Introduction to dash plotly for building python data apps

# introduction to dash by plotly

dash is a powerful web application framework for python, created by plotly. it is designed for building interactive web applications, particularly those that visualize data. dash is built on top of flask, plotly, and react, which allows users to create complex web applications with minimal effort and a high degree of customization.

in this tutorial, we'll cover the basics of dash, how to set it up, and create a simple interactive data visualization app.

## setting up dash

### installation

to get started, you need to install dash. you can do this using pip:

### basic structure of a dash app

a dash application typically consists of two main components:

1. **layout:** this defines the structure of your app, specifying how different components (like graphs, dropdowns, sliders, etc.) are arranged.
2. **callbacks:** these are functions that define how the app should respond to user inputs or interactions.

### example: building a simple dash app

in this example, we'll create a simple dash app that displays a scatter plot of the famous iris dataset. users will be able to select which features to plot on each axis.

#### step 1: import libraries

first, we need to import the necessary libraries:

#### step 2: load the data

next, we will load the iris dataset using pandas:

#### step 3: initialize the dash app

now, we will initialize the dash app:

#### step 4: define the layout

next, we define the layout of the app. we'll include a dropdown for selecting features and a graph for displaying the scatter plot:

#### step 5: define callbacks

now we need to set up the callbacks that will update the scatter plot based on user input from the dropdowns:

#### step 6: run the app

finally, we run the app:

### complete code

here’s the complete code for the dash app:

### running the app

open a web browser and go to `http: ...

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