/Unicorns

Analysis of All Unicorn Companies around the world in 2022, the information include the Value, Industry and Country. US $1 Billion or more as a Unicorn, US $10 Billion as a Decacorn, US $100 Billion as a Hectatorn.

Primary LanguageJupyter NotebookMIT LicenseMIT

Table of Content

Interactive-Unicorns-Dashboard

  • Scatter Plot Graph by Country (Comparison by years 2011-2022)
  • Bubble Graph by Industry (Acumulate Value by Industry)
  • Box Plot Graph (Comparison)
  • Map Visualization of Unicorn Companies
  • Investor Analysis (Funds, Countries)
  • Buble Map with Animation (During Years, by Cities)
  • See all the graphs in the link Streamlit app

Definition

The term “unicorn” was first coined in 2013 by Aileen Lee, the founder of Cowboy Ventures, a US-based seed-stage venture capital firm. In a TechCrunch article Welcome to The Unicorn Club: Learning from Billion-Dollar Startups (2013), she named a startup company valued at US $1 Billion or more as a unicorn. Article-Jan,2023

Description

A work of building an interactive dashboard to provide insights about Unicorn Companies globally by Master in Digital Sciences from the Digital Sciences Track of Université Paris Cité.

Datasets

Columns in the datasets:

  • unicorns: the name of the company
  • ranking_companies = ranking of companies by market value
  • date_joined = official start of each company
  • country = country
  • city = city
  • industry = industry category
  • selected_investros = funds that invested in the company
  • value = company value in trillions of dollars
  • lat = latitude
  • lng = longitude
  • capital = city type category ("primary" = country capital, "admin" = regional capital, "minor"= metropolitan city, "" = city)
  • population= population of the city.
  • id_city = international identification number of the city.

Installation Requirements

  • Install the project dependencies run pip install -r requirements.txt
pip install -r requirements.txt
  • Requirements includes:
pandas == 1.5.3
streamlit==1.19.0
plotly.express==0.4.0
altair==4.2.2 
numpy==1.23.1
pydeck==0.7.1
folium==0.14.0

To run the streamlit code

streamlit run exercise.py

Licensing

License: MIT

Authors: