What Is a Regression Transform in Vega-Lite?

A regression transform is a powerful tool in Vega-Lite that fits two-dimensional regression models to help smooth and predict data. Think of it as a way to create trend lines that sum up your data points or to find the best-fit equation that explains their relationship.

If you're looking to understand patterns, predict future points, or showcase trends, this is the transform you want to explore!

Why Would You Use a Regression Transform?

Imagine you have a scatter plot of your sales data over time, and you want to see if there's a general upward or downward trend. A regression transform can help you add that trend line to your visualization, making it easier to grasp the overall direction of your data.

Supported Models

Here are the types of models you can fit with the regression transform:

• Linear (linear): y = a + b * x
• Logarithmic (log): y = a + b * log(x)
• Exponential (exp): y = a * e^(b * x)
• Power (pow): y = a * x^b
• Quadratic (quad): y = a + b * x + c * x^2
• Polynomial (poly): y = a + b * x + … + k * x^(order)

All these models use ordinary least squares to find the best fit.

How to Apply a Regression Transform

Here's a basic structure to include a regression transform in your Vega-Lite specification:

{
  ...
  "transform": [
    {"regression": "y", "on": "x"} // This creates a linear regression line for y on x
  ],
  ...
}

Here's a JSON example for quick implementation:

{
  "data": { "url": "data/my_scatter_data.json" },
  "mark": "line",
  "encoding": {
    "x": { "field": "x", "type": "quantitative" },
    "y": { "field": "y", "type": "quantitative" }
  },
  "transform": [
    {"regression": "y", "on": "x"}
  ]
}

Practical Example

Let's look at an example where you have a dataset of points and you want to add a regression line to visualize the trend:

[
  {"x": 1, "y": 2.3},
  {"x": 2, "y": 2.7},
  {"x": 3, "y": 3.0},
  // More data points...
]

By applying a regression transform, your final visualization can easily highlight trends.

FAQ

Q1: What types of data trends can I visualize with regression transforms?

You can visualize linear, logarithmic, exponential, power, quadratic, and polynomial trends using regression transforms in Vega-Lite. This flexibility allows you to pick the model that best fits your data's unique pattern.

Q2: How can I include separate trend lines for different groups in my data?

You can use the groupby parameter to fit separate trend lines for each group. This is particularly useful if you're dealing with segmented data and want to see trends within each segment.

Q3: Are the regression transforms in Vega-Lite customizable?

Yes, you can customize your regression transform using parameters like order for polynomial models or extent to define the range of input data. This customization ensures that the regression line fits your specific needs.