Heart Disease prediction , Frame Wrok.ipynb

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    "#4ok done\n",
    "import tkinter as tk\n",
    "from tkinter import ttk\n",
    "from tkinter.scrolledtext import ScrolledText  # Import ScrolledText for a scrollable text widget\n",
    "import pandas as pd\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "\n",
    "# Function to predict target\n",
    "def predict_target():\n",
    "    # Get input values from entry widgets\n",
    "    input_data = {}\n",
    "    for column, entry in input_fields.items():\n",
    "        input_data[column] = float(entry.get())\n",
    "\n",
    "    # Preprocess data\n",
    "    X = data.drop(\"target\", axis=1)\n",
    "    y = data[\"target\"]\n",
    "    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
    "    scaler = StandardScaler()\n",
    "    X_train_scaled = scaler.fit_transform(X_train)\n",
    "    X_test_scaled = scaler.transform(X_test)\n",
    "\n",
    "    # Train logistic regression model\n",
    "    model = LogisticRegression()\n",
    "    model.fit(X_train_scaled, y_train)\n",
    "\n",
    "    # Prepare input data for prediction\n",
    "    input_df = pd.DataFrame([input_data])\n",
    "    input_scaled = scaler.transform(input_df)\n",
    "\n",
    "    # Predict target using logistic regression model\n",
    "    prediction = model.predict(input_scaled)[0]\n",
    "\n",
    "    # Display prediction in sticky note\n",
    "    sticky_text.insert(tk.END, f\"Predicted Target (0-->Healthy heart, 1--> Defective Heart): {prediction}\\n\")\n",
    "    sticky_text.see(tk.END)  # Scroll to the bottom\n",
    "\n",
    "\n",
    "# Function to exit the application\n",
    "def exit_application():\n",
    "    root.destroy()\n",
    "\n",
    "\n",
    "# Function to clear input fields and sticky note text\n",
    "def clear_fields():\n",
    "    for entry in input_fields.values():\n",
    "        entry.delete(0, tk.END)  # Clear entry fields\n",
    "    sticky_text.delete(1.0, tk.END)  # Clear sticky note text\n",
    "\n",
    "\n",
    "# Creating tkinter window with fixed geometry\n",
    "\n",
    "# Load data\n",
    "data = pd.read_csv(r\"C:\\Users\\Vignesh\\Desktop\\data sets\\heart_disease_data.csv\")\n",
    "\n",
    "# Create main window\n",
    "root = tk.Tk()\n",
    "\n",
    "root.title(\"Heart Disease Prediction\")\n",
    "root.geometry(\"800x900\")\n",
    "root.iconbitmap(r\"C:\\Users\\Vignesh\\Pictures\\ico.ico\")\n",
    "\n",
    "\n",
    "# Load the image\n",
    "image_path = r\"C:\\Users\\Vignesh\\Pictures\\peakpxy.png\"\n",
    "bg_image = tk.PhotoImage(file=image_path)\n",
    "\n",
    "# Keep a reference to the image to prevent garbage collection\n",
    "root.bg_image = bg_image\n",
    "\n",
    "# Create a Label with the image\n",
    "bg_label = tk.Label(root, image=root.bg_image)\n",
    "bg_label.place(x=0, y=0, relwidth=1, relheight=1)\n",
    "\n",
    "\n",
    "# Create a labeled box for the text\n",
    "text_frame = tk.LabelFrame(root, text=\"Explanation\", padx=10, pady=10)\n",
    "text_frame.place(relx=0.01, rely=0.05, relwidth=0.40, relheight=0.8)\n",
    "\n",
    "# Add text to the labeled box\n",
    "explanation_text =\"\"\"1) age: age in years\n",
    "\n",
    "2)sex: ,1 = male,0 = female\n",
    "      \n",
    "3)cp: chest pain type,Value 0: typical angina,Value 1: atypical angina,\n",
    "Value 2: non-anginal pain,Value 3: asymptomatic\n",
    "\n",
    "4)trestbps: resting blood pressure (in mm Hg on admission to the hospital)\n",
    "5)chol: serum cholestoral in mg/dl\n",
    "6)fbs: (fasting blood sugar > 120 mg/dl),1 = true,0 = false\n",
    "\n",
    "7)restecg:  resting electrocardiographic results,Value 0: normal\n",
