verticapy.vDataFrame.contour#

Draws the contour plot of the input function using two input vDataColumns.

Parameters#

columns: SQLColumns: List of the vDataColumns names. The list must have two elements.
func: function / str: Function used to compute the contour score. It can also be a SQL expression.
nbins: int, optional: Number of bins used to discretize the two input numerical vDataColumns.
chart: PlottingObject, optional: The chart object to plot on.
**style_kwargs: Any optional parameter to pass to the plotting functions.

Note

The below example is a very basic one. For other more detailed examples and customization options, please see Contour Plot

Let’s begin by importing VerticaPy.

import verticapy as vp

Let’s also import numpy to create a dataset.

import numpy as np

We can create a variable N to fix the size:

N = 30

For contour plots, we also need a function to apply:

def f(x, y):
    return x ** 2 - y + 1

Let’s generate a dataset using the following data.

data = vp.vDataFrame(
    {
        "x": np.random.normal(5, 1, N),
        "y": np.random.normal(8, 1.5, N),
    }
)

Below is an examples of one type of contour plots:

Contour Plot

data.contour(columns = ["x", "y"], func = f)