How to annotate a stackplot or area plot

Question

I was trying to plot an area graph with these values.

y1=[26.8,24.97,25.69,24.07]
y2=[21.74,19.58,20.7,21.09]
y3=[13.1,12.45,12.75,10.79]
y4=[9.38,8.18,8.79,6.75]
y5=[12.1,10.13,10.76,8.03]
y6=[4.33,3.73,3.78,3.75]

df = pd.DataFrame([y1,y2,y3,y4,y5,y6])

cumsum = df.cumsum()
cumsum

I was able to do the area part, however I don´t know how to add the specific numbers in the graph.

labels = ["Medical", "Surgical", "Physician Services", "Newborn", "Maternity", "Mental Health"]
x = [1,2,3,4]
years = [2011,2012,2013,2014]

fig, ax = plt.subplots()
plt.title("Overall, inpatient costs have decreased in 2011")
ax.stackplot(x, y1,y2,y3,y4,y5,y6, labels=labels, colors = sns.color_palette("Blues")[::-1])
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)
ax.spines['bottom'].set_visible(False)
ax.spines['left'].set_visible(False)

plt.legend(bbox_to_anchor=(1.05, 1), loc="upper left")
display()

This is the current output, but does not match the desired output

The output should look something like this.

Answer 1

You could add the following snippet at the end of your code:

for i, c in df.iteritems():
    v2 = 0
    for v in c:
        v2 += v
        ax.text(i+1, v2, f'${v:.2f}')

output:

Answer 2

I change these lines in your code:

fig, ax = plt.subplots(figsize=(10,7))
ax.stackplot(years, y1,y2,y3,y4,y5,y6, labels=labels, colors = sns.color_palette("Blues")[::-1])
plt.legend(bbox_to_anchor=(1.1, 1), loc="upper left")

And add these lines and get what you want:

df2 = df.cumsum()

for id_col, col in df2.iteritems():
    prev_val = 0
    for val in col:
        ax.annotate(text='${}'.format(round((val - prev_val),2)), xy=(years[id_col],(val)), weight='bold')        
        prev_val = val

plt.xticks(years)

Output:

Whole code:

import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns

y1=[26.8,24.97,25.69,24.07]
y2=[21.74,19.58,20.7,21.09]
y3=[13.1,12.45,12.75,10.79]
y4=[9.38,8.18,8.79,6.75]
y5=[12.1,10.13,10.76,8.03]
y6=[4.33,3.73,3.78,3.75]
labels = ["Medical", "Surgical", "Physician Services", 
          "Newborn", "Maternity", "Mental Health"]
years = [2011,2012,2013,2014]
fig, ax = plt.subplots(figsize=(10,7))
plt.title("Overall, inpatient costs have decreased in 2011", weight='bold')
ax.spines['right'].set_visible(False);ax.spines['top'].set_visible(False)
ax.spines['bottom'].set_visible(False);ax.spines['left'].set_visible(False)
ax.stackplot(years, y1,y2,y3,y4,y5,y6, labels=labels, 
             colors = sns.color_palette("Blues")[::-1])

df2 = pd.DataFrame([y1,y2,y3,y4,y5,y6]).cumsum()
for id_col, col in df2.iteritems():
    prev_val = 0
    for val in col:
        # Base Matplotlib version use `text` or `s`
        # ax.annotate(text='${}'.format(round((val - prev_val),2)),  xy=(years[id_col],(val)) , weight='bold')   
        ax.annotate(s='${}'.format(round((val - prev_val),2)),  xy=(years[id_col],(val)) , weight='bold')        

        prev_val = val

plt.xticks(years)
plt.xlabel('Year')
plt.ylabel('Cost (USD)')
plt.legend(bbox_to_anchor=(1.1, 1), loc="upper left")
plt.show()