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Sep 6, 2024 · import pandas as pd # download iris data and read it into a dataframe url = 'http://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data' df = pd. read_csv (url, names = ['sepal_length', 'sepal_width', 'petal_length', 'petal_width', 'class'])
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- iris_dataset.csv · GitHub
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Sepal Length (cm)Sepal Width (cm)Petal Length (cm)Petal Width (cm)5.13.51.40.24.93.01.40.24.73.21.30.24.63.11.50.2This is one of the earliest datasets used in the literature on classification methods and widely used in statistics and machine learning. The data set contains 3 classes of 50 instances each, where each class refers to a type of iris plant.
5.1,3.5,1.4,0.2,Iris-setosa 4.9,3.0,1.4,0.2,Iris-setosa 4.7,3.2,1.3,0.2,Iris-setosa 4.6,3.1,1.5,0.2,Iris-setosa 5.0,3.6,1.4,0.2,Iris-setosa 5.4,3.9,1.7,0.4,Iris ...
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The Iris data set contains four numerical columns for the petal and sepal measurements and one categorical column for the class or type of iris. The pandas read_csv function loads delimited data from a file, URL or file-like object using the comma as the default delimiter and creates a DataFrame object.
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Iris Species Dataset. The Iris dataset was used in R.A. Fisher's classic 1936 paper, The Use of Multiple Measurements in Taxonomic Problems, and can also be found on the UCI Machine Learning Repository. It includes three iris species with 50 samples each as well as some properties about each flower.