对红酒质量数据集5个可视化图表,python实现

好的，这里是对红酒质量数据集的5个可视化图表的Python实现代码：

1. 直方图：

import pandas as pd
import matplotlib.pyplot as plt

data = pd.read_csv('winequality-red.csv', sep=';')
plt.hist(data['quality'], bins=6, edgecolor='black')
plt.xlabel('Quality')
plt.ylabel('Count')
plt.title('Wine Quality Distribution')
plt.show()

2. 箱线图：

import pandas as pd
import matplotlib.pyplot as plt

data = pd.read_csv('winequality-red.csv', sep=';')
plt.boxplot(data['quality'])
plt.xlabel('Quality')
plt.title('Wine Quality Distribution')
plt.show()

3. 散点图矩阵：

import pandas as pd
import matplotlib.pyplot as plt
from pandas.plotting import scatter_matrix

data = pd.read_csv('winequality-red.csv', sep=';')
scatter_matrix(data, figsize=(10,10))
plt.show()

4. 热力图：

import pandas as pd
import seaborn as sns

data = pd.read_csv('winequality-red.csv', sep=';')
corr = data.corr()
sns.heatmap(corr, cmap='coolwarm', annot=True)
plt.show()

5. 折线图：

import pandas as pd
import matplotlib.pyplot as plt

data = pd.read_csv('winequality-red.csv', sep=';')
plt.plot(data['quality'], data['fixed acidity'], label='Fixed Acidity')
plt.plot(data['quality'], data['volatile acidity'], label='Volatile Acidity')
plt.plot(data['quality'], data['citric acid'], label='Citric Acid')
plt.plot(data['quality'], data['residual sugar'], label='Residual Sugar')
plt.xlabel('Quality')
plt.ylabel('Feature')
plt.title('Features vs Quality')
plt.legend()
plt.show()