我刚碰到过类似的标题对齐坑，给你两个能完美解决的方案！

问题根源 #

你之前遇到的标题消失、对齐不符合预期，主要是因为Matplotlib的标题系统分两种：画布级的suptitle和绘图区域级的title，它们的对齐参考系不一样，直接用loc='left'没法让两者视觉上统一靠左。另外之前的绘图环境清理操作也可能导致上下文混乱，造成标题不显示。

方案一：精准控制标题位置（最直观） #

通过x参数（取值0-1，对应画布/绘图区域的左右位置）把两个标题都定位到画布左侧的同一位置，代码如下：

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

# 构造mtcars数据集（已有数据集可跳过此步）
mtcars_dict = {'Unnamed: 0': {0: 'Mazda RX4', 1: 'Mazda RX4 Wag', 2: 'Datsun 710', 3: 'Hornet 4 Drive', 4: 'Hornet Sportabout', 5: 'Valiant', 6: 'Duster 360', 7: 'Merc 240D', 8: 'Merc 230', 9: 'Merc 280', 10: 'Merc 280C', 11: 'Merc 450SE', 12: 'Merc 450SL', 13: 'Merc 450SLC', 14: 'Cadillac Fleetwood', 15: 'Lincoln Continental', 16: 'Chrysler Imperial', 17: 'Fiat 128', 18: 'Honda Civic', 19: 'Toyota Corolla', 20: 'Toyota Corona', 21: 'Dodge Challenger', 22: 'AMC Javelin', 23: 'Camaro Z28', 24: 'Pontiac Firebird', 25: 'Fiat X1-9', 26: 'Porsche 914-2', 27: 'Lotus Europa', 28: 'Ford Pantera L', 29: 'Ferrari Dino', 30: 'Maserati Bora', 31: 'Volvo 142E'}, 'mpg': {0: 21.0, 1: 21.0, 2: 22.8, 3: 21.4, 4: 18.7, 5: 18.1, 6: 14.3, 7: 24.4, 8: 22.8, 9: 19.2, 10: 17.8, 11: 16.4, 12: 17.3, 13: 15.2, 14: 10.4, 15: 10.4, 16: 14.7, 17: 32.4, 18: 30.4, 19: 33.9, 20: 21.5, 21: 15.5, 22: 15.2, 23: 13.3, 24: 19.2, 25: 27.3, 26: 26.0, 27: 30.4, 28: 15.8, 29: 19.7, 30: 15.0, 31: 21.4}, 'cyl': {0: 6, 1: 6, 2: 4, 3: 6, 4: 8, 5: 6, 6: 8, 7: 4, 8: 4, 9: 6, 10: 6, 11: 8, 12: 8, 13: 8, 14: 8, 15: 8, 16: 8, 17: 4, 18: 4, 19: 4, 20: 4, 21: 8, 22: 8, 23: 8, 24: 8, 25: 4, 26: 4, 27: 4, 28: 8, 29: 6, 30: 8, 31: 4}, 'disp': {0: 160.0, 1: 160.0, 2: 108.0, 3: 258.0, 4: 360.0, 5: 225.0, 6: 360.0, 7: 146.7, 8: 140.8, 9: 167.6, 10: 167.6, 11: 275.8, 12: 275.8, 13: 275.8, 14: 472.0, 15: 460.0, 16: 440.0, 17: 78.7, 18: 75.7, 19: 71.1, 20: 120.1, 21: 318.0, 22: 304.0, 23: 350.0, 24: 400.0, 25: 79.0, 26: 120.3, 27: 95.1, 28: 351.0, 29: 145.0, 30: 301.0, 31: 121.0}, 'hp': {0: 110, 1: 110, 2: 93, 3: 110, 4: 175, 5: 105, 6: 245, 7: 62, 8: 95, 9: 123, 10: 123, 11: 180, 12: 180, 13: 180, 14: 205, 15: 215, 16: 230, 17: 66, 18: 52, 19: 65, 20: 97, 21: 150, 22: 150, 23: 245, 24: 175, 25: 66, 26: 91, 27: 113, 28: 264, 29: 175, 30: 335, 31: 109}, 'drat': {0: 3.9, 1: 3.9, 2: 3.85, 3: 3.08, 4: 3.15, 5: 2.76, 6: 3.21, 7: 3.69, 8: 3.92, 9: 3.92, 10: 3.92, 11: 3.07, 12: 3.07, 13: 3.07, 14: 2.93, 15: 3.0, 16: 3.23, 17: 4.08, 18: 4.93, 19: 4.22, 20: 3.7, 21: 2.76, 22: 3.15, 23: 3.73, 24: 3.08, 25: 4.08, 26: 4.43, 27: 3.77, 28: 4.22, 29: 3.62, 30: 3.54, 31: 4.11}, 'wt': {0: 2.62, 1: 2.875, 2: 2.32, 3: 3.215, 4: 3.44, 5: 3.46, 6: 3.57, 7: 3.19, 8: 3.15, 9: 3.44, 10: 3.44, 11: 4.07, 12: 3.73, 13: 3.78, 14: 5.25, 15: 5.424, 16: 5.345, 17: 2.2, 18: 1.615, 19: 1.835, 20: 2.465, 21: 3.52, 22: 3.435, 23: 3.84, 24: 3.845, 25: 1.935, 26: 2.14, 27: 1.513, 28: 3.17, 29: 2.77, 30: 3.57, 31: 2.78}, 'qsec': {0: 16.46, 1: 17.02, 2: 18.61, 3: 19.44, 4: 17.02, 5: 20.22, 6: 15.84, 7: 20.0, 8: 22.9, 9: 18.3, 10: 18.9, 11: 17.4, 12: 17.6, 13: 18.0, 14: 17.98, 15: 17.82, 16: 17.42, 17: 19.47, 18: 18.52, 19: 19.9, 20: 20.01, 21: 16.87, 22: 17.3, 23: 15.41, 24: 17.05, 25: 18.9, 26: 16.7, 27: 16.9, 28: 14.5, 29: 15.5, 30: 14.6, 31: 18.6}, 'vs': {0: 0, 1: 0, 2: 1, 3: 1, 4: 0, 5: 1, 6: 0, 7: 1, 8: 1, 9: 1, 10: 1, 11: 0, 12: 0, 13: 0, 14: 0, 15: 0, 16: 0, 17: 1, 18: 1, 19: 1, 20: 1, 21: 0, 22: 0, 23: 0, 24: 0, 25: 1, 26: 0, 27: 1, 28: 0, 29: 0, 30: 0, 31: 1}, 'am': {0: 1, 1: 1, 2: 1, 3: 0, 4: 0, 5: 0, 6: 0, 7: 0, 8: 0, 9: 0, 10: 0, 11: 0, 12: 0, 13: 0, 14: 0, 15: 0, 16: 0, 17: 1, 18: 1, 19: 1, 20: 0, 21: 0, 22: 0, 23: 0, 24: 0, 25: 1, 26: 1, 27: 1, 28: 1, 29: 1, 30: 1, 31: 1}, 'gear': {0: 4, 1: 4, 2: 4, 3: 3, 4: 3, 5: 3, 6: 3, 7: 4, 8: 4, 9: 4, 10: 4, 11: 3, 12: 3, 13: 3, 14: 3, 15: 3, 16: 3, 17: 4, 18: 4, 19: 4, 20: 3, 21: 3, 22: 3, 23: 3, 24: 3, 25: 4, 26: 5, 27: 5, 28: 5, 29: 5, 30: 5, 31: 4}, 'carb': {0: 4, 1: 4, 2: 1, 3: 1, 4: 2, 5: 1, 6: 4, 7: 2, 8: 2, 9: 4, 10: 4, 11: 3, 12: 3, 13: 3, 14: 4, 15: 4, 16: 4, 17: 1, 18: 2, 19: 1, 20: 1, 21: 2, 22: 2, 23: 4, 24: 2, 25: 1, 26: 2, 27: 2, 28: 4, 29: 6, 30: 8, 31: 2}}
mtcars = pd.DataFrame.from_dict(mtcars_dict)

