Excel Data Viz PAA, Don - Plan

Date: 2025 02-February 25

My boss has a Excel sheet in which he does data visualization. His workflow is labor intensive and non-optimal, with plenty of opportunity for automation. I would like to use Python to speed up the generation of graphs, though he wants to keep using Excel, to allow for the addition of custom details.

Combining Python with Excel can be a powerful solution to automate tasks while still allowing for the customization your boss desires. Here’s how you can approach this:

1. Automate Data Processing and Graph Generation with Python

You can use Python to handle the heavy lifting of data processing and initial graph generation. Libraries like pandas and matplotlib (or seaborn for more advanced visualizations) are great for this.

Here's a simple example of how you can automate the process:

python

import pandas as pd
import matplotlib.pyplot as plt

# Load Excel file
df = pd.read_excel('your_data_file.xlsx')

# Process data (example: grouping data by a specific column)
processed_data = df.groupby('Category').sum()

# Generate plot
plt.figure(figsize=(10, 6))
processed_data.plot(kind='bar')
plt.title('Your Graph Title')
plt.xlabel('Category')
plt.ylabel('Values')
plt.savefig('generated_graph.png')  # Save the graph as an image file
plt.show()

2. Embed Generated Graphs Back into Excel

To keep your boss happy with using Excel, you can use openpyxl or xlsxwriter to embed the generated graphs back into the Excel sheet.

Here's a quick example:

python

from openpyxl import load_workbook
from openpyxl.drawing.image import Image

# Load the existing Excel file
workbook = load_workbook('your_data_file.xlsx')
sheet = workbook['Sheet1']

# Insert the image into the Excel sheet
img = Image('generated_graph.png')
sheet.add_image(img, 'A10')  # Place the image at cell A10

workbook.save('your_data_file_with_graph.xlsx')

3. Maintaining Flexibility

Ensure that the Excel sheet remains editable for custom details:

4. Communication with Your Boss

Explain the benefits of this approach:

5. Training and Transition

This way, you can leverage Python to automate and streamline the workflow while keeping the flexibility and customization that Excel offers.

Does this approach sound feasible? If you need further details or help with specific parts of the code, feel free to ask! 😊

Rather than embedding a png of the graph in the excel file, can I generate a native Excel plot, using Python

Absolutely! You can generate native Excel plots using Python by leveraging libraries like openpyxl along with pandas. Here’s how you can do it:

1. Install Required Libraries

Ensure you have the necessary libraries installed:

sh

pip install pandas openpyxl

2. Generate and Save Excel Plot using Python

Here's an example of how you can create a native Excel plot:

python

import pandas as pd
import openpyxl
from openpyxl.chart import BarChart, Reference

# Load your data into a pandas DataFrame
df = pd.read_excel('your_data_file.xlsx')

# Perform any data processing required
processed_data = df.groupby('Category').sum()

# Write the processed data back to a new Excel file
processed_data.to_excel('processed_data.xlsx', sheet_name='ProcessedData')

# Load the workbook and select the sheet
wb = openpyxl.load_workbook('processed_data.xlsx')
ws = wb['ProcessedData']

# Define the data for the chart
values = Reference(ws, min_col=2, min_row=2, max_col=2, max_row=len(processed_data) + 1)
categories = Reference(ws, min_col=1, min_row=2, max_row=len(processed_data) + 1)

# Create a bar chart
chart = BarChart()
chart.add_data(values)
chart.set_categories(categories)
chart.title = "Your Chart Title"
chart.x_axis.title = 'Category'
chart.y_axis.title = 'Values'

# Add the chart to the sheet
ws.add_chart(chart, 'E5')  # Position the chart at cell E5

# Save the workbook
wb.save('your_data_file_with_chart.xlsx')

Explanation:

  1. Load Data: Load your Excel data into a pandas DataFrame.

  2. Process Data: Perform any data processing required (e.g., grouping by a category).

  3. Save Processed Data: Write the processed data to a new Excel file.

  4. Load Workbook: Load the workbook using openpyxl.

  5. Define Data for Chart: Define the data range for the chart using openpyxl.chart.Reference.

  6. Create Chart: Create a bar chart (you can create other types of charts like LineChart, PieChart, etc.).

  7. Add Chart to Sheet: Add the chart to the desired position in the Excel sheet.

  8. Save Workbook: Save the workbook with the chart included.

Flexibility:

Your boss can still open the Excel file, view the generated charts, and add any custom details as needed.

