如何在Python Spyder中用Tkinter实现调用Excel关联DataFrame的均值查询弹窗

Got it, let's build this Tkinter popup step by step to meet your exact needs. Here's a complete, working implementation that loads your Excel data, creates the input/button UI, and handles the mean calculation logic:

import tkinter as tk
from tkinter import messagebox
import pandas as pd

# ----------------------
# Step 1: Load Excel Data
# ----------------------
# Map your codes to their respective Excel files
# Replace these file paths with your actual Excel locations
code_to_df = {
    "cgk": pd.read_excel("cgk_data.xlsx"),
    "ams": pd.read_excel("ams_data.xlsx"),
    # Add your other 3-4 codes and Excel paths here
}

# ----------------------
# Step 2: Mean Calculation Logic
# ----------------------
def calculate_mean():
    # Get input from the entry box and clean it up
    input_codes = entry.get().strip().lower()
    if not input_codes:
        messagebox.showwarning("Input Error", "Please enter at least one code!")
        return
    
    # Split input into individual codes (handles spaces between entries)
    codes = input_codes.split()
    result_text = ""
    
    for code in codes:
        if code in code_to_df:
            df = code_to_df[code]
            # Calculate mean for all numeric columns (adjust this for specific columns)
            mean_values = df.mean(numeric_only=True)
            # Format results for readability
            result_text += f"=== Mean values for {code.upper()} ===\n"
            result_text += mean_values.to_string() + "\n\n"
        else:
            result_text += f"⚠️ Code '{code}' not found. Skipping...\n\n"
    
    # Update the result display box
    result_box.delete(1.0, tk.END)
    result_box.insert(tk.END, result_text)

# ----------------------
# Step 3: Build the Tkinter UI
# ----------------------
# Create main window
root = tk.Tk()
root.title("DataFrame Mean Calculator")
root.geometry("600x400")  # Set initial window size

# Input section
input_label = tk.Label(root, text="Enter code(s) (e.g., cgk ams):")
input_label.pack(pady=10)

entry = tk.Entry(root, width=50)
entry.pack(pady=5)

# Mean calculation button
mean_btn = tk.Button(root, text="Mean value", command=calculate_mean, padx=10, pady=5)
mean_btn.pack(pady=10)

# Result display section
result_label = tk.Label(root, text="Calculation Results:")
result_label.pack(pady=5)

result_box = tk.Text(root, height=15, width=70)
result_box.pack(pady=5, padx=10)

# Start the Tkinter loop
root.mainloop()

• Excel File Paths: Replace the file paths in the code_to_df dictionary with your actual Excel locations. Add all 5-6 of your code-DataFrame mappings here.
• Target Columns for Mean: The current code calculates means for all numeric columns. If you need to focus on specific columns only, modify the mean line to:

  mean_values = df[["your_column1", "your_column2"]].mean()
  

  Just list the columns you want to include inside the brackets.
• UI Tweaks: Adjust the window size (geometry), button colors, or result display (e.g., use a Label instead of Text for simpler output) based on your preferences.
• Error Handling: The code already handles empty inputs and unknown codes, but you can expand this (e.g., add try/except blocks to catch Excel load errors) if needed.

1. Data Loading: When the script starts, it loads all your Excel files into DataFrames and stores them in a dictionary keyed by their codes.
2. User Input: Type one or more codes (separated by spaces) into the entry box.
3. Calculation Trigger: Clicking the "Mean value" button runs the calculate_mean function, which validates input, fetches the matching DataFrame(s), computes numeric column means, and formats the results.
4. Result Display: Results (or error messages) show up in the text box below the button for easy reading.

内容的提问来源于stack exchange，提问作者yosam