Histogram

The Histogram node creates histograms using ggplot2 to help you visualise the distribution of a single variable in your data.

What it does

Creates a histogram from one column of your dataset
Optionally fill bars by a grouping variable
Supports custom axis labels and bin count
The plot can be downloaded as a PNG image

How to use it

Connect a data source — drag an edge from an Input CSV node
Select a variable — choose which column to plot
Optionally configure — set a fill variable, number of bins, or custom axis labels
Click Run — the histogram is generated and displayed

Configuration

Setting	Required	Description
Upstream connection	Yes	A node providing data
Variable	Yes	The column to plot on the x axis
Fill variable	No	Choose a categorical grouping variable to colour bars by, leave at the default for grey bars, or select No colour fill for transparent bars with black outlines
Number of bins	No	How many bins to use (default: 30)
X axis label	No	Custom label (defaults to column name)
Y axis label	No	Custom label (defaults to “Count”)
Comment	No	Annotation for generated R code

Output

The Output tab displays:

The histogram as an image
A Zoom button to view the plot full-screen
A Download plot button to save it as a PNG file (named histogram_{variable}.png)

Generated R code

Basic histogram:

library(ggplot2)
ggplot(data = my_data, aes(x = height)) +
  geom_histogram() +
  theme_classic()

With fill variable, custom bins and labels:

library(ggplot2)
ggplot(data = my_data, aes(x = height, fill = species)) +
  geom_histogram(bins = 20, position = "identity", alpha = 0.5) +
  theme_classic() +
  labs(x = "Height (cm)", y = "Frequency")

With no colour fill:

library(ggplot2)
ggplot(data = my_data, aes(x = height)) +
  geom_histogram(fill = NA, colour = "black") +
  theme_classic()

Tips

Choose a numeric column to get a meaningful histogram
The fill variable is useful for comparing distributions across groups
When using a fill variable, bars are overlaid with transparency so you can see both distributions
If the default 30 bins produces a noisy or overly smooth plot, try adjusting the bin count
You can download the plot for use in reports or presentations