Chart and dashboard examples you can open and change.

Start with a simple vertical bar graph for comparing one value across categories.

Use horizontal bars when category labels are long or a ranked list should be easy to scan.

Compare multiple series side by side for each category, including double and clustered bar graphs.

Stack multiple series to show both each category total and how the total is composed.

Normalize each category to 100% to compare composition instead of absolute totals.

Start with one distribution and see its median, quartiles, whiskers, and potential outliers.

Compare several distributions next to one another using the same numeric scale.

See how observations beyond Tukey 1.5×IQR fences are separated from the whiskers.

See a longer lower tail with the mean pulled below the median.

See a longer upper tail with the mean pulled above the median.

Label Q1, median, Q3, whisker endpoints, and the mean while viewing the calculated statistics.

Start with a classic pie chart for showing a small set of categories as parts of one whole.

Show calculated percentage labels directly on each slice while keeping the raw values editable.

Use the donut variant to keep the same part-to-whole encoding while opening the center for a total.

Start with a simple XY scatter plot for exploring the relationship between two numeric variables.

See points rise from left to right when larger X values tend to occur with larger Y values.

See points fall from left to right when larger X values tend to occur with smaller Y values.

See a point cloud with little linear association and a Pearson r close to zero.

Add a linear trend line with a regression equation, R², and Pearson r to paired XY observations.

See how one observation can sit far from the main point pattern and deserve closer inspection.

Start with a simple single-series line graph for showing change across an ordered sequence.

Compare two or more ordered series on the same axes with a shared multi-line chart.

Show point markers and explicit values when each observation needs to be read directly.

Start with raw numeric observations and let Vizvero group them into continuous bins.

See a positive-skew distribution with most observations near the lower end and a long right tail.

See a negative-skew distribution concentrated near higher values with a longer tail on the left.

Use a roughly symmetric bell-shaped sample to inspect a center-heavy distribution with lighter tails.

See an approximately even distribution where similar numbers of observations fall into equal-width intervals.

Show the number of observations in each bin with counts on the Y axis and optional value labels.

Express each bin as a percentage of all observations instead of an absolute count.

Start with one ordered series when you want the filled area to emphasize magnitude as well as trend.

Stack additive series to show total magnitude over time while preserving each series contribution.

Compare multiple ordered series from the same zero baseline without adding them into a cumulative stack.