Distribution Data
Explore our comprehensive workflows related to Distribution Data, a crucial aspect of supply chain management that focuses on the effective dissemination of products and information. Discover best practices, tools, and strategies to optimize your distribution processes, enhance data accuracy, and improve decision-making. Whether you're looking to streamline logistics or analyze distribution patterns, our curated workflows will guide you. Dive in now to unlock the potential of your distribution data!
Create a Jitter Plot
A jitter plot is similar to scatter plot but introduces intentional random dispersions of points – referred to as ‘jittering’ – along one axis to prevent overlapping. This technique helps to reveal the density and distribution of data points that would otherwise overlap. Create your own using this workflow!
Create a Histogram
A histogram is used to display the distribution of a dataset by dividing it into intervals, or bins, and counting the data points that fall into each interval. Create your own with this workflow!
Create Density Plots
A density plot measures the probability distribution of a continuous variable. By providing a smooth curve that represents the distribution of data points over a range, it helps readers to identify patterns, trends, and the overall shape of the distribution.
Create a Boxplot
A boxplot, or box-and-whiskers plot, is a standardized method for displaying the distribution of a dataset. It highlights five key aspects: the minimum value, the first quartile (Q1), median, third quartile (Q3), and the maximum value. Create your own with this workflow!
Create Beeswarm Plot with Boxplot Overlay
A beeswarm chart visualizes data points along a single axis, with dots representing each individual datapoint. Create your own using this workflow!