python数据处理与分析入门-Pandas数据可视化例子

懂一点的陈老师2024-05-29 11:36

相关内容
Matplotlib可视化练习

Pandas 数据可视化总结

柱状图

reviews['points'].value_counts().sort_index().plot.bar()

散点图

reviews[reviews['price'] < 100].sample(100).plot.scatter(x='price', y='points')

蜂窝图

reviews[reviews['price'] < 100].plot.hexbin(x='price', y='points', gridsize=15)

大量重复的点可以用这种图表示

柱状图-叠加模式

wine_counts.plot.bar(stacked=True)

面积模式

wine_counts.plot.area()

折线模式

wine_counts.plot.line()

美化

设置图的大小，字体大小，颜色，标题

reviews['points'].value_counts().sort_index().plot.bar(
    figsize=(12, 6),
    color='mediumvioletred',
    fontsize=16,
    title='Rankings Given by Wine Magazine',
)

借助Matplotlib

import matplotlib.pyplot as plt

ax = reviews['points'].value_counts().sort_index().plot.bar(
    figsize=(12, 6),
    color='mediumvioletred',
    fontsize=16
)
ax.set_title("Rankings Given by Wine Magazine", fontsize=20)

借助Seaborn-去除边框

import matplotlib.pyplot as plt
import seaborn as sns

ax = reviews['points'].value_counts().sort_index().plot.bar(
    figsize=(12, 6),
    color='mediumvioletred',
    fontsize=16
)
ax.set_title("Rankings Given by Wine Magazine", fontsize=20)
sns.despine(bottom=True, left=True)

多图表

matplotlib

fig, axarr = plt.subplots(2, 2, figsize=(12, 8))

reviews['points'].value_counts().sort_index().plot.bar(
    ax=axarr[0][0]
)

reviews['province'].value_counts().head(20).plot.bar(
    ax=axarr[1][1]