    "Value 1:  (T wave inversions and/or ST elevation or depression of > 0.05 mV)\n",
    "Value 2: showing probable or definite left ventricular hypertrophy by Estes' criteria\n",
    "\n",
    "8)thalach: maximum heart rate achieved\n",
    "\n",
    "9)exang: exercise induced angina,1 = yes,0 = no\n",
    "\n",
    "10)oldpeak = ST depression induced by exercise relative to rest\n",
    "\n",
    "11)slope:the slope of the peak exercise ST segment\n",
    "Value 0: upsloping,Value 1: flat,Value 2: downsloping\n",
    "\n",
    "12)ca: number of major vessels (0-3) colored by flourosopy\n",
    "\n",
    "13)thal:,0 = error (in the original dataset 0 maps to NaN's),1 = fixed defect\n",
    ",2 = normal,3 = reversable defect\n",
    "\n",
    "14)target(the label): 0=no diseas, 1=disease\"\"\"\n",
    "explanation_label = tk.Label(text_frame, text=explanation_text, justify='left', anchor='w')\n",
    "explanation_label.pack(fill='both', expand=True)\n",
    "\n",
    "# Create a sticky note-like widget on the right side\n",
    "sticky_note = tk.Frame(root, bg='#f8e5e5', bd=2, relief='groove')\n",
    "sticky_note.place(relx=0.60, rely=0.05, relwidth=0.40, relheight=0.5)\n",
    "\n",
    "# Add a text widget to the sticky note for user interaction\n",
    "sticky_text = ScrolledText(sticky_note, wrap=tk.WORD, bg='#f8e5e5', bd=0, font=('Arial', 12))\n",
    "sticky_text.pack(fill='both', expand=True)\n",
    "\n",
    "# Create labels and entry fields for each feature\n",
    "input_fields = {}\n",
    "for column in data.columns:\n",
    "    if column != \"target\":  # Exclude the target column\n",
    "        label = ttk.Label(root, text=column)\n",
    "        label.pack()\n",
    "        entry = ttk.Entry(root)\n",
    "        entry.pack()\n",
    "        input_fields[column] = entry\n",
    "\n",
    "\n",
    "# Prediction button\n",
    "predict_button = tk.Button(root, text=\"SUBMIT\", bg='LIGHT BLUE', command=predict_target)\n",
    "predict_button.pack()\n",
    "\n",
    "# Clear button\n",
    "clear_button = tk.Button(root, text=\"CLEAR\", bg='Green', command=clear_fields)\n",
    "clear_button.pack()\n",
    "\n",
    "# Exit button\n",
    "exit_button = tk.Button(root, text=\"EXIT\", bg='Red', command=exit_application)\n",
    "exit_button.pack()\n",
    "\n",
    "\n",
    "\n",
    "# Run the application\n",
    "root.mainloop()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5434805b",
   "metadata": {},
   "outputs": [],
   "source": [
    "def predict_target():\n",
    "    input_data = {}\n",
    "    for column, entry in input_fields.items():\n",
    "        input_value = entry.get()\n",
    "        if input_value.strip():  # Check if input is not empty\n",
    "            try:\n",
    "                input_data[column] = float(input_value)\n",
    "            except ValueError:\n",
    "                tk.messagebox.showerror(\"Error\", f\"Invalid input for {column}: {input_value}\")\n",
    "                return\n",
    "        else:\n",
    "            tk.messagebox.showerror(\"Error\", f\"Please enter a value for {column}\")\n",
    "            return\n",
    "    \n",
    "    # Perform prediction based on input values\n",
    "    # This is just a placeholder, you need to replace it with your actual prediction code\n",
    "    predicted_target = \"Replace this with actual prediction\"\n",
    "    \n",
    "    # Display the predicted target in a message box\n",
    "    tk.messagebox.showinfo(\"Prediction\", f\"The predicted target is: {predicted_target}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b3d815e8",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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