Your First Health App
With your development environment set up, it's time to create your first healthcare app using Health Universe and Streamlit. In this tutorial, we will guide you through building a simple app that visualizes healthcare data using interactive charts.
Step 1: Prepare Your Data
For this tutorial, we'll use a sample dataset containing information about patients, such as age, gender, and health metrics. You can find a suitable dataset online or create a CSV file with the following columns: Patient_ID
, Age
, Gender
, Height
, Weight
, Blood_Pressure
, and Heart_Rate
.
Save the CSV file as patient_data.csv
in the data
directory of your project.
Step 2: Load the Data in Your App
To load the data in your app, we'll use the Pandas library. If you haven't installed Pandas, run the following command in your terminal:
Next, open app.py
in your text editor or IDE and import the Pandas library by adding the following line at the beginning of the file:
Now, modify the main()
function to load the patient data and display it as a table using Streamlit:
Save the app.py
file.
Step 3: Add Interactive Data Filtering
To allow users to filter the data based on age and gender, add the following code to the main()
function, right after displaying the data table:
This code adds interactive sliders and a dropdown menu to the sidebar, allowing users to select minimum and maximum ages and a gender. The filtered data is then displayed as a table in the main content area.
Step 4: Visualize the Data
To visualize the filtered data, we'll create a bar chart showing the average blood pressure for each age group. First, install the Plotly library by running the following command in your terminal:
Next, import the Plotly library in app.py
by adding the following line at the beginning of the file:
Now, add the following code to the main()
function, after displaying the filtered data:
This code calculates the average blood pressure for each age group, creates a bar chart using Plotly Express, and displays the chart in the main content area of the app.
Save the app.py
file.
Step 5: Run Your Healthcare App
To run your healthcare data visualization app, open the terminal, navigate to your project directory, and run the following command:
Streamlit will launch your app in your default web browser, displaying the interactive data filters and bar chart. To stop the app, press Ctrl+C
in the terminal.
Congratulations! You have successfully created your first healthcare app using Streamlit that you can deploy to Health Universe and share with the world. You can now build on this foundation to create more advanced applications, incorporating machine learning models, additional visualizations, and user interactivity.
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