Box plot & histogram — see the distribution

The histogram bins a numeric variable into a frequency distribution: DataLion forms the bins automatically and shows how often values fall into each range. The number of bins comes from Sturges' rule — a proven starting point for most distributions.

If the default does not fit, override the bin count under chart settings → Bins. That makes skew, clustering and gaps in age, revenue or ratings visible in a single click.

• A numeric variable binned into a frequency distribution
• Automatic bin count via Sturges' rule
• Bin count freely overridable under chart settings → Bins
• Skew, clustering and gaps at a glance

The box plot draws a classic Tukey box with minimum, Q1, median, Q3 and maximum: the box spans the middle 50% of the values, the line marks the median, and the whiskers reach the extreme values within range.

Values beyond 1.5×the interquartile range (IQR) are drawn as individual outlier points. So you spot spread and extreme cases at once — without an average that hides them.

• Tukey box with minimum, Q1, median, Q3 and maximum
• Whiskers to the extreme values within range
• Outliers beyond 1.5×the IQR as points
• Spread and extreme cases instead of a single average

Without a breakdown the box plot shows one box per selected numeric variable. Add a categorical breakdown and DataLion draws one box per group — so you compare a distribution directly across segments such as region, age group or wave.

Both chart types render with amCharts4 and export to PowerPoint via image export. DataLion already offers regression, ANOVA and driver analysis — these charts close the gap of visualising a distribution, its spread and outliers directly. Note: in this first version the distributions are unweighted.

• Without a breakdown: one box per numeric variable
• With a categorical breakdown: one box per group
• Rendered with amCharts4, image export to PowerPoint
• Complements regression, ANOVA and driver analysis with the distribution view