Automate Your Excel Tasks Using Python
Introduction
In this post, I will show you how to create a Python-powered Excel file that can automate the extraction of specific values from multiple Excel files. This approach is particularly useful if you often need to gather data from reports and datasheets, such as total and average sales or total quantities. Let’s go through the process step-by-step.
Setting Up Your Workbook
To start, I have an Excel workbook where I will input the folder path to my Excel files. Below that, I create a table specifying which cells I want to retrieve data from. Once I click a button in the workbook, a Python script is executed, creating a new workbook that contains all the extracted values in a structured format. This structured data can be easily uploaded to a database or used for further analysis.
Integrating Python with Excel
The main goal here is to integrate Python into Excel using the xlwings package. This is different from the new Python functionality that Microsoft has introduced, which is more focused on data analysis rather than automation. To set up xlwings, first, I need to install the required packages. I will use the command line to execute the following commands:
- Install xlwings:
pip install xlwings - Install OpenPyXL: This package is needed for scraping data.
- Install pandas: This is used for transforming the data.
Creating the xlwings Project
Once the packages are installed, I will create an xlwings quickstart project. This can be done by typing:
xlwings quickstart xlscraper --standaloneThis command creates a new folder with both a Python file and an Excel file. I will then move these files next to my input folder.
Setting Up the User Interface
Next, I will open the workbook and insert a button to trigger the Python code. If you don’t have the Developer tab visible, you can enable it by right-clicking on the ribbon and selecting “Customize the Ribbon.”
Once the Developer tab is visible, I go to “Insert” and select a button to draw on my sheet. After that, I link this button to the Python function I want to execute.
Troubleshooting the Connection
If you encounter an error stating that the interpreter could not be found, you may need to check the settings sheet where you can specify the path to your Python interpreter. Simply remove the leading underscore from the settings sheet name to activate it.
Building the Data Scraper Interface
For the data scraper app, I will set the input folder path and create a table to define which cells I want to scrape. Using named ranges will make the app more robust, allowing for easier access to specific cells later on.
After defining my ranges, I will convert the relevant cell ranges into a table, which simplifies converting them to a pandas DataFrame later.
Formatting and Adding Emojis
To enhance the user interface, I will format the spreadsheet and add some fun emojis using my Excel add-in called Emojify. This add-in lets me easily insert emojis into my cells, either inside or outside the cell.
Writing the Python Code
With the user interface set up, I will switch to the Python file to write the code that will perform the data scraping. I will import the necessary libraries and prepare to read the settings from the Excel sheet. The code will load the workbook, read specified cells, and store the data in a structured format.
Executing the Data Scraping
After writing the code, I can run the entire process by clicking the button in Excel. This will execute the Python code, which collects data from the specified Excel files and saves it into a new workbook.
Upon completion, a message box will appear to notify me that the results have been saved in the output folder.
Conclusion
This guide has shown how to automate Excel tasks using Python and xlwings. By integrating Python into Excel, I can efficiently scrape data from multiple files and generate reports without manual effort. The flexibility of Excel allows me to adjust settings and parameters without needing to alter the Python code directly.
