帮我优化一下代码 import matplotlib.pyplot as plt from matplotlib.offsetbox import OffsetImage, AnnotationBbox import pandas as pd import tkinter as tk from tkinter import filedialog import csv import numpy as np filepath = filedialog.askopenfilename() readData = pd.read_csv(filepath, encoding = 'gb2312') # 读取csv数据 print(readData) xdata = readData.iloc[:, 2].tolist() # 获取dataFrame中的第3列，并将此转换为list ydata = readData.iloc[:, 3].tolist() # 获取dataFrame中的第4列，并将此转换为list Color_map = { '0x0': 'r', '0x10': 'b', '0x20': 'pink', '0x30': 'm', '0x40': 'm', '0x50': 'm', '0x60': 'g', '0x70': 'orange', '0x80': 'orange', '0x90': 'm', '0xa0': 'b', '0xb0': 'g', '0xc0': 'g', '0xd0': 'orange', '0xe0': 'orange', '0xf0': 'orange', } plt.ion() fig = plt.figure(num = "蓝牙钥匙连接状态", figsize= (10.8,10.8),frameon= True) gs = fig.add_gridspec(1, 1) ax = fig.add_subplot(gs[0, 0]) colors = readData.iloc[:, 1].map(Color_map) plt.title("Connecting Status For Bluetooth Key") #plt.rcParams['figure.figsize']=(15, 15) ax.axis('equal') a,b = (0.,0.) r = [5,10] for r1 in r: theta = np.arange(0,r1*np.pi,0.05) ax.plot(a+r1*np.cos(theta),b+r1*np.sin(theta),linestyle='-.',c = 'darkgrey') ax.spines['bottom'].set_position(('data', 0)) ax.spines['left'].set_position(('data', 0)) ax.spines['right'].set_position(('data', 0)) ax.spines['top'].set_position(('data', 0)) arr_img = plt.imread('D:\\2022\\测试工作\\蓝牙钥匙测试\\定位\\室内定位(v3.6.21).rar-1656500746516.室内定位(v3.6.21)\\车型图2.png') imagebox = OffsetImage(arr_img, zoom=0.3) ab = AnnotationBbox(imagebox, [0, 0],xybox=(0, 0),pad=0) ax.add_artist(ab) ticks = np.arange(-10,10,2) plt.xticks(ticks) plt.yticks(ticks) #plt.figure(figsize=(15,15)) plt.scatter(xdata, ydata, s=150, edgecolors = None, linewidths=0, alpha=0.3,c = colors) # 画散点图，*:r表示点用*表示，颜色为红色 plt.legend() plt.ioff() plt.show() # 画图

import pandas as pd import csv import matplotlib.pyplot as plt import tkinter as tk from PIL import Image, ImageTk from tkinter import filedialog from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg from tkinter import Tk, Button, Text, filedialog, messagebox from sklearn.preprocessing import StandardScaler,LabelEncoder from sklearn.model_selection import train_test_split from sklearn.linear_model import LinearRegression from sklearn.tree import DecisionTreeRegressor from sklearn.ensemble import RandomForestRegressor解释每一句代码的含义

- import matplotlib.pyplot as plt: 导入matplotlib库，并使用plt作为别名，matplotlib是一个绘图库，可以用于绘制各种图形、图表等。 - import tkinter as tk: 导入tkinter库，并使用tk作为别名，tkinter是...

import io import tkinter as tk from tkinter import * from tkinter import messagebox from tkinter import font import pandas as pd from pandas import DataFrame import numpy as np import matplotlib.pyplot as plt clickable = 1 data = None row = 0 column = 0 changing_label = None changing_entry = None rroot = None addr = '' aa = 0 bb = 0 index = 0

这是一段 Python 代码，其中使用了 tkinter、pandas、numpy 和 matplotlib.pyplot 库。它定义了一些变量和函数，但没有具体的实现代码。其中 clickable 变量的作用不明确，data 变量可能是存储数据的容器，row 和 ...

