How to add data labels to seaborn barplot?

Question

I have the following code to produce a bar plot in seaborn

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

df = pd.DataFrame(np.random.randint(0,100,size=(100, 4)), columns=list('ABCD'))
print(df):
    A   B   C   D
0   15  21  13   5
1   14  94  99  14
2   11  11  13  69
3   27  90  37   6
4   51  93  92  24
..  ..  ..  ..  ..
95  45  40  85  62
96  44  48  61  43
97  39  66  72  72
98  51  97  17  32
99  51  42  29  15


probbins = [0,10,20,30,40,50,60,70,80,90,100]
df['Groups'] = pd.cut(df['D'],bins=probbins)
plt.figure(figsize=(15,6))
chart = sns.barplot(x=df['Groups'], y=df['C'],estimator=sum,ci=None)
chart.set_title('Profit/Loss')
chart.set_xticklabels(chart.get_xticklabels(), rotation=30)
plt.show()

Which gives me:

How can I simply add data labels to this plot? Any help would be much appreciated!

Answer 1

As of matplotlib 3.4.0, we can now annotate bars with the new Axes.bar_label.

In OP's code, chart is an Axes object, so we can just use:

chart = sns.barplot(data=df, x='Groups', y='C', estimator=sum, ci=None)

# new helper method to auto-label bars (matplotlib 3.4.0+)
chart.bar_label(chart.containers[0])

Note that a grouped bar chart (with hue) would have multiple bar containers, so in that case containers would need to be iterated:

for container in chart.containers:
    chart.bar_label(container)

Answer 2

For those intersted in how I solved it:

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

df = pd.DataFrame(np.random.randint(0,100,size=(100, 4)), columns=list('ABCD'))
print(df):
    A   B   C   D
0   31  11  65  15
1   83  21   5  87
2   16   6  81  41
3   91  78  95  70
4   26  51  26  61
..  ..  ..  ..  ..
95  31  18  91  24
96  73  97  42  45
97  76  22   2  36
98  12  43  98  27
99  33  96  67  68


probbins = [0,10,20,30,40,50,60,70,80,90,100]
df['Groups'] = pd.cut(df['D'],bins=probbins)
plt.figure(figsize=(15,6))
chart = sns.barplot(x=df['Groups'], y=df['C'],estimator=sum,ci=None)
chart.set_title('Profit/Loss')
chart.set_xticklabels(chart.get_xticklabels(), rotation=30)
# annotation here
for p in chart.patches:
             chart.annotate("%.0f" % p.get_height(), (p.get_x() + p.get_width() / 2., p.get_height()),
                 ha='center', va='center', fontsize=10, color='black', xytext=(0, 5),
                 textcoords='offset points')
plt.show()