使用 Seaborn 和 Matplotlib 绘制 IRIS 数据集的图形
Matplotlib.pyplot库是机器学习领域Python中最常用的库。它有助于绘制大型数据集的图形。这不仅有助于对不同的数据集进行分类。它可以绘制 2d 和 3d 格式的图形。它具有图例、标签、网格、图形形状、网格等功能,使数据集更易于理解和分类。
Seaborn提供了一个漂亮的不同风格的图形绘图,使我们的数据集更具可区分性和吸引力。
安装
要安装软件包,请在 ubuntu/Linux 的终端或窗口命令提示符下编写以下代码。
pip install matplotlib
pip install seaborn
关于数据集的属性信息:
Attribute Information:
-> sepal length in cm
-> sepal width in cm
-> petal length in cm
-> petal width in cm
-> class:
Iris Setosa
Iris Versicolour
Iris Virginica
Number of Instances: 150
Summary Statistics:
Min Max Mean SD Class Correlation
sepal length: 4.3 7.9 5.84 0.83 0.7826
sepal width: 2.0 4.4 3.05 0.43 -0.4194
petal length: 1.0 6.9 3.76 1.76 0.9490 (high!)
petal width: 0.1 2.5 1.20 0.76 0.9565 (high!)
Class Distribution: 33.3% for each of 3 classes.
要获取虹膜数据,请单击此处。
使用 Seaborn 库和 matplotlib.pyplot 库为 IRIS 数据集绘制图形
加载数据中
Python3
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
data = pd.read_csv("Iris.csv")
print (data.head(10))
Python3
import pandas as pd
import matplotlib.pyplot as plt
iris = pd.read_csv("Iris.csv")
plt.plot(iris.Id, iris["SepalLengthCm"], "r--")
plt.show
Python3
iris.plot(kind ="scatter",
x ='SepalLengthCm',
y ='PetalLengthCm')
plt.grid()
Python3
import seaborn as sns
iris = sns.load_dataset('iris')
# style used as a theme of graph
# for example if we want black
# graph with grid then write "darkgrid"
sns.set_style("whitegrid")
# sepal_length, petal_length are iris
# feature data height used to define
# Height of graph whereas hue store the
# class of iris dataset.
sns.FacetGrid(iris, hue ="species",
height = 6).map(plt.scatter,
'sepal_length',
'petal_length').add_legend()
输出:
使用 Matplotlib 绘图
Python3
import pandas as pd
import matplotlib.pyplot as plt
iris = pd.read_csv("Iris.csv")
plt.plot(iris.Id, iris["SepalLengthCm"], "r--")
plt.show
散点图
Python3
iris.plot(kind ="scatter",
x ='SepalLengthCm',
y ='PetalLengthCm')
plt.grid()
使用 Seaborn 绘图
Python3
import seaborn as sns
iris = sns.load_dataset('iris')
# style used as a theme of graph
# for example if we want black
# graph with grid then write "darkgrid"
sns.set_style("whitegrid")
# sepal_length, petal_length are iris
# feature data height used to define
# Height of graph whereas hue store the
# class of iris dataset.
sns.FacetGrid(iris, hue ="species",
height = 6).map(plt.scatter,
'sepal_length',
'petal_length').add_legend()