how to build interactive excel dashboard with python dash

creating an interactive excel dashboard using python dash involves several steps, including preparing your data, building the dash app, and deploying it. below is an informative tutorial that will guide you through the process.

step 1: set up your environment

first, ensure you have python installed on your machine. you will also need to install the following libraries:

- **dash**: a web application framework for python.
- **pandas**: a data manipulation library to handle data.
- **openpyxl**: a library to read/write excel files.

step 2: prepare your data

| product | sales | month |
|---------|-------|-------|
| a | 200 | jan |
| b | 150 | jan |
| a | 300 | feb |
| b | 200 | feb |

you can create this file using excel or programmatically with pandas, like so:

step 3: read data with pandas

step 4: build the dash app

now, let’s create a dash application that visualizes the data.

step 5: run the application

to run the application, execute the following command in your terminal:

step 6: interact with your dashboard

once you open the dashboard, you will see a dropdown menu to select a product. when you select a product, the bar chart will update to show the sales data for that product over the months.

step 7: deploying your dashboard (optional)

to deploy your dash app, you can use platforms like heroku, aws, or digitalocean. each platform has its own deployment procedure. here’s a brief overview of deploying on heroku:

1. install the heroku cli.
2. log in to your heroku account using `heroku login`.
3. create a new heroku app with `heroku create`.
4. add the required files:
- `procfil ...

#ExcelDashboard #PythonDash #numpy
interactive excel dashboard
Python Dash
data visualization
Excel integration
dashboard design
web applications
user interactivity
data analysis
Python programming
real-time updates
visual analytics
charting libraries
dashboard components
UI design
business intelligence