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seaborn常用的10种数据分析图表

 3 years ago
source link: https://zhuanlan.zhihu.com/p/130510767
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seaborn常用的10种数据分析图表

公号：Python大数据分析，关注进学习群

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()
v2-aae4f36eb8c767cd503ee00b32f3d62a_720w.png
import seaborn as sns
# 导出鸢尾花数据集
data = sns.load_dataset('iris')
data.head()
v2-9d5c6c71097a553244af7fb96f09c350_720w.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()
v2-3bbb46e0ffb0f4c3fe5b17eba1792e64_720w.jpg

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
tips = sns.load_dataset("tips")
ax = sns.barplot(x="day", y="total_bill", data=tips)
plt.show()

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()

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()

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()

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()

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()

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()

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()

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()
v2-0a306750dadf67e133c061c3b645da16_720w.jpg

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