I am using the following code to plot a bar chart:
df.groupby(['Borrow_Rank'])['Outcome'].mean().plot(kind = 'bar')
This is showing the mean of the Outcome variable that ranges from 0-1. However, I need the bar chart to also show how many instances or rows are in each group (2000-5000 in each group).
How you want the data displayed is unclear, but you could use several aggregation functions:
df.groupby(['Borrow_Rank'])['Outcome'].agg(['mean', 'count']).plot.bar()
output:
Other option, annotate the counts as text:
g = df.groupby(['Borrow_Rank'])['Outcome']
s = g.mean()
ax = s.plot.bar()
for x, (y, count) in enumerate(zip(s, g.count())):
ax.annotate(f'n = {count}', (x, y), ha='center', va='bottom')
output:
reproducible dummy input:
df = pd.DataFrame({'Borrow_Rank': list('AABABACC'), 'Outcome': range(8)})