如何在tkinter中显示matplotlib图表

Question

我试图在tkinter窗口中显示4个或更多图表，但它们放错了位置，我认为我还需要一个滚动条。代码如下：

root = tk.Tk()

    figure1 = plt.Figure(figsize=(2,2), dpi=100)

    ax1 = figure1.add_subplot(221)
    ax1.plot(df1['year'], df1['personal'], color='red')
    scatter1 = FigureCanvasTkAgg(figure1, root)
    scatter1.get_tk_widget().pack()
    ax1.legend([''])
    ax1.set_xlabel('valeur de personals')
    ax1.set_title('ev de personal ')

    figure2 = plt.Figure(figsize=(2,2), dpi=100)
    ax2 = figure2.add_subplot(222)
    scatter2 = FigureCanvasTkAgg(figure2, root)
    scatter2.get_tk_widget().pack(side=tk.RIGHT)
    ax2.legend([''])
    ax2.set_xlabel('valeur BSA')
    ax2.set_title('Evolutiion des valeurs BSA depuis 1990 ')
    ax2.plot(df2['year'], df2['value'], color='red')

    figure3 = plt.Figure(figsize=(2,2), dpi=100)
    ax3 = figure3.add_subplot(223)
    #the same code for the reste 


    root.mainloop()

但结果是：

Answer 1

我看到两个问题

第一名：

创建4个画布FigureCanvasTkAgg，在每个画布上使用add_subplot(222)为4个绘图（2x2）创建位置，但在每个画布中仅使用一个位置。您只能使用一个画布进行此操作

秒：

您需要pack(fill="both", expand=True)来调整绘图大小并使用窗口中的所有空间

您还可以使用pack(side=tk.RIGHT)，这会使布局出现问题

---

最小工作代码

import tkinter as tk
import pandas as pd
import matplotlib.pyplot as plt

import matplotlib
matplotlib.use("TkAgg")

from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
#from matplotlib.figure import Figure

df1 = pd.DataFrame({
    'year': [2001, 2002, 2003],
    'value': [1, 3, 2],
    'personal': [9, 1, 5],
})

df2 = pd.DataFrame({
    'year': [2001, 2002, 2003],
    'value': [1, 3, 2],
    'personal': [9, 1, 5],
})

#  - 

root = tk.Tk()

figure = plt.Figure(figsize=(2,2), dpi=100)

scatter = FigureCanvasTkAgg(figure, root)
scatter.get_tk_widget().pack() #fill='both', expand=True)

#  - 

ax1 = figure.add_subplot(221)
ax1.plot(df1['year'], df1['personal'], color='red')

ax1.legend([''])
ax1.set_xlabel('valeur de personals')
ax1.set_title('ev de personal ')

#  - 

ax2 = figure.add_subplot(222)
ax2.plot(df2['year'], df2['value'], color='red')

ax2.legend([''])
ax2.set_xlabel('valeur BSA')
ax2.set_title('Evolutiion des valeurs BSA depuis 1990 ')

#  - 

ax3 = figure.add_subplot(223)
ax3.plot(df1['year'], df1['personal'], color='red')

ax3.legend([''])
ax3.set_xlabel('valeur de personals')
ax3.set_title('ev de personal ')

#  - 

ax4 = figure.add_subplot(224)
ax4.plot(df2['year'], df2['value'], color='red')

ax4.legend([''])
ax4.set_xlabel('valeur BSA')
ax4.set_title('Evolutiion des valeurs BSA depuis 1990 ')

#  -

root.mainloop()

结果:

---

编辑：

与4个画布相同-每个画布使用add_plot('111')只保留一个绘图-但这次我使用grid()而不是pack()来组织它

它需要columnconfigure、rowconfigure来调整单元格大小并使用窗口中的所有空间。和grid( ..., sticky='news')将画布调整为单元格大小

import tkinter as tk
import pandas as pd
import matplotlib.pyplot as plt

import matplotlib
matplotlib.use("TkAgg")

from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
#from matplotlib.figure import Figure

df1 = pd.DataFrame({
    'year': [2001, 2002, 2003],
    'value': [1, 3, 2],
    'personal': [9, 1, 5],
})

df2 = pd.DataFrame({
    'year': [2001, 2002, 2003],
    'value': [1, 3, 2],
    'personal': [9, 1, 5],
})

#  - 

root = tk.Tk()

# resize grid
root.columnconfigure(0, weight=1)
root.columnconfigure(1, weight=1)
root.rowconfigure(0, weight=1)
root.rowconfigure(1, weight=1)

#  - 

figure1 = plt.Figure(figsize=(2,2), dpi=100)

scatter1 = FigureCanvasTkAgg(figure1, root)
scatter1.get_tk_widget().grid(row=0, column=0, sticky='news')
#scatter1.get_tk_widget().pack(fill='both', expand=True)

ax1 = figure1.add_subplot(111)
ax1.plot(df1['year'], df1['personal'], color='red')

ax1.legend([''])
ax1.set_xlabel('valeur de personals')
ax1.set_title('ev de personal ')

#  - 

figure2 = plt.Figure(figsize=(2,2), dpi=100)

scatter2 = FigureCanvasTkAgg(figure2, root)
scatter2.get_tk_widget().grid(row=0, column=1, sticky='news')
#scatter2.get_tk_widget().pack(side='right', fill='both', expand=True)

ax2 = figure2.add_subplot(111)
ax2.plot(df2['year'], df2['value'], color='red')

ax2.legend([''])
ax2.set_xlabel('valeur BSA')
ax2.set_title('Evolutiion des valeurs BSA depuis 1990 ')

#  - 

figure3 = plt.Figure(figsize=(2,2), dpi=100)

scatter3 = FigureCanvasTkAgg(figure3, root)
scatter3.get_tk_widget().grid(row=1, column=0, sticky='news')
#scatter3.get_tk_widget().pack(fill='both', expand=True)

ax3 = figure3.add_subplot(111)
ax3.plot(df1['year'], df1['personal'], color='red')

ax3.legend([''])
ax3.set_xlabel('valeur de personals')
ax3.set_title('ev de personal ')

#  - 

figure4 = plt.Figure(figsize=(2,2), dpi=100)

scatter4 = FigureCanvasTkAgg(figure4, root)
scatter4.get_tk_widget().grid(row=1, column=1, sticky='news')
#scatter4.get_tk_widget().pack(fill='both', expand=True)

ax4 = figure4.add_subplot(111)
ax4.plot(df2['year'], df2['value'], color='red')

ax4.legend([''])
ax4.set_xlabel('valeur BSA')
ax4.set_title('Evolutiion des valeurs BSA depuis 1990 ')

#  -

root.mainloop()

结果:

现在，这些地块的利润率较小