如何按行计算百分比并注释 100% 堆积条

How to calculate percent by row and annotate 100 percent stacked bars

我需要帮助在 pandas 从数据框中的交叉表创建的堆叠条形图的每个部分中添加总数的百分比分布(无小数)。

这是示例数据:

data = {
    'Name':['Alisa','Bobby','Bobby','Alisa','Bobby','Alisa',
            'Alisa','Bobby','Bobby','Alisa','Bobby','Alisa'],
    'Exam':['Semester 1','Semester 1','Semester 1','Semester 1','Semester 1','Semester 1',
            'Semester 2','Semester 2','Semester 2','Semester 2','Semester 2','Semester 2'],
     
    'Subject':['Mathematics','Mathematics','English','English','Science','Science',
               'Mathematics','Mathematics','English','English','Science','Science'],
   'Result':['Pass','Pass','Fail','Pass','Fail','Pass','Pass','Fail','Fail','Pass','Pass','Fail']}
df = pd.DataFrame(data)

# display(df)
     Name        Exam      Subject Result
0   Alisa  Semester 1  Mathematics   Pass
1   Bobby  Semester 1  Mathematics   Pass
2   Bobby  Semester 1      English   Fail
3   Alisa  Semester 1      English   Pass
4   Bobby  Semester 1      Science   Fail
5   Alisa  Semester 1      Science   Pass
6   Alisa  Semester 2  Mathematics   Pass
7   Bobby  Semester 2  Mathematics   Fail
8   Bobby  Semester 2      English   Fail
9   Alisa  Semester 2      English   Pass
10  Bobby  Semester 2      Science   Pass
11  Alisa  Semester 2      Science   Fail

这是我的代码:

#crosstab
pal = ["royalblue", "dodgerblue", "lightskyblue", "lightblue"]
ax= pd.crosstab(df['Name'], df['Subject']).apply(lambda r: r/r.sum()*100, axis=1)
ax.plot.bar(figsize=(10,10),stacked=True, rot=0, color=pal)
display(ax)
    
plt.legend(loc='best', bbox_to_anchor=(0.1, 1.0),title="Subject",)

plt.xlabel('Name')
plt.ylabel('Percent Distribution')

plt.show()

我知道我需要添加一个 plt.text 一些方法,但无法弄清楚。我希望将总计的百分比嵌入到堆叠条中。

让我们试试:

# crosstab
pal = ["royalblue", "dodgerblue", "lightskyblue", "lightblue"]
ax= pd.crosstab(df['Name'], df['Subject']).apply(lambda r: r/r.sum()*100, axis=1)
ax_1 = ax.plot.bar(figsize=(10,10), stacked=True, rot=0, color=pal)
display(ax)

plt.legend(loc='upper center', bbox_to_anchor=(0.1, 1.0), title="Subject")

plt.xlabel('Name')
plt.ylabel('Percent Distribution')

for rec in ax_1.patches:
    height = rec.get_height()
    ax_1.text(