【数据分析可视化】seaborn介绍

Kande ·
更新时间:2024-11-10
· 769 次阅读

存在意义

是matplotlib的扩展封装

简单使用 import numpy as np import pandas as pd import matplotlib.pyplot as plt import seaborn as sns %matplotlib inline /Users/bennyrhys/opt/anaconda3/lib/python3.7/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject return f(*args, **kwds) /Users/bennyrhys/opt/anaconda3/lib/python3.7/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject return f(*args, **kwds) /Users/bennyrhys/opt/anaconda3/lib/python3.7/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject return f(*args, **kwds) /Users/bennyrhys/opt/anaconda3/lib/python3.7/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject return f(*args, **kwds) iris = pd.read_csv('/Users/bennyrhys/Desktop/数据分析可视化-数据集/homework/iris.csv') iris.head()
SepalLength SepalWidth PetalLength PetalWidth Name
0 5.1 3.5 1.4 0.2 Iris-setosa
1 4.9 3.0 1.4 0.2 Iris-setosa
2 4.7 3.2 1.3 0.2 Iris-setosa
3 4.6 3.1 1.5 0.2 Iris-setosa
4 5.0 3.6 1.4 0.2 Iris-setosa
需求:画一个花瓣(petal)和花萼(sepal)长度的散点图,并且点的颜色要区分鸢尾花的种类 # 花的种类 iris.Name.unique() array(['Iris-setosa', 'Iris-versicolor', 'Iris-virginica'], dtype=object) # 设置对应颜色字典 color_map = dict(zip(iris.Name.unique(),['blue','green','red'])) color_map {'Iris-setosa': 'blue', 'Iris-versicolor': 'green', 'Iris-virginica': 'red'} # 原本画图 for species, group in iris.groupby('Name'): plt.scatter(group['PetalLength'],group['SepalLength'], color = color_map[species], alpha=0.3,edgecolor=None, label = species) plt.legend(frameon=True, title='None') plt.xlabel('PetalLength') plt.ylabel('SepalLength')

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作者:bennyrhys瑞新



Seaborn 数据 数据分析 可视化

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