Seaborn Catplot 在条形图上设置值

Question

我策划了catplot在seaborn这样的

import seaborn as sns
import pandas as pd

data  = {'year': [2016, 2013, 2014, 2015, 2016, 2013, 2014, 2015, 2016, 2013, 2014, 2015, 2016, 2013, 2014, 2015, 2016, 2013, 2014, 2015], 'geo_name': ['Michigan', 'Michigan', 'Michigan', 'Michigan', 'Washtenaw County, MI', 'Washtenaw County, MI', 'Washtenaw County, MI', 'Washtenaw County, MI', 'Ann Arbor, MI', 'Ann Arbor, MI', 'Ann Arbor, MI', 'Ann Arbor, MI', 'Philadelphia, PA', 'Philadelphia, PA', 'Philadelphia, PA', 'Philadelphia, PA', 'Ann Arbor, MI Metro Area', 'Ann Arbor, MI Metro Area', 'Ann Arbor, MI Metro Area', 'Ann Arbor, MI Metro Area'], 'geo': ['04000US26', '04000US26', '04000US26', '04000US26', '05000US26161', '05000US26161', '05000US26161', '05000US26161', '16000US2603000', '16000US2603000', '16000US2603000', '16000US2603000', '16000US4260000', '16000US4260000', '16000US4260000', '16000US4260000', '31000US11460', '31000US11460', '31000US11460', '31000US11460'], 'income': [50803.0, 48411.0, 49087.0, 49576.0, 62484.0, 59055.0, 60805.0, 61003.0, 57697.0, 55003.0, 56835.0, 55990.0, 39770.0, 37192.0, 37460.0, 38253.0, 62484.0, 59055.0, 60805.0, 61003.0], 'income_moe': [162.0, 163.0, 192.0, 186.0, 984.0, 985.0, 958.0, 901.0, 2046.0, 1688.0, 1320.0, 1259.0, 567.0, 424.0, 430.0, 511.0, 984.0, 985.0, 958.0, 901.0]}
df = pd.DataFrame(data)

g = sns.catplot(x='year', y='income', data=df, kind='bar', hue='geo_name', legend=True)
g.fig.set_size_inches(15,8)
g.fig.subplots_adjust(top=0.81,right=0.86)  

我得到如下所示的输出

我想在 K 表示中在其顶部添加每个条的值。例如，2013在栏中 for Michiganis at48411所以我想在该栏的48.4K顶部添加值。对于所有酒吧也是如此。

Answer 1

• 使用matplotlib.pyplot.bar_label截至matplotlib v3.4.2
  • 有关与新方法相关的其他绘图选项，请参阅在 matplotlib 条形图上添加值标签。
  • 有关其他格式选项，请参阅matplotlib：条形标签演示页面。
  • 使用fmt参数表示简单格式，使用labels参数表示自定义字符串格式。
  • 对于水平条，请使用v.get_width代替v.get_height。
• 测试于python 3.11, pandas 1.5.3, matplotlib 3.7.1,seaborn 0.12.2

仅适用于单个地块

g = sns.catplot(data=df, x='year', y='income', kind='bar', hue='geo_name', legend=True, height=6, aspect=2)

# extract the matplotlib axes_subplot objects from the FacetGrid
ax = g.facet_axis(0, 0)  # or ax = g.axes.flat[0]

# iterate through the axes containers
for c in ax.containers:
    labels = [f'{(v.get_height() / 1000):.1f}K' for v in c]
    ax.bar_label(c, labels=labels, label_type='edge')

对于单个或多个地块

g = sns.catplot(data=df, x='year', y='income', kind='bar', col='geo_name', col_wrap=3)

g.fig.subplots_adjust(top=0.9)
g.fig.suptitle('Bar Count with Annotations')

# iterate through axes
for ax in g.axes.ravel():
    
    # add annotations
    for c in ax.containers:
        labels = [f'{(v.get_height() / 1000):.1f}K' for v in c]
        ax.bar_label(c, labels=labels, label_type='edge')
    ax.margins(y=0.2)

plt.show()

• 也适用于 Facets 中的分组条（子图）

df = sns.load_dataset('titanic')
g = sns.catplot(data=df, kind='count', x='survived', hue='sex', col='class')

# iterate through axes
for ax in g.axes.ravel():
    
    # add annotations
    for c in ax.containers:
        # add custom labels with the labels=labels parameter if needed
        # labels = [f'{h}' if (h := v.get_height()) > 0 else '' for v in c]
        ax.bar_label(c, label_type='edge')
    ax.margins(y=0.2)

Answer 2

我们可以使用 sns.catplot() 返回的 Facet 网格并选择轴。使用 for 循环使用 ax.text() 以我们需要的格式定位 Y 轴值

g = sns.catplot(x='year', y='income', data=data, kind='bar', hue='geo_name', legend=True)
g.fig.set_size_inches(16,8)
g.fig.subplots_adjust(top=0.81,right=0.86) 

ax = g.facet_axis(0,0)
for p in ax.patches:
    ax.text(p.get_x() - 0.01, 
            p.get_height() * 1.02, 
           '{0:.1f}K'.format(p.get_height()/1000),   #Used to format it K representation
            color='black', 
            rotation='horizontal', 
            size='large')