import tkinter as tk import pandas as pd import matplotlib.pyplot as plt from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg import os class ExcelPlotter(tk.Frame): def init(self, master=None): super().init(master) self.master = master self.master.title("图方便") self.file_label = tk.Label(master=self, text="Excel File Path:") self.file_label.grid(row=0, column=0, sticky="w") self.file_entry = tk.Entry(master=self) self.file_entry.grid(row=0, column=1, columnspan=2, sticky="we") self.file_button = tk.Button(master=self, text="Open", command=self.open_file) self.file_button.grid(row=0, column=3, sticky="e") self.plot_button = tk.Button(master=self, text="Plot", command=self.plot_data) self.plot_button.grid(row=1, column=2, sticky="we") self.name_label = tk.Label(master=self, text="Out Image Name:") self.name_label.grid(row=2, column=0, sticky="w") self.name_entry = tk.Entry(master=self) self.name_entry.grid(row=2, column=1, columnspan=2, sticky="we") self.save_button = tk.Button(master=self, text="Save", command=self.save_image) self.save_button.grid(row=2, column=3, sticky="e") self.figure = plt.figure(figsize=(5, 4), dpi=150) self.canvas = FigureCanvasTkAgg(self.figure, master=self) self.canvas.get_tk_widget().grid(row=4, column=0, columnspan=4, sticky="we") self.pack() def open_file(self): file_path = tk.filedialog.askopenfilename(filetypes=[("Excel Files", "*.xls")]) self.file_entry.delete(0, tk.END) self.file_entry.insert(tk.END, file_path) def plot_data(self): file_path = self.file_entry.get() if os.path.exists(file_path): data = pd.read_excel(file_path) plt.plot(data['波长(nm)'], data['吸光度'], 'k') plt.xlim(300, 1000) plt.xlabel('Wavelength(nm)', fontsize=16) plt.ylabel('Abs.', fontsize=16) plt.gcf().subplots_adjust(left=0.13, top=0.91, bottom=0.16) plt.savefig('Last Fig', dpi=1000) plt.show() def save_image(self): if self.figure: file_path = tk.filedialog.asksaveasfilename(defaultextension=".png") if file_path: self.figure.savefig(file_path) root = tk.Tk() app = ExcelPlotter(master=root) app.mainloop()帮我增加一个删除当前图像的功能

import matplotlib.pyplot as plt from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg import os class ExcelPlotter(tk.Frame): def __init__(self, master=None): super().__init__(master...

import tkinter as tk import csv import pandas as pd import matplotlib.pyplot as plt from tkinter import filedialog from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg root = tk.Tk() root.title("数据科学基础") root.geometry("800x600") font = ("楷体", 16) root.option_add("*Font", font) root.configure(bg="pink") def import_csv_data(): global file_path, df, txt_data file_path = filedialog.askopenfilename() df = pd.read_csv(file_path) top_5 = df.head() txt_data.delete('1.0', tk.END) txt_data.insert(tk.END, top_5) label2 = tk.Label(root, text="请选择要显示的图像：") label2.pack(side="left") button1 = tk.Button(root, text="散点图") button1.pack(side="left") button2 = tk.Button(root, text="折线图") button2.pack(side="left") button3 = tk.Button(root, text="柱状图") button3.pack(side="left") fig_container = tk.Frame(root) fig_container.pack() def show_figure(): x = df.iloc[:, 0] y = df.iloc[:, 1] if plt.fignum_exists(1): plt.clf() # 清空画布 if button1["state"] == "normal": plt.scatter(x, y) elif button2["state"] == "normal": plt.plot(x, y) elif button3["state"] == "normal": plt.bar(x, y) canvas = FigureCanvasTkAgg(plt.gcf(), master=fig_container) canvas.draw() canvas.get_tk_widget().pack() button1.config(command=lambda: (button1.config(state="disabled"), button2.config(state="normal"), button3.config(state="normal"), show_figure())) button2.config(command=lambda: (button2.config(state="disabled"), button1.config(state="normal"), button3.config(state="normal"), show_figure())) button3.config(command=lambda: (button3.config(state="disabled"), button1.config(state="normal"), button2.config(state="normal"), show_figure())) btn_import = tk.Button(root,text="导入CSV文件",command=import_csv_data) btn_import.pack() txt_data = tk.Text(root) txt_data.pack() btn_show_figure = tk.Button(root, text="显示图像", command=lambda: (button1.config(state="normal"), button2.config(state="normal"), button3.config(state="normal"))) btn_show_figure.pack() root.mainloop()如何修改代码实现对界面右侧实现滑动上下拉动界面的功能

import matplotlib.pyplot as plt from tkinter import filedialog from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg root = tk.Tk() root.title("数据科学基础") root.geometry("800x600") ...

