Flight-Delay-Time-Statistics-Dashboard-Using-Dash-With-Python

Objectives

After completing the lab you will be able to:

• Know how to add multiple graphs to the dashboard
• Work with Dash Callbacks to handle multiple outputs

Theme

Analyze flight delays in a dashboard.

Dashboard Components

• Monthly average carrier delay by reporting airline for the given year.
• Monthly average weather delay by reporting airline for the given year.
• Monthly average national air system delay by reporting airline for the given year.
• Monthly average security delay by reporting airline for the given year.
• Monthly average late aircraft delay by reporting airline for the given year.

NOTE: Year range should be between 2010 and 2020

Expected Output

Below is the expected result from the lab. Our dashboard application consists of three components:

• Title of the application

• Component to enter input year

• 5 Charts conveying the different types of flight delay. Chart section is divided into three segments.

    * Carrier and Weather delay in the first segment
    
    * National air system and Security delay in the second segment
    
    * Late aircraft delay in the third segment
  

Later in the browser address bar use this:

http://localhost:8090

Airline Reporting Carrier On-Time Performance Dataset

The Reporting Carrier On-Time Performance Dataset contains information on approximately 200 million domestic US flights reported to the United States Bureau of Transportation Statistics. The dataset contains basic information about each flight (such as date, time, departure airport, arrival airport) and, if applicable, the amount of time the flight was delayed and information about the reason for the delay. This dataset can be used to predict the likelihood of a flight arriving on time.

Preview data, dataset metadata, and data glossary here.