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This notebook demos Python data visualizations on the Iris dataset 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. In [1]: # First, we'll import pandas, a data processing and CSV file I/O library import pandas as pd # We'll also import seaborn, a Python graphing library import warnings # current version of seaborn generates a bunch of warnings that we'll ignore warnings . filterwarnings ( "ignore" ) import seaborn as sns import matplotlib.pyplot as plt sns . set ( style = "white" , color_codes = True ) # Next, we'll load the Iris flower dataset, which is in the "../input/" directory iris = pd . read_csv ( ".....