Plotting graph For IRIS Dataset Using Seaborn And Matplotlib
Matplotlib.pyplot library is most commonly used in Python in the field of machine learning. It helps in plotting the graph of large dataset. Not only this also helps in classifying different dataset. It can plot graph both in 2d and 3d format. It has a feature of legend, label, grid, graph shape, grid and many more that make it easier to understand and classify the dataset.
Seaborn provides a beautiful with different styled graph plotting that make our dataset more distinguishable and attractive.
To install the package write the below code in terminal of ubuntu/Linux or Window Command prompt.
pip install matplotlib pip install seaborn
Attribute Information about data set:
Attribute Information: -> sepal length in cm -> sepal width in cm -> petal length in cm -> petal width in cm -> class: Iris Setosa Iris Versicolour Iris Virginica Number of Instances: 150 Summary Statistics: Min Max Mean SD Class Correlation sepal length: 4.3 7.9 5.84 0.83 0.7826 sepal width: 2.0 4.4 3.05 0.43 -0.4194 petal length: 1.0 6.9 3.76 1.76 0.9490 (high!) petal width: 0.1 2.5 1.20 0.76 0.9565 (high!) Class Distribution: 33.3% for each of 3 classes.
To get the Iris Data click here.
Plotting graph For IRIS Dataset Using Seaborn Library And matplotlib.pyplot library
Plotting Using Matplotlib
Plotting using Seaborn
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