如何用Matplotlib绘制分组柱状图叠加折线图并解决显示问题

目标图表 #

需要复现的是包含分组柱状图（展示两类占比分布）和双折线图（展示两类事件率）的双Y轴组合图表。

表格数据 #

遇到的问题 #

• 柱状图出现重叠
• X轴标签未旋转，导致文字重叠
• 需要为折线图添加标记点

原代码 #

import pandas as pd
import matplotlib.pyplot as plt

# Create a Pandas DataFrame with your data
data = {
    "Category": ["00 (-inf, 0.25)", "01 [0.25, 4.75)", "02 [4.75, 6.75)", "03 [6.75, 8.25)",
                 "04 [8.25, 9.25)", "05 [9.25, 10.75)", "06 [10.75, 11.75)", "07 [11.75, 13.75)", "08 [13.75, inf)"],
    "%_total_dist_1": [5.7, 7, 10.5, 13.8, 9.1, 14.1, 13.7, 16.8, 9.4],
    "event_rate_%_1": [36.5, 11.2, 5, 3.9, 3.4, 2.5, 1.6, 1.3, 1],
    "%_total_dist_2": [5.8, 7, 10.5, 13.7, 9.2, 14.2, 13.7, 16.7, 9.1],
    "event_rate_%_2": [10, 11, 4.8, 4, 3.1, 2.4, 1.8, 1.3, 1.3]
}

df = pd.DataFrame(data)

# Create a figure and primary y-axis
fig, ax1 = plt.subplots(figsize=(10, 6))

# Plot percentage distribution on the primary y-axis
ax1.bar(df['Category'], df['%_total_dist_1'], alpha=0.7, label="%_total_dist_1", color='b')
ax1.bar(df['Category'], df['%_total_dist_2'], alpha=0.7, label="%_total_dist_2", color='g')
ax1.set_ylabel('% Distribution', color='b')
ax1.tick_params(axis='y', labelcolor='b')

# Create a secondary y-axis
ax2 = ax1.twinx()

# Plot event rate on the secondary y-axis
ax2.plot(df['Category'], df['event_rate_%_1'], marker='o', label='event_rate_%_1', color='r')
ax2.plot(df['Category'], df['event_rate_%_2'], marker='o', label='event_rate_%_2', color='orange')
ax2.set_ylabel('Event Rate (%)', color='r')
ax2.tick_params(axis='y', labelcolor='r')

# Adding legend
fig.tight_layout()
plt.title('Percentage Distribution and Event Rate')
fig.legend(loc="upper left", bbox_to_anchor=(0.15, 0.85))

# Rotate x-axis labels for better readability
plt.xticks(rotation=45, ha="right")

# Show the plot
plt.show()

修正后的代码 #

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

# 构建数据
data = {
    "Category": ["00 (-inf, 0.25)", "01 [0.25, 4.75)", "02 [4.75, 6.75)", "03 [6.75, 8.25)",
                 "04 [8.25, 9.25)", "05 [9.25, 10.75)", "06 [10.75, 11.75)", "07 [11.75, 13.75)", "08 [13.75, inf)"],
    "%_total_dist_1": [5.7, 7, 10.5, 13.8, 9.1, 14.1, 13.7, 16.8, 9.4],
    "event_rate_%_1": [36.5, 11.2, 5, 3.9, 3.4, 2.5, 1.6, 1.3, 1],
    "%_total_dist_2": [5.8, 7, 10.5, 13.7, 9.2, 14.2, 13.7, 16.7, 9.1],
    "event_rate_%_2": [10, 11, 4.8, 4, 3.1, 2.4, 1.8, 1.3, 1.3]
}

df = pd.DataFrame(data)

# 创建画布和主Y轴
fig, ax1 = plt.subplots(figsize=(12, 6))

# 设置X轴索引和柱子宽度
x = np.arange(len(df['Category']))
width = 0.35

# 绘制分组柱状图，避免重叠
bar1 = ax1.bar(x - width/2, df['%_total_dist_1'], width, alpha=0.7, label="%_total_dist_1", color='blue')
bar2 = ax1.bar(x + width/2, df['%_total_dist_2'], width, alpha=0.7, label="%_total_dist_2", color='green')

# 主Y轴设置
ax1.set_ylabel('占比分布 (%)', color='blue')
ax1.tick_params(axis='y', labelcolor='blue')
# 设置X轴标签并旋转45度，右对齐
ax1.set_xticks(x)
ax1.set_xticklabels(df['Category'], rotation=45, ha='right')

# 创建副Y轴
ax2 = ax1.twinx()

# 绘制带标记点的折线图
line1, = ax2.plot(x, df['event_rate_%_1'], marker='o', markersize=6, label='event_rate_%_1', color='red')
line2, = ax2.plot(x, df['event_rate_%_2'], marker='s', markersize=6, label='event_rate_%_2', color='orange')

# 副Y轴设置
ax2.set_ylabel('事件率 (%)', color='red')
ax2.tick_params(axis='y', labelcolor='red')

# 合并图例
ax1.legend(handles=[bar1, bar2, line1, line2], loc="upper left")

# 调整布局，防止标签被截断
plt.title('占比分布与事件率')
fig.tight_layout()

plt.show()

关键修正说明 #

1. 解决柱状图重叠：用np.arange生成X轴数值索引，给两组柱子分别设置x - width/2和x + width/2的位置，实现分组排列。
2. X轴标签旋转：直接在主轴ax1上设置xticklabels时添加rotation=45和ha='right'，确保标签旋转后对齐整齐，避免重叠。
3. 折线标记点：保留marker参数，通过markersize调整标记大小，用不同形状（圆形、方形）区分两组数据，提升辨识度。

内容的提问来源于stack exchange，提问作者bunti papu