Loading...

verticapy.vDataFrame.hist

vDataFrame.hist(columns: Annotated[str | list[str], 'STRING representing one column or a list of columns'], method: Literal['density', 'count', 'avg', 'min', 'max', 'sum'] | str = 'density', of: str | None = None, h: Annotated[int | float | Decimal, 'Python Numbers'] | None = None, chart: PlottingBase | TableSample | Axes | mFigure | Highchart | Highstock | Figure | None = None, **style_kwargs) → PlottingBase | TableSample | Axes | mFigure | Highchart | Highstock | Figure

Draws the histograms of the input vDataColumns based on an aggregation.

Parameters

columns: SQLColumns

list of the vDataColumns names. The list must have less than 5 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, for example: AVG(column1) + 5

of: str, optional

The vDataColumns used to compute the aggregation.

h: tuple, optional

Interval width of the input vDataColumns. 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 Histogram

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 = 50

Let’s generate a dataset using the following data.

data = vp.vDataFrame(
    {
        "score1": np.random.normal(5, 1, N),
        "score2": np.random.normal(8, 1.5, N),
        "score3": np.random.normal(10, 2, N),
    }
)

Below are examples of two types of hist plots:

  • Single

  • Multi

data.hist(["score1"])

data.hist(columns = ["score1", "score2"])