怎么样把import tkinter as tk import csv from tkinter import filedialog root = tk.Tk() root.title("数据科学基础") root.geometry("800x600") #修改字体 font = ("楷体", 16) root.option_add("Font", font) #修改背景颜色 root.configure(bg="pink") def import_csv_data(): global file_path file_path = filedialog.askopenfilename() # 读取CSV文件并显示在Text控件上 data = pd.read_csv(file_path) # 获取前5行数据 top_5 = data.head() # 将前5行数据插入到Text控件 #txt_data.delete('1.0'.tk.END) txt_data.insert(tk.END, top_5) #创建导入按钮和文本框 btn_import = tk.Button(root,text="导入CSV文件",command=import_csv_data) btn_import.pack() txt_data = tk.Text(root) txt_data.pack() root.mainloop()怎么样把这段代码和import pandas as pd import matplotlib.pyplot as plt from tkinter import from tkinter import filedialog from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg # 创建 Tkinter 窗口 root = Tk() # 设置窗口标题 root.title("CSV文件分析") # 创建标签 label = Label(root, text="请选择要导入的CSV文件：") label.pack() # 创建按钮 button = Button(root, text="选择文件") # 创建事件处理函数 def choose_file(): # 弹出文件选择对话框 file_path = filedialog.askopenfilename() # 读取CSV文件 df = pd.read_csv(file_path) # 创建标签 label2 = Label(root, text="请选择要显示的图像：") label2.pack() # 创建按钮 button1 = Button(root, text="散点图") button1.pack() button2 = Button(root, text="折线图") button2.pack() button3 = Button(root, text="柱状图") button3.pack() # 创建图形容器 fig_container = Frame(root) fig_container.pack() # 创建事件处理函数 def show_scatter(): # 获取数据 x = df.iloc[:, 0] y = df.iloc[:, 1] # 绘制散点图 fig = plt.figure(figsize=(4, 4)) plt.scatter(x, y) # 将图形显示在容器中 canvas = FigureCanvasTkAgg(fig, master=fig_container) canvas.draw() canvas.get_tk_widget().pack() def show_line(): # 获取数据 x = df.iloc[:, 0] y = df.iloc[:, 1] # 绘制折线图 fig = plt.figure(figsize=(4, 4)) plt.plot(x, y) # 将图形显示在容器中 canvas = FigureCanvasTkAgg(fig, master=fig_container) canvas.draw() canvas.get_tk_widget().pack() def show_bar(): # 获取数据 x = df.iloc[:, 0] y = df.iloc[:, 1] # 绘制柱状图 fig = plt.figure(figsize=(4, 4)) plt.bar(x, y) # 将图形显示在容器中 canvas = FigureCanvasTkAgg(fig, master=fig_container) canvas.draw() canvas.get_tk_widget().pack() # 绑定事件处理函数 button1.config(command=show_scatter) button2.config(command=show_line) button3.config(command=show_bar) # 绑定事件处理函数 button.config(command=choose_file) button.pack() # 运行窗口 root.mainloop()这段代码结合起来一起实现

import matplotlib.pyplot as plt from tkinter import filedialog from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg root = tk.Tk() root.title("数据科学基础") root.geometry("800x600") font...

import numpy as np import math import matplotlib.pyplot as plt import tkinter as tk import tkinter.messagebox import pandas as pd from openpyxl import load_workbook from warnings import simplefilter engine_torque = 10 i0 = 2.088 i1 = 2.928 ig = 2.929 efficiency = 0.96 Wheel_radius = 0.3059 slope = 0 #坡度单位弧度 slope_cos = math.cos(slope) slope_sin = math.sin(slope) rolling_resistance_coefficient = 0.01 air_coefficient = 0.28 face_area = 0.4 air_density = 1.2258 vehicle_speed = 0 weight = 268 step_size = 0.01 flag = 0 time = 0 vehicle_speed_plot = [] time_plot = [] def drive_force(engine_torque,i0,i1,ig,efficiency,Wheel_radius): drive_force = engine_torquei0igi1efficiency/Wheel_radius return drive_force def rolling_resistance(weight,rolling_resistance_coefficient,slope_cos): rolling_resistance = weightrolling_resistance_coefficientslope_cos return rolling_resistance def air_resistance(air_coefficient,face_area,air_density,relative_speed): air_resistance = 0.5air_coefficientface_areaair_densityrelative_speedrelative_speed return air_resistance def grade_resistance(weight,slope_sin): grade_resistance = weightslope_sin return grade_resistance while flag==0: relative_speed = vehicle_speed vehicle_acclerate = (drive_force(engine_torque,i0,i1,ig,efficiency,Wheel_radius)-rolling_resistance(weight,rolling_resistance_coefficient,slope_cos)-air_resistance(air_coefficient,face_area,air_density,relative_speed))/weight vehicle_speed = vehicle_accleratestep_size+vehicle_speed running_distance = relative_speedstep_size+0.5vehicle_accleratestep_size*step_size time = time+step_size if time == 10: flag = 1 vehicle_speed_plot.append(vehicle_speed) time_plot.append(time)

这段代码使用了多个变量和函数来计算车辆在直线道路上的行驶情况。具体来说，代码的主要功能是根据车辆的...最后，代码中使用了 numpy、math、matplotlib.pyplot、tkinter、pandas 和 openpyxl 等模块来实现各种功能。

