image_output_1.png
import matplotlib.pyplot as plt

import pandas as pd # Data Processing, CSV file I/O (e.g. pd.read_csv)

import seaborn as sns

Iris = pd.read_csv('../input/iris/Iris.csv')

Iris.isnull().sum()

Iris.drop('Id', axis=1, inplace=True)

#Exploratory Data Analysis
#Sepal Length VS Sepal Width
fig=Iris[Iris.Species=='Iris-setosa'].plot(kind='scatter',x='SepalLengthCm',y='SepalWidthCm',marker='x',color='#fa6c33',label='Setosa')
fig=Iris[Iris.Species=='Iris-versicolor'].plot(kind='scatter',x='SepalLengthCm',y='SepalWidthCm',marker='*',color='#3c8991',label='Versicolor',ax=fig)
fig=Iris[Iris.Species=='Iris-virginica'].plot(kind='scatter',x='SepalLengthCm',y='SepalWidthCm',marker='D',color='#d5081e',label='Virginica',ax=fig)
fig.set_xlabel('Sepal Length')
fig.set_ylabel('Sepal Width')
fig.set_title('Sepal Length VS Sepal Width')
fig=plt.gcf()
fig.set_size_inches(10,6)
sns.set_style("darkgrid")
plt.show()

#Exploratory Data Analysis
#Petal Length VS Petal Width
fig=Iris[Iris.Species=='Iris-setosa'].plot(kind='scatter',x='PetalLengthCm',y='PetalWidthCm',marker='x',color='#270c8c',label='Setosa')
fig=Iris[Iris.Species=='Iris-versicolor'].plot(kind='scatter',x='PetalLengthCm',y='PetalWidthCm',marker='o',color='#d5081e',label='Versicolor',ax=fig)
fig=Iris[Iris.Species=='Iris-virginica'].plot(kind='scatter',x='PetalLengthCm',y='PetalWidthCm',marker='>',color='#45aa53',label='Virginica',ax=fig)
fig.set_xlabel('Petal Length')
fig.set_ylabel('Petal Width')
fig.set_title('Petal Length VS Petal Width')
fig=plt.gcf()
fig.set_size_inches(10,6)
sns.set_style("darkgrid")
plt.show()

fig = plt.gcf()
fig.set_size_inches(15, 9)

Iris.plot.area(y=['SepalLengthCm', 'SepalWidthCm', 'PetalLengthCm', 'PetalWidthCm'], alpha=0.5, figsize=(13, 9))