Exploring Unicorn Companies: An Analysis of Growth and Trends
In this project, I explored a dataset of unicorn companies—privately held startups valued at over one billion dollars—to uncover patterns in how and when companies achieve unicorn status. The dataset included key information such as company name, valuation, date joined, industry, city, country, continent, year founded, funding, and investors. Using Python and its data analysis libraries, I applied exploratory data analysis (EDA) techniques to understand trends, distributions, and relationships within the data.
The first step involved cleaning and structuring the data. I converted the Date Joined column into a datetime format, enabling time-based analyses and the creation of additional features such as Month Joined and Years To Join, which represents the number of years it took for each company to reach unicorn status. These transformations allowed for more nuanced visualizations and comparisons across time intervals.
Using subsets of the dataset for specific years, I visualized trends in the number of companies reaching unicorn status using bar plots, grouped by month and quarter. This revealed temporal patterns, such as months with higher concentrations of companies achieving unicorn valuation. I also examined the distribution of Years To Join with box plots, showing the variability in how long it took companies to reach unicorn status depending on their month of joining.
Finally, I analyzed average company valuations over quarterly intervals, allowing comparison across different years. This highlighted differences in growth patterns and provided insight into which periods experienced higher average valuations.
Overall, this project demonstrates the power of EDA in understanding business growth patterns and investment trends. By combining data cleaning, transformation, aggregation, and visualization, I was able to generate actionable insights into the timing and valuation of unicorn companies, reinforcing skills in Python programming, pandas, and data visualization while producing a clear, analytical narrative for stakeholders.