btahir

# install packages
# pip install faiss-cpu sentence-transformers

import numpy as np
import torch
import faiss
import time
from sentence_transformers import SentenceTransformer

# https://www.sbert.net/docs/pretrained_models.html#multi-qa-models

btahir

// create an Instagram Card with Tailwind CSS and Font Awesome Icons

import { FontAwesomeIcon } from '@fortawesome/react-fontawesome'
import { faHeart, faComment, faPaperPlane, faBookmark } from '@fortawesome/free-regular-svg-icons'
import { faEllipsisH } from '@fortawesome/free-solid-svg-icons'

function InstaCard() {
  return (
    <div className="pt-20 min-h-screen">
      <div className="w-full bg-white max-w-lg shadow-sm sm:my-4 sm:rounded-sm mx-auto">

btahir

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Background

This visualization captures the flights to and from the Virginia region (Central Virginia and Washington DC) in January 2015. The reason I chose this dataset was because, around the same time when I was working on this project, I was also participating in a Data Visualization competition within my company and this dataset was provided to us. I figured this would be a great way to work on this project and test it out.

Summary

The data visualization captures all the flight paths and delay information based on airport. It categorizes the airports by color based on the most frequent cause of the delay in that airport. There is also a bar chart that summarizes the average delays for each airport (in minutes). The visualization is interactive as you can hover over which airport you want to see the information for.

Findings