What are parallel coordinates and parallel categories in plotly?

What are parallel coordinates and parallel categories in plotly?

What are parallel coordinates and parallel categories in plotly?

This recipe explains what are parallel coordinates and parallel categories in plotly


Recipe Objective

What are parallel coordinates and parallel categories in plotly, explain with example.

Parallel Coordinates in this each row of the dataframe is represented by a polyline mark which traverses a set of parallel axes, one for each of the dimensions. For this we have to use function "px.parallel_coordinates". Parallel Categories this is useful for visualizin multi-dimensional categorical data. Each variable in the data set is represented by a column of rectangles, where each rectangle corresponds to a discrete value taken on by that variable. The relative heights of the rectangles reflect the relative frequency of occurrence of the corresponding value.

Step 1 - Import the necessary libraries

import plotly.express as px import seaborn as sns

Step 2 - load the Sample data

Sample_data = px.data.iris() Sample_data.head()

Step 3 - Plot the Parallel coordinates graph

fig = px.parallel_coordinates(Sample_data, color="species_id", labels={"species_id": "Species", "sepal_width": "Sepal Width", "sepal_length": "Sepal Length", "petal_width": "Petal Width", "petal_length": "Petal Length", }, color_continuous_scale=px.colors.diverging.Tealrose, color_continuous_midpoint=2, ) fig.show()

Here in the above plot the functions used are:

color - It will consist name of a column in the dataframe, values from this are used to assign color to marks.

labels - this can be dictionary with string keys and string values, the column are used here is for axis titles. The keys of the dictionary should correspond to column names, and the values should correspond to the desired label to be displayed.

color_continuos scale - these are list of string, the strings should valid CSS-color. This list is used to build a continuous color scale when the column denoted by color contains numeric data.

color_continuos_midpoint - computes the bounds of the continuous color scale to have the desired midpoint.

Step 4 - Plot the Parallel categories graph

Sample_data2 = px.data.tips() fig = px.parallel_categories(Sample_data2, color="size", color_continuous_scale=px.colors.sequential.Inferno) fig.show()

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