组合条形图和线图的问题

Question

我有这样的数据框：

df_meshX_min_select = pd.DataFrame({
'Number of Elements'  : [5674, 8810,13366,19751,36491],
'Time (a)'            : [42.14, 51.14, 55.64, 55.14, 56.64],
'Different Result(Temperature)' : [0.083849, 0.057309, 0.055333, 0.060516, 0.035343]})

我尝试将条形图（元素数量与不同结果）和线图（元素数量与时间）结合在同一图中，但我发现了以下问题：

合并 2 个图时，x_value 似乎不匹配，但如果您看到数据框，x 值是完全相同的值。

我的期望是将这两张图合并成一张图：

这是我制作的代码：

import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker

df_meshX_min_select = pd.DataFrame({
    'Number of Elements'  : [5674, 8810,13366,19751,36491],
    'Time (a)'            : [42.14, 51.14, 55.64, 55.14, 56.64],
    'Different Result(Temperature)' : [0.083849, 0.057309, 0.055333, 0.060516, 0.035343]})

x1= df_meshX_min_select["Number of Elements"]
t1= df_meshX_min_select["Time (a)"]
T1= df_meshX_min_select["Different Result(Temperature)"]

#Create combo chart
fig, ax1 = plt.subplots(figsize=(10,6))
color = 'tab:green'
#bar plot creation
ax1.set_title('Mesh Analysis', fontsize=16)
ax1.set_xlabel('Number of elements', fontsize=16)
ax1.set_ylabel('Different Result(Temperature)', fontsize=16)
ax1 = sns.barplot(x='Number of Elements', y='Different Result(Temperature)', data = df_meshX_min_select)
ax1.tick_params(axis='y')

#specify we want to share the same x-axis
ax2 = ax1.twinx()
color = 'tab:red'
#line plot creation
ax2.set_ylabel('Time (a)', fontsize=16)
ax2 = sns.lineplot(x='Number of Elements', y='Time (a)', data = df_meshX_min_select, sort=False, color=color, ax=ax2)
ax2.tick_params(axis='y', color=color)
#show plot


plt.show()

Answer 1

Seaborn 和 pandas 使用分类 x 轴表示条形图（内部编号为 0,1,2,...），使用浮点数表示折线图。请注意，您的 x 值间隔不均匀，因此条形图之间的距离可能会很奇怪，或者与线图中的 x 值不对齐。

这是使用标准 matplotlib 组合两个图的解决方案。

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

df_meshx_min_select = pd.DataFrame({
    'number of elements': [5674, 8810, 13366, 19751, 36491],
    'time (a)': [42.14, 51.14, 55.64, 55.14, 56.64],
    'different result(temperature)': [0.083849, 0.057309, 0.055333, 0.060516, 0.035343]})
x1 = df_meshx_min_select["number of elements"]
t1 = df_meshx_min_select["time (a)"]
d1 = df_meshx_min_select["different result(temperature)"]

fig, ax1 = plt.subplots(figsize=(10, 6))
color = 'limegreen'
ax1.set_title('mesh analysis', fontsize=16)
ax1.set_xlabel('number of elements', fontsize=16)
ax1.set_ylabel('different result(temperature)', fontsize=16, color=color)
ax1.bar(x1, height=d1, width=2000, color=color)
ax1.tick_params(axis='y', colors=color)

ax2 = ax1.twinx()  # share the x-axis, new y-axis
color = 'crimson'
ax2.set_ylabel('time (a)', fontsize=16, color=color)
ax2.plot(x1, t1, color=color)
ax2.tick_params(axis='y', colors=color)

plt.show()