https://github.com/bovem/stock-tracker

An interactive data visualization application developed in Python
https://github.com/bovem/stock-tracker

data data-analysis data-visualization iex-api plotly-dash python stock-data stock-tracker visualization

Last synced: about 3 hours ago
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An interactive data visualization application developed in Python

• Host: GitHub
• URL: https://github.com/bovem/stock-tracker
• Owner: bovem
• License: mit
• Created: 2018-07-03T06:02:33.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2021-09-05T11:19:52.000Z (over 3 years ago)
• Last Synced: 2023-03-10T01:32:01.137Z (almost 2 years ago)
• Topics: data, data-analysis, data-visualization, iex-api, plotly-dash, python, stock-data, stock-tracker, visualization
• Language: CSS
• Homepage:
• Size: 837 KB
• Stars: 10
• Watchers: 0
• Forks: 6
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        


## Project Overview

Stock Tracker is an interactive data visualization application developed in Python, with the help of [Dash](https://github.com/plotly/dash) , [yfinance](https://pypi.org/project/yfinance/) and [Pandas](https://github.com/pandas-dev/pandas)

## Features

It uses yfinance to get intraday trading data of any [NASDAQ](https://www.nasdaq.com/) listed company.  

It takes the ticker symbol of that company as input and price fluctuations till current date are plotted on an interactive graph provided by plot.ly.

Other than displaying current price, open price, high, low and volume of that stock, it also calculates percentage change of price in the last one-day interval.  

The interface is created using [Litera](https://bootswatch.com/litera/), a bootstrap theme from [Bootswatch](https://bootswatch.com/).

## Demo & Screenshot

  



## Techstack

* Python

* Dash

* Plot.ly

* Docker

* yfinance

## Setup

### Pre-requisites

Install [docker](https://www.docker.com/) and [docker-compose](https://docs.docker.com/compose/).

### Steps

1. Change directory to `docker`.

```bash

cd docker

```

2. Build docker service `stock-tracker` using docker compose.

```bash

docker-compose build

```

3. Start docker service

```bash

docker-compose up

```

4. Visit `localhost:8050` in your web browser.

## License

[MIT](LICENSE)