我用Python的Seaborn库，绘制了15个超好看图表!

pip install seaborn

import matplotlib.pyplot as pltimport seaborn as snsimport pandas as pd
print('\n')data = pd.read_csv('iris.csv')print(data[10:15])

print(data['species'].value_counts())

sns.barplot(x='species', y='petal_length', hue='species', data=data)plt.show()

sns.scatterplot(x='petal_length', y='sepal_length', hue='species', style='species', s=90, data=data)plt.show()

sns.histplot(x='sepal_length', kde=True, data=data)plt.show()

sns.histplot(x='sepal_length', kde=True, hue='species', data=data)plt.show()

sns.lineplot(x='petal_length', y='petal_width', data=data)plt.show()

sns.violinplot(x='species', y='petal_length', data=data, hue='species')plt.show()

sns.boxplot(x='species', y='sepal_length', data=data, hue='species')plt.show()

heat_corr = data.corr()sns.heatmap(heat_corr, annot=True)plt.show()

sns.pointplot(x='species', y='petal_length', data=data, markers='^', color='g')plt.show()

sns.kdeplot(x='petal_length', data=data, hue='species', multiple='stack')plt.show()

sns.kdeplot(x='petal_length', y='sepal_length', data=data, hue='species')plt.show()

sns.countplot(x='species', data=data)plt.show()

sns.swarmplot(x='sepal_width', y='species', data=data, hue='species', dodge=True, orient='h', size=8)plt.show()

sns.set(rc={"figure.figsize": (6, 3)})sns.pairplot(data=data, hue='species')plt.show()

g = sns.FacetGrid(data, col="species", height=4, hue='species')g.map(sns.histplot, "petal_length")plt.show()

sns.jointplot(x="sepal_length", y="sepal_width", data=data, palette='Set2', hue='species')plt.show()

sns.catplot(data=data, x="petal_length", y="species", kind="violin", color=".9", inner=None)sns.swarmplot(data=data, x="petal_length", y="species", size=3)plt.show()