# 绘图代码
plt.figure(figsize=(8,5))
sns.histplot(data=mtcars, x="mpg", bins=30)

# 主标题：x=0.01 紧贴画布左侧，y控制上下位置
plt.suptitle("Mtcars", x=0.01, y=0.98, horizontalalignment='left', fontsize=14)
# 副标题：x=0.01 和主标题对齐，pad调整和主标题的间距
plt.title("histogram", x=0.01, loc='left', fontsize=12, pad=10)

plt.show()

方案二：用Figure和Axes对象更清晰控制 #

如果你习惯面向对象的绘图方式，直接用fig, ax = plt.subplots()分别控制画布和绘图区域，逻辑更清晰：

fig, ax = plt.subplots(figsize=(8,5))
sns.histplot(data=mtcars, x="mpg", bins=30, ax=ax)

# 画布级主标题
fig.suptitle("Mtcars", x=0.01, y=0.98, ha='left', fontsize=14)
# 绘图区域副标题
ax.set_title("histogram", loc='left', fontsize=12, pad=20)

plt.show()

为什么之前的方法不行？ #

• 标题消失：之前的绘图环境清理操作（plt.figure().clear()等）导致绘图上下文混乱，Seaborn绘制的图没有绑定到正确的Figure上，直接创建新的Figure就能避免这个问题。
• 对齐不对：plt.title()的loc='left'是相对于**绘图区域（Axes）的左对齐，而plt.suptitle()的horizontalalignment='left'是相对于整个画布（Figure）**的左对齐，参考系不同导致视觉错开，通过x参数统一位置就能解决。

内容的提问来源于stack exchange，提问作者hachiko