Real-Time Excel Chart Updater with Python and Watchdog

Automatically Refresh Charts When Excel Files Change

This tutorial shows you how to build a real-time Excel chart visualizer using Python, pandas, matplotlib, and watchdog.
The script detects changes in an Excel file and automatically updates a live chart without manual refresh — perfect for dashboards, live monitoring, and educational demos.

Table of Contents

Overview

This project continuously monitors an Excel file named garden_data.xlsx.
Whenever the file changes, the Python program automatically reloads it and redraws the chart.

Ideal for:

  • Real-time data logging dashboards
  • Automatically visualizing IoT or sensor data
  • Tracking and plotting financial trends in Excel

How It Works

  1. Watchdog detects when the Excel file changes.
  2. pandas loads and parses the Excel data.
  3. matplotlib renders an interactive live chart.
  4. The chart updates instantly — no need to rerun the program.

Setup Instructions

First, install the dependencies:

pip install pandas matplotlib watchdog numpy openpyxl

Next, create a file named garden_data.xlsx in the same folder.
Example sheet content:

PlantHeight
Rose30
Tulip25
Lily35

Now, you’re ready to run the script!

Core Components

1. Drawing the Chart

The draw_chart(ax) function automatically detects numeric columns from your Excel sheet and plots them.
It also handles errors gracefully if the file is missing or contains no numeric data.

def draw_chart(ax):
    ax.clear()
    try:
        xls = pd.ExcelFile(filename)
    except Exception as e:
        ax.text(0.5, 0.5, f"Error reading file:\n{e}",
                ha='center', va='center', fontsize=10)
        plt.draw()
        return

    sheet_names = xls.sheet_names
    numeric_sheets = []

    for sheet in sheet_names:
        df = pd.read_excel(xls, sheet_name=sheet)
        numeric_df = df.select_dtypes(include=[np.number])
        if not numeric_df.empty:
            numeric_sheets.append((sheet, df, numeric_df))

    if not numeric_sheets:
        ax.text(0.5, 0.5, "No numeric data found", 
                ha='center', va='center')
        plt.draw()
        return

    # Use the first numeric sheet found
    sheet, df, numeric_df = numeric_sheets[0]
    x_candidates = df.select_dtypes(
        exclude=[np.number]).columns.tolist()
    y_candidates = numeric_df.columns.tolist()

    ycol = y_candidates[0]
    xcol = x_candidates[0] if x_candidates else ycol

    try:
        ax.bar(df[xcol], df[ycol], color="steelblue")
    except Exception:
        ax.bar(range(len(df[ycol])), df[ycol],
               color="steelblue")
    ax.set_title(f"{sheet} — {ycol} vs {xcol}")
    ax.set_xlabel(xcol)
    ax.set_ylabel(ycol)
    plt.tight_layout()
    plt.draw()

2. Watching for File Changes

The Watcher class listens for file modification events using watchdog.
Whenever the Excel file changes, a flag is triggered to refresh the chart.

class Watcher(FileSystemEventHandler):
    def on_modified(self, event):
        global needs_update
        if event.src_path.endswith(filename):
            needs_update = True

3. Main Loop

The main loop runs continuously with plt.ion() (interactive mode).
It checks for updates and redraws the chart automatically.

if __name__ == "__main__":
    plt.ion()
    fig, ax = plt.subplots(figsize=(4, 3))
    event_handler = Watcher()
    observer = Observer()
    observer.schedule(event_handler, ".", recursive=False)
    observer.start()
    print(f"Watching '{filename}'... (Ctrl+C to stop)")

    try:
        while True:
            if needs_update:
                print("Excel refreshing chart...")
                draw_chart(ax)
                needs_update = False
            plt.pause(0.01)
    except KeyboardInterrupt:
        observer.stop()
    observer.join()

Complete Code

Here’s the entire script in one block:

import pandas as pd
import matplotlib.pyplot as plt
from watchdog.observers import Observer
from watchdog.events import FileSystemEventHandler
import numpy as np

filename = "garden_data.xlsx"
needs_update = True

def draw_chart(ax):
    ax.clear()
    try:
        xls = pd.ExcelFile(filename)
    except Exception as e:
        ax.text(0.5, 0.5, f"Error reading file:\n{e}",
                ha='center', va='center', fontsize=10)
        plt.draw()
        return

    sheet_names = xls.sheet_names
    numeric_sheets = []

    for sheet in sheet_names:
        df = pd.read_excel(xls, sheet_name=sheet)
        numeric_df = df.select_dtypes(include=[np.number])
        if not numeric_df.empty:
            numeric_sheets.append((sheet, df, numeric_df))

    if not numeric_sheets:
        ax.text(0.5, 0.5, "No numeric data found", 
                ha='center', va='center')
        plt.draw()
        return

    # Use the first numeric sheet found
    sheet, df, numeric_df = numeric_sheets[0]
    x_candidates = df.select_dtypes(
        exclude=[np.number]).columns.tolist()
    y_candidates = numeric_df.columns.tolist()

    ycol = y_candidates[0]
    xcol = x_candidates[0] if x_candidates else ycol

    try:
        ax.bar(df[xcol], df[ycol], color="steelblue")
    except Exception:
        ax.bar(range(len(df[ycol])), df[ycol],
               color="steelblue")
    ax.set_title(f"{sheet} — {ycol} vs {xcol}")
    ax.set_xlabel(xcol)
    ax.set_ylabel(ycol)
    plt.tight_layout()
    plt.draw()


class Watcher(FileSystemEventHandler):
    def on_modified(self, event):
        global needs_update
        if event.src_path.endswith(filename):
            needs_update = True


if __name__ == "__main__":
    plt.ion()
    fig, ax = plt.subplots(figsize=(4, 3))
    event_handler = Watcher()
    observer = Observer()
    observer.schedule(event_handler, ".", recursive=False)
    observer.start()
    print(f"Watching '{filename}'... (Ctrl+C to stop)")

    try:
        while True:
            if needs_update:
                print("Excel refreshing chart...")
                draw_chart(ax)
                needs_update = False
            plt.pause(0.01)
    except KeyboardInterrupt:
        observer.stop()
    observer.join()

How to Run

  1. Save the above script as excel_chart_watcher.py
  2. Place garden_data.xlsx in the same directory
  3. Run:
python excel_chart_watcher.py

Make any edits to the Excel file — and watch your chart refresh instantly! ⚡

Key Learnings

  • Real-time file watching with watchdog
  • Automated Excel parsing with pandas
  • Smart detection of numeric vs non-numeric columns
  • Live visualization using matplotlib

Further Ideas

  • Display multiple charts (for each sheet)
  • Add filtering or smoothing for better clarity
  • Save charts as images automatically
  • Integrate with Tkinter or Streamlit for dashboards

You’ve built a live Excel chart updater in Python!
Perfect for automation, teaching, and data monitoring projects.