visualize iris dataset using python

This notebook demos Python data visualizations on the Iris dataset

from: https://www.kaggle.com/benhamner/d/uciml/iris/python-data-visualizations

This Python 3 environment comes with many helpful analytics libraries installed. It is defined by the kaggle/python docker image

We’ll use three libraries for this tutorial: pandas, matplotlib, and seaborn.

Press “Fork” at the top-right of this screen to run this notebook yourself and build each of the examples.

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  Id SepalLengthCm SepalWidthCm PetalLengthCm PetalWidthCm Species
0 1 5.1 3.5 1.4 0.2 Iris-setosa
1 2 4.9 3.0 1.4 0.2 Iris-setosa
2 3 4.7 3.2 1.3 0.2 Iris-setosa
3 4 4.6 3.1 1.5 0.2 Iris-setosa
4 5 5.0 3.6 1.4 0.2 Iris-setosa
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Wrapping Up

I hope you enjoyed this quick introduction to some of the quick, simple data visualizations you can create with pandas, seaborn, and matplotlib in Python!

I encourage you to run through these examples yourself, tweaking them and seeing what happens. From there, you can try applying these methods to a new dataset and incorprating them into your own workflow!

See Kaggle Datasets for other datasets to try visualizing. The World Food Facts data is an especially rich one for visualization.