我想把我画的pd.plotting.scatter_matrix放入tkinter窗口的frame框架

import matplotlib.pyplot as plt from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg import tkinter as tk # 创建一个示例数据集 data = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6], 'C': [7,...

table.div(table.sum(1).astype(float), axis=0).plot(kind='bar', stacked=True) tkinter 绘图

import matplotlib.pyplot as plt import pandas as pd # 创建 tkinter 窗口 root = tk.Tk() # 创建图形 fig = plt.figure() ax = fig.add_subplot(111) # 创建数据 data = pd.DataFrame({'A': [1, 2, 3], 'B': ...

import tkinter as tk from sklearn.neighbors import KNeighborsClassifier from sklearn.model_selection import train_test_split import numpy as np import pandas as pd global button1 seeds=pd.read_csv("seed2.csv",sep='\t',header=None) X = seeds.iloc[:,:7].copy() y=seeds.iloc[:,-1].copy() X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=test,random_state=random) def knn_score(k,X,y):# 构造算法对象 knn = KNeighborsClassifier(n_neighbors = k) scores = [] train_scores = [] random=NIrandom_state.get() global test_size for i in range(100): # 拆分 if random_state!="": X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=test,random_state=random) else: X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=test) # 训练 knn.fit(X_train,y_train) # 评价模型 scores.append(knn.score(X_test,y_test)) # 经验评分 train_scores.append(knn.score(X_train,y_train)) return np.array(scores).mean(),np.array(train_scores).mean() def root4(): root4=tk.Toplevel()#建立顶层控件wind root4.geometry("800x600")#设置窗口大小 root4.title("测试集与训练集划分")#设置窗口标题 label1 = tk.Label(root4, text="测试集与训练集划分", font=("Arial", 16)) label1.pack() global NIrandom_state,NItest_size NIrandom_state= tk.IntVar() tk.Label(root4, text="random_state:").place(x=50, y=50) tk.Entry(root4, textvariable=NIrandom_state).place(x=190,y=50) NItest_size= tk.IntVar() tk.Label(root4, text="用于测试的数据集比例:").place(x=50,y=110) tk.Entry(root4, textvariable=NItest_size).place(x=190,y=110) # 添加按钮 global button1 button1 = tk.Button(root4, text="运算", font=("Arial", 12),command=button_click) button1.place(x=50,y=150) global button2 button2=tk.Button(root4,text="图表展示",font=("Arial", 12),command=chart) button2.place(x=100,y=150) # 添加文本框 global text1 text1 = tk.Text(root4, width=50, height=10) text1.place(x=50,y=200) # 绑定按钮def button_click(): global test,random random=int(NIrandom_state.get()) test=float(NItest_size.get()) global button1 result_dict = {} k_list = [1,3,5,7,9,11] for k in k_list: score,train_score = knn_score(k,X,y) result_dict[k] = [score,train_score] result = pd.DataFrame(result_dict).T.copy() result.columns = ['Test','Train'] text=tk.Text(root4) text.place(x=100, y=220) text.insert("end",X_train) text.insert("end",X_text) text.insert("end",y_train) text.insert("end",y_text) text1.delete(1.0, tk.END) text1.insert(tk.END, result) import tkinter as tk from matplotlib.figure import Figure from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg from matplotlib.backend_bases import key_press_handler import matplotlib.pyplot as plt %matplotlib inline def chart(): root5= tk.Toplevel() root5.title("结果图形") fig = plt.figure() k_list = [1,3,5,7,9,11] result_dict = {} canvas = FigureCanvasTkAgg(fig, master=root5) canvas.get_tk_widget().pack() canvas.draw() global result result = pd.DataFrame(result_dict).T.copy() plt.xticks(k_list) plt.show() root4.mainloop()其中有什么问题

此外，函数 button_click() 中的 text1.insert(tk.END, result) 可能会出现异常，因为 result 是一个 pandas 数据框，而 Text 组件只能接受字符串类型的输入。需要将 result 转换为字符串类型才能插入到 ...

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import matplotlib.pyplot as plt class DataVisualizer: def __init__(self, master): self.master = master self.master.title("数据可视化系统") # 创建控件 self.file_label = tk.Label(self.master, ...

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import matplotlib.pyplot as plt # 读取CSV文件 df = pd.read_csv('data.csv') # 绘制线图 plt.plot(df['x'], df['y']) # 显示图形 plt.show() 其中，data.csv是您的数据文件名，x和y是您要绘制的两...

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import matplotlib.pyplot as plt # 从数据库中读取数据 cursor.execute("SELECT * FROM books") books = cursor.fetchall() # 转化为 pandas DataFrame df = pd.DataFrame(list(books), columns=['id', 'title', ...

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