How to annotate grouped bars with group count instead of bar height

Question

To draw plot, I am using seaborn and below is my code

import seaborn as sns

sns.set_theme(style="whitegrid")

tips = sns.load_dataset("tips")
tips=tips.head()
ax = sns.barplot(x="day", y="total_bill",hue="sex", data=tips, palette="tab20_r")

I want to get and print frequency of data plots that is no. of times it occurred and below is the expected image

To Add label in bar, I have used below code

for rect in ax.patches:
    y_value = rect.get_height()
    x_value = rect.get_x() + rect.get_width() / 2
    space = 1
    label = "{:.0f}".format(y_value)
    ax.annotate(label, (x_value, y_value), xytext=(0, space), textcoords="offset points", ha='center', va='bottom')
plt.show()

So, With above code. I am able to display height with respect to x-axis , but I don't want height. I want frequency/count that satisfies relationship. For above example, there are 2 male and 3 female who gave tip on Sunday. So it should display 2 and 3 and not the amount of tip

Below is the code

import seaborn as sns
import matplotlib.pyplot as plt

sns.set_theme(style="whitegrid")

df = sns.load_dataset("tips")
ax = sns.barplot(x='day', y='tip',hue="sex", data=df, palette="tab20_r")

for rect in ax.patches:
    y_value = rect.get_height()
    x_value = rect.get_x() + rect.get_width() / 2
    space = 1
    label = "{:.0f}".format(y_value)
    ax.annotate(label, (x_value, y_value), xytext=(0, space), textcoords="offset points", ha='center', va='bottom')
plt.show()

Trenton McKinney · Answer 1 · 2022-11-22T21:26:38.127

How to display custom values on a bar plot does not clearly show how to annotate grouped bars, nor does it show how to determine the frequency of each hue category for each day.
How to plot and annotate grouped bars in seaborn / matplotlib shows how to annotate grouped bars, but not with custom labels.
for rect in ax.patches is an obsolete way to annotate bars. Use matplotlib.pyplot.bar_label, as fully described in How to add value labels on a bar chart.
Use pandas.crosstab or pandas.DataFrame.groupby to calculate the count of each category by the hue group.
As tips.info() shows, several columns have a category Dtype, which insures the plotting order and why the tp.index and tp.column order matches the x-axis and hue order of ax. Use pandas.Categorical to set a column to a category Dtype.
Tested in python 3.11, pandas 1.5.2, matplotlib 3.6.2, seaborn 0.12.1

import pandas as pd
import seaborn as sns

# load the data
tips = sns.load_dataset('tips')

# determine the number of each gender for each day
tp = pd.crosstab(tips.day, tips.sex)

# or use groupby
# tp = tips.groupby(['day', 'sex']).sex.count().unstack('sex')

# plot the data
ax = sns.barplot(x='day', y='total_bill', hue='sex', data=tips)

# move the legend if needed
sns.move_legend(ax, bbox_to_anchor=(1, 1.02), loc='upper left', frameon=False)

# iterate through each group of bars, zipped to the corresponding column name
for c, col in zip(ax.containers, tp):
    
    # add bar labels with custom annotation values
    ax.bar_label(c, labels=tp[col], padding=3, label_type='center')

`DataFrame` Views

`tips`

tips.head()

   total_bill   tip     sex smoker  day    time  size
0       16.99  1.01  Female     No  Sun  Dinner     2
1       10.34  1.66    Male     No  Sun  Dinner     3
2       21.01  3.50    Male     No  Sun  Dinner     3
3       23.68  3.31    Male     No  Sun  Dinner     2
4       24.59  3.61  Female     No  Sun  Dinner     4

tips.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 244 entries, 0 to 243
Data columns (total 7 columns):
 #   Column      Non-Null Count  Dtype   
---  ------      --------------  -----   
 0   total_bill  244 non-null    float64 
 1   tip         244 non-null    float64 
 2   sex         244 non-null    category
 3   smoker      244 non-null    category
 4   day         244 non-null    category
 5   time        244 non-null    category
 6   size        244 non-null    int64   
dtypes: category(4), float64(2), int64(1)
memory usage: 7.4 KB

`tp`

sex   Male  Female
day               
Thur    30      32
Fri     10       9
Sat     59      28
Sun     58      18

How to annotate grouped bars with group count instead of bar height

1 Answers1

DataFrame Views

tips

tp

`DataFrame` Views

`tips`

`tp`