The scatter chart shows the relationship among two metrics, for instance between units and price.
Datasets larger than 100k observations are plotted as datashader heatmaps. The darkness of each shape is proportional to the number of observations encountered. The chart below plots 900k observations.
Datasets smaller than 100k observations are plotted as scatterplots by default.
Often, scatterplots with less than 100k observations are impossible to read because the dots are one on top of the other. The chart above plots 60k observations and the dots are one on top of the other.
To solve this you can try not to show the isolines and you get this.
Alternatively, you could plot the data as a datashader heatmap.
As default, each row of the dataset (which corresponds to an observation, a sale for example) will be plotted as a dot: three sales of the same product in the same period will be plotted as three separate dots.
If you to aggregate all the sales by product, one dot represents the total of sales for each product in the period.
This returns a plot a lot less dots, in which each dot represents the total sales, and the average gross margin, of a product.
To further reduce dot clutter you can plot one or both axes of the plot in log scale. Log scales disables both isolines and trendlines.
The plot is run at the total plotted data level. You color the dots in the plot by the facet dimension
SMALL MULTIPLIES PLOT
The plot also runs on the chosen facet dimension.
You can plot a regression trendline.
In the cases in which the two X and Y metrics can by multiplied in order to show a third metric (here: Units x Average Price in Units = Sales) you can plot isolines of the third metric.
You can choose whether to plot the isolines labels at the right or at the left of the isolines using this widget.
Isolines can change the range of the chart. The same plot without isolines looks like this.
You can choose to plot one period, or both periods together. If you choose to plot both periods together you can color each dot based on the period.
SAVING THE PLOT
To save the plot as a PNG file, hover the top right side on the chart. A menu will appear. Click on the camera icon.
Open the expander under the 📊 Plot type drop down menu by clicking on the ➕ sign.
Additional options are available for selection.
The Y-axis metric and the X-axis metric widget allow you to change the axes of your plot.
You can change the number of top items for the coloring and faceting dimension.
Choose whether to exclude outliers from the plot. If this widget is set to True, another widget will appear to choose beyond how many standard deviations a data point will be considered an outlier.
EDIT AND MOVE LABELS
You can edit and move around plot titles and labels. In this chart...
...you can further adjust the value label position with the mouse.
It is possible to annotate charts with lines, rectangles and circles. It is possible to modify the shapes and move them around, and delete them.
Hover and click on the "draw line", "draw circle" and "draw rectangle" icons on the menu bar on the upper right of the chart.
Draw and edit your shapes.
ADD PLOT MESSAGE
It is possible to add a message to the chart.
Add your message to the text box, one chart at a time.
Once you have finished writing the message for a chart, click on the 🚀 Submit button.
Your message will appear above the chart title.
The downloaded image of the chart contains the message.
The chart title is set on three lines: the first line contains the reporting unit ("who"), the second line the business metric ("what") and the third line the time period ("when").
You can adjust the position of the title, the message text and the horizontal line by moving them around with the mouse.
CHOICE OF COLOR PALETTE
This elegant palette is both beautiful and functional.
This bright palette contains clusters with distinct color separations.
This fresh palette contains modern tones and stunning highlight colors.
BLUE & GREEN PALETTE
This contiguous palette creates a bi-chromatic chart in cool subdued hues.
KHAKI & DENIM PALETTE
This subdued palette great for complex charts.
This subdued palette is good for charts requiring contrast between segments.
HEATING UP PALETTE
This bright palette is great for complex charts.
POWERBI DEFAULT PALETTE
A lively, colorful palette.
This functional palette minimizes the risk of confusion between colors .