these data sets are typically stored in csv (comma separated valuesformatwhich can be easily read into python for exampleto access the abalone data set from this website with pythondownload the file to your working directoryimport the pandas package via import pandas as pd and read in the data as followsabalone pd read_csv ('abalone data ',header noneit is important to add header noneas this lets python know that the first line of the csv does not contain the names of the featuresas it assumes so by default the data set was originally used to predict the age of abalone from physical measurementssuch as shell weight and diameter another useful repository of over data sets from various packages in the programming languagecollected by vincent arel-bundockcan be found atfor exampleto read fisher' famous iris data set from ' datasets package into pythontypeurlprefix 'https :/vincentarelbundock github iordatasets /csv/dataname 'datasets /iris csv iris pd read_csv urlprefix dataname the iris data set contains four physical measurements (sepal/petal length/widthon specimens (eachof species of irissetosaversicolorand virginica note that in this case the headers are included the output of read_csv is dataframe objectwhich is pandas' implementation of spreadsheetsee section the dataframe method head gives the first few rows of the dataframeincluding the feature names the number of rows can be passed as an argument and is by default for the iris dataframewe haveiris head ( unnamed sepal length petal width species setosa setosa setosa setosa setosa [ rows columns the names of the features can be obtained via the columns attribute of the dataframe objectas in iris columns note that the first column is duplicate index columnwhose name (assigned by pandasis 'unnamed we can drop this column and reassign the iris object as followsiris iris drop('unnamed ,