Python Machine Learning Blueprints - Second Edition

Analyzing the data

The data types all look good now, so we'll begin our exploratory analysis by graphing the number of IPOs since 2000:

fig, ax = plt.subplots(figsize=(16,8)) 
by_year_cnt.plot(kind='bar', ax=ax, color='crimson') 
ax.legend(['Ticker Count']) 
ax.set_title('IPO Count by Year', fontdict={'size': 18}, y=1.02); 

The preceding code generates the following output:

From the chart, we can see that most years have over 100 IPOs, but that in the years after and including 2001 and 2008, there was a notable reduction, mostly likely due to the aftermath of 9/11 and the financial crisis.