Add ONLY the total values on top of stacked bars

Question

I am working with the following bar plot:

And I would like to add only the total amount of each index on top of the bars, like this:

However, when I use the following code, I only get parts of the stacks of each bar.

import matplotlib.pyplot as plt

data = [['0.01 - 0.1','A'],['0.1 - 0.5','B'],['0.5 - 1.0','B'],['0.01 - 0.1','C'],['> 2.5','A'],['1.0 - 2.5','A'],['> 2.5','A']]

df = pd.DataFrame(data, columns = ['Size','Index'])

### plot

df_new = df.sort_values(['Index'])

list_of_colors_element = ['green','blue','yellow','red','purple']

# Draw
piv = df_new.assign(dummy=1) \
            .pivot_table('dummy', 'Index', 'Size', aggfunc='count', fill_value=0) \
            .rename_axis(columns=None)
ax = piv.plot.bar(stacked=True, color=list_of_colors_element, rot=0, width=1)

ax.bar_label(ax.containers[0],fontsize=9)

# Decorations
plt.title("Index coloured by size", fontsize=22)
plt.ylabel('Amount')
plt.xlabel('Index')
plt.grid(color='black', linestyle='--', linewidth=0.4)
plt.xticks(range(3),fontsize=15)
plt.yticks(fontsize=15)

plt.show()

I have tried with different varieties of ax.bar_label(ax.containers[0],fontsize=9) but none displays the total of the bars.

Answer 1

As Trenton points out, bar_label is usable only if the topmost segment is never zero (i.e., exists in every stack) but otherwise not. Here are examples of the two cases.

---

If the topmost segment is never zero, use bar_label

In this example, the topmost segment (purple '>2.5') exists for all A, B, and C, so we can just use ax.bar_label(ax.containers[-1]):

df = pd.DataFrame({'Index': [*'AAAABBCBC'], 'Size': ['0.01-0.1', '>2.5', '1.0-2.5', '>2.5', '0.1-0.5', '0.5-1.0', '0.01-0.1', '>2.5', '>2.5']})
piv = pd.crosstab(df['Index'], df['Size'])
ax = piv.plot.bar(stacked=True)

# auto label since none of the topmost segments are missing
ax.bar_label(ax.containers[-1])

---

Otherwise, sum and label manually

In OP's example, the topmost segment (purple '>2.5') does not always exist (missing for B and C), so the totals need to be summed manually.

How to compute the totals will depend on your specific dataframe. In OP's case, A, B, and C are rows, so the totals should be computed as sum(axis=1):

df = pd.DataFrame({'Index': [*'AAAABBC'], 'Size': ['0.01-0.1', '>2.5', '1.0-2.5', '>2.5', '0.1-0.5', '0.5-1.0', '0.01-0.1']})
piv = pd.crosstab(df['Index'], df['Size'])
ax = piv.plot.bar(stacked=True)

# manually sum and label since some topmost segments are missing
for x, y in enumerate(piv.sum(axis=1)):
    ax.annotate(y, (x, y+0.1), ha='center')