrir o editorA line chart plots values as a path with nothing underneath. An area chart fills the space beneath that path, and the fill visually implies volume or accumulation. Use area only when that 'amount of stuff' reading actually matches your data: filling in a rate or a percentage as an area can make readers see a bigger quantity than really exists.
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