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verticapy.vDataFrame.heatmap#

vDataFrame.heatmap(columns: str | list[str], method: Literal['density', 'count', 'avg', 'min', 'max', 'sum'] | str = 'count', of: str | None = None, h: tuple = (None, None), chart: PlottingBase | TableSample | Axes | mFigure | Highchart | Highstock | Figure | None = None, **style_kwargs) PlottingBase | TableSample | Axes | mFigure | Highchart | Highstock | Figure#

Draws the Heatmap of the two input vDataColumns.

Parameters#

columns: SQLColumns

List of the vDataColumns names. The list must have two elements.

method: str, optional

The method used to aggregate the data.

  • count:

    Number of elements.

  • density:

    Percentage of the distribution.

  • mean:

    Average of the vDataColumns of.

  • min:

    Minimum of the vDataColumns of.

  • max:

    Maximum of the vDataColumns of.

  • sum:

    Sum of the vDataColumns of.

  • q%:

    q Quantile of the vDataColumns of (ex: 50% to get the median).

It can also be a cutomized aggregation (ex: AVG(column1) + 5).

of: str, optional

The vDataColumn used to compute the aggregation.

h: tuple, optional

Interval width of the vDataColumns 1 and 2 bars. Optimized h will be computed if the parameter is empty or invalid.

chart: PlottingObject, optional

The chart object to plot on.

**style_kwargs

Any optional parameter to pass to the plotting functions.

Returns#

obj

Plotting Object.

Examples#

Note

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

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

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 heatmap plots:

  • Heatmap

data.heatmap(columns = ["x", "y"])

See also

vDataFrame.hexbin() : Hexbin Plot.
vDataFrame.contour() : Contour Plot.