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seaborn绘制各种图形
2023-12-18 18:31课程教程文章 人已围观
内置示例数据集
seaborn内置了十几个示例数据集,通过load_dataset
函数可以调用。
其中包括常见的泰坦尼克、鸢尾花等经典数据集。
# 查看数据集种类 import seaborn as sns sns.get_dataset_names()
![](https://pic3.zhimg.com/80/v2-aae4f36eb8c767cd503ee00b32f3d62a_720w.png)
import seaborn as sns # 导出鸢尾花数据集 data = sns.load_dataset('iris') data.head()
![1590478587482355.jpg 01.jpg](https://oss.py.cn/pycn/upload/image/461/298/817/1590478587482355.jpg)
1、散点图
函数sns.scatterplot
import seaborn as sns sns.set() import matplotlib.pyplot as plt %matplotlib inline # 小费数据集 tips = sns.load_dataset('tips') ax = sns.scatterplot(x='total_bill',y='tip',data=tips) plt.show()
2、条形图
函数sns.barplot
显示数据平均值和置信区间
import seaborn as sns sns.set() import matplotlib.pyplot as plt %matplotlib inline # 小费数据集t ips = sns.load_dataset("tips") ax = sns.barplot(x="day", y="total_bill", data=tips) plt.show()
![1590478716906682.jpg 02.jpg](https://oss.py.cn/pycn/upload/image/325/159/956/1590478716906682.jpg)
3、线型图
函数sns.lineplot
绘制折线图和置信区间
import seaborn as sns sns.set() import matplotlib.pyplot as plt %matplotlib inline fmri = sns.load_dataset("fmri") ax = sns.lineplot(x="timepoint", y="signal", data=fmri) plt.show()
![1590478824138181.jpg 03.jpg](https://oss.py.cn/pycn/upload/image/385/833/861/1590478824138181.jpg)
4、箱线图
函数seaborn.boxplot
import seaborn as sns sns.set() import matplotlib.pyplot as plt %matplotlib inline tips = sns.load_dataset("tips") ax = sns.boxplot(x="day", y="total_bill", data=tips) plt.show()
![1590478887227320.jpg 04.jpg](https://oss.py.cn/pycn/upload/image/441/237/902/1590478887227320.jpg)
5、直方图
函数seaborn.distplot
import seaborn as sns import numpy as np sns.set() import matplotlib.pyplot as plt %matplotlib inline np.random.seed(0) x = np.random.randn(1000) ax = sns.distplot(x) plt.show()
![1590479876286177.jpg 05.jpg](https://oss.py.cn/pycn/upload/image/724/619/626/1590479876286177.jpg)
6、热力图
函数seaborn.heatmap
import numpy as np np.random.seed(0) import seaborn as sns sns.set() import matplotlib.pyplot as plt %matplotlib inline uniform_data = np.random.rand(10, 12) ax = sns.heatmap(uniform_data) plt.show()
![1590479933697284.jpg 06.jpg](https://oss.py.cn/pycn/upload/image/992/464/533/1590479933697284.jpg)
7、散点图矩阵
函数sns.pairplot
import seaborn as sns sns.set() import matplotlib.pyplot as plt %matplotlib inline iris = sns.load_dataset("iris") ax = sns.pairplot(iris) plt.show()
![1590480031212427.jpg 07.jpg](https://oss.py.cn/pycn/upload/image/786/400/441/1590480031212427.jpg)
8、分类散点图
函数seaborn.catplot
import seaborn as sns sns.set() import matplotlib.pyplot as plt %matplotlib inline exercise = sns.load_dataset("exercise") ax = sns.catplot(x="time", y="pulse", hue="kind", data=exercise)\ plt.show()
![1590480164576062.jpg 08.jpg](https://oss.py.cn/pycn/upload/image/653/238/777/1590480164576062.jpg)
9、计数条形图
函数seaborn.countplot
import seaborn as sns sns.set() import matplotlib.pyplot as plt %matplotlib inline titanic = sns.load_dataset("titanic") ax = sns.countplot(x="class", data=titanic) plt.show()
![1590480149549714.jpg 09.jpg](https://oss.py.cn/pycn/upload/image/886/517/786/1590480149549714.jpg)
10、回归图
函数 seaborn.lmplot
绘制散点及回归图
import seaborn as sns sns.set() import matplotlib.pyplot as plt %matplotlib inline tips = sns.load_dataset("tips") ax = sns.lmplot(x="total_bill", y="tip", data=tips) plt.show()
![1590480269687577.jpg 10.jpg](https://oss.py.cn/pycn/upload/image/283/827/247/1590480269687577.jpg)
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