k means

1import tkinter as tk
2from tkinter import filedialog
3import pandas as pd
4from pandas import DataFrame
5import matplotlib.pyplot as plt
6from sklearn.cluster import KMeans
7from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
8
9root= tk.Tk()
10
11canvas1 = tk.Canvas(root, width = 400, height = 300,  relief = 'raised')
12canvas1.pack()
13
14label1 = tk.Label(root, text='k-Means Clustering')
15label1.config(font=('helvetica', 14))
16canvas1.create_window(200, 25, window=label1)
17
18label2 = tk.Label(root, text='Type Number of Clusters:')
19label2.config(font=('helvetica', 8))
20canvas1.create_window(200, 120, window=label2)
21
22entry1 = tk.Entry (root) 
23canvas1.create_window(200, 140, window=entry1)
24
25def getExcel ():
26    
27    global df
28    import_file_path = filedialog.askopenfilename()
29    read_file = pd.read_excel (import_file_path)
30    df = DataFrame(read_file,columns=['x','y'])  
31    
32browseButtonExcel = tk.Button(text=" Import Excel File ", command=getExcel, bg='green', fg='white', font=('helvetica', 10, 'bold'))
33canvas1.create_window(200, 70, window=browseButtonExcel)
34
35def getKMeans ():
36    global df
37    global numberOfClusters
38    numberOfClusters = int(entry1.get())
39    
40    kmeans = KMeans(n_clusters=numberOfClusters).fit(df)
41    centroids = kmeans.cluster_centers_
42    
43    label3 = tk.Label(root, text= centroids)
44    canvas1.create_window(200, 250, window=label3)
45    
46    figure1 = plt.Figure(figsize=(4,3), dpi=100)
47    ax1 = figure1.add_subplot(111)
48    ax1.scatter(df['x'], df['y'], c= kmeans.labels_.astype(float), s=50, alpha=0.5)
49    ax1.scatter(centroids[:, 0], centroids[:, 1], c='red', s=50)
50    scatter1 = FigureCanvasTkAgg(figure1, root) 
51    scatter1.get_tk_widget().pack(side=tk.RIGHT, fill=tk.BOTH)
52    
53processButton = tk.Button(text=' Process k-Means ', command=getKMeans, bg='brown', fg='white', font=('helvetica', 10, 'bold'))
54canvas1.create_window(200, 170, window=processButton)
55
56root.mainloop()
57