This approach allows you to automate the data processing and chart generation while keeping the flexibility of manual adjustments in Excel.

Feel free to adjust the code based on your specific requirements. If you need further assistance, I'm here to help! 😊

Does this solution fit your needs?

I think so. My idea now is to use pyxll tormediate calulations. This way, if he wants to add additional data to any graph, to show a non-standard curve, he can. Also, he won't have to write any python himself, or even see it. Can a script that used openpyxl run to perform changes to a sheet that is already open?

That's a clever idea! Using PyXLL for intermediate calculations can indeed streamline the workflow while keeping everything user-friendly for your boss.

Running openpyxl with an Open Excel Sheet

Typically, openpyxl works by reading and writing to Excel files, which can be problematic if the file is currently open in Excel. When a file is open in Excel, it is often locked and cannot be accessed for writing by another process.

However, PyXLL can help here, as it integrates Python with Excel and can execute Python functions directly from Excel. This way, you avoid the issue of file locking entirely.

Using PyXLL for Calculations and Graphs

  1. Install PyXLL: Ensure you have PyXLL installed and properly configured.

  2. Define Python Functions: Use PyXLL to define Python functions that can be called directly from Excel cells for calculations and graph generation.

Here's a simple example to get you started:

python

# Add this to your pyxll.cfg file:
# [PYXLL]
# pythonpath = path/to/your/python/files

from pyxll import xl_func, xl_macro
import pandas as pd
import openpyxl
from openpyxl.chart import BarChart, Reference

@xl_func
def generate_chart(filename, sheetname):
    # Load the workbook and select the sheet
    wb = openpyxl.load_workbook(filename)
    ws = wb[sheetname]

    # Define the data for the chart (update the range as needed)
    values = Reference(ws, min_col=2, min_row=2, max_col=2, max_row=ws.max_row)
    categories = Reference(ws, min_col=1, min_row=2, max_row=ws.max_row)

    # Create a bar chart
    chart = BarChart()
    chart.add_data(values)
    chart.set_categories(categories)
    chart.title = "Your Chart Title"
    chart.x_axis.title = 'Category'
    chart.y_axis.title = 'Values'

    # Add the chart to the sheet
    ws.add_chart(chart, 'E5')  # Position the chart at cell E5

    # Save the workbook
    wb.save(filename)

    return "Chart created successfully!"

Workflow:

  1. Intermediate Calculations:

    • Use PyXLL to call Python functions for intermediate calculations directly from Excel cells.

    • This way, your boss can add custom data and see the results instantly without needing to run any Python scripts manually.

  2. Graph Generation:

    • Use PyXLL to call a Python function for generating and inserting graphs into the Excel sheet.

    • Ensure the function handles the data range dynamically to accommodate any added custom data.

Example Excel Workflow:

By using PyXLL, you ensure the Python functions are seamlessly integrated into Excel, allowing your boss to add custom details and see real-time updates without worrying about running Python scripts separately.

Does this approach align with your goals? If you need further customization or have more questions, I'm here to help! 😊

Will my boss need pyxll installed on his system?

Yes, your boss will need PyXLL installed on his system to run the Python functions directly from Excel. Here’s how you can ensure a smooth setup:

1. PyXLL Installation

Provide your boss with instructions to install PyXLL:

  1. Download PyXLL: Visit the PyXLL website and download the appropriate version for your boss’s system.

  2. Install PyXLL: Follow the installation instructions provided on the PyXLL website. This typically involves running an installer and following the prompts.

  3. Configure PyXLL: Ensure that the pyxll.cfg configuration file is set up correctly, specifying the paths to your Python scripts.

2. Setting Up Your Python Environment

Make sure your boss’s Python environment is set up with the necessary libraries:

  1. Install Required Libraries:

    sh

    pip install pandas openpyxl

  2. Provide Python Scripts: Share the Python scripts you’ve created for intermediate calculations and chart generation.

3. Using PyXLL Functions in Excel

Provide a brief guide on how to use the PyXLL functions in Excel:

  1. Call Functions: Explain how to call the Python functions from Excel cells using the PyXLL add-in.

  2. Run Macros: If you’ve created any macros for more complex tasks, show how to run them.

Simplified Guide for Your Boss

Create a simplified guide or cheat sheet for your boss, covering the following:

By ensuring that your boss has PyXLL installed and providing clear instructions, you can streamline the workflow and make it easier for him to use the automated processes you’ve set up without needing to interact with the underlying Python code.

Does this approach sound good? If you need help with any specific part of the setup, let me know! 😊