Fortune Global 2000 in 2021

INTRODUCTION

A detailed analysis project based on the top 2000 global companies in 2021. It focuses on countries, profit to sales and assets. The project uses Pandas, Numpy and Matplotlib.

The dataset used is a list of the fortune 2000 companies globally with results from 2021.

• The dataset is courtesy of Kaggle:

https://www.kaggle.com/shivamb/fortune-global-2000-companies-till-2021/version/1

• The questions answered in this project focus on 3 areas of interest

1. Countries - which countries appear most in the list for various metrics such as number of companies on the list, top 20 for average profit per company and more.
2. Profit to Sales - which of the top companies have the best profit to sales ratio?
3. Assets - which companies have the most assets?

FEATURES

1. Defining business questions - (1-business-questions.ipynb)
2. Extract the data and check column info, spelling errors, column formats, tidy columns and find and replace errors and any null or NaN values - (2-extract-and-clean-data.ipynb)
3. Transforming the data by creating functions to convert string representation to integers and create new columns from existing data - (3.transform-the-data)
4. Creating visualizations using matplotlib - (4-visualizations.ipynb)

TOOLS

Pandas Matplotlib Numpy

GETTING STARTED

If you are new to Pandas or Python

1. Set up Jupyter notebooks (see below)
2. Work through the examples step by step.

New to Pandas

1. Make sure you learn Python and SQL basics before Pandas (my recommendation)
2. This pandas intro course is useful - https://www.youtube.com/watch?v=WcDaZ67TVRo&t=7270s

Pandas docs: https://pandas.pydata.org/pandas-docs/stable/index.html

Matplotlib docs: https://matplotlib.org/stable/tutorials/index.html

Setting up Jupyter Notebooks

Jupyter notebooks and other useful tools can be downloaded with an Anaconda package:

https://www.anaconda.com/

Check out more at the Jupyter notebook docs:

https://docs.jupyter.org/en/latest/