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import pandas fileurl = 'https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data' names = ['sepal_length','sepal_width','petal_length','petal_width','class'] data = pandas.read_csv(fileurl, names=names) #Print the correlation pandas.set_option('display.width', 100) pandas.set_option('precision', 2) correlations = data.corr(method='pearson') print(correlations) #-1 indicates 100% negative correlation while a positive 1 indicates 100% correlation. 0 Indicates no correlation. Certain algorithms do not work well with correlated data.
sepal_length
sepal_width
petal_length
petal_width
sepal_length
1.00
-0.11
0.87
0.82
sepal_width
-0.11
1.00
-0.42
-0.36
petal_length
0.87
-0.42
1.00
0.96
petal_width
0.82
-0.36
0.96
1.00