vastorbit.VastColumn.boxplot¶

Draws the box plot of the VastColumn.

Parameters:

by (str, optional) – VastColumn used to partition the data.
q (tuple, optional) – Tuple including the 2 quantiles used to draw the BoxPlot.
h (PythonNumber, optional) – Interval width if the ‘by’ VastColumn is numerical or of a date-like type. Optimized h will be computed if the parameter is empty or invalid.
max_cardinality (int, optional) – Maximum number of distinct VastColumn elements to be used as categorical. The less frequent elements are gathered together to create a new category : ‘Others’.
cat_priority (PythonScalar / ArrayLike, optional) – ArrayLike list of the different categories to consider when drawing the box plot. The other categories are filtered.
max_nb_fliers (int, optional) – Maximum number of points used to represent the fliers of each category. Drawing fliers slows down the graphic computation.
whis (float, optional) – The position of the whiskers.
chart (PlottingObject, optional) – The chart object to plot on.
**style_kwargs – Any optional parameter to pass to the plotting functions.

Returns:

Plotting Object.

Return type:

obj

Examples

Note

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

Let’s begin by importing vastorbit.

import vastorbit as vo

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 = vo.VastFrame(
    {
        "score1": np.random.normal(5, 1, N),
    }
)

Now we are ready to draw the plot:

data["score1"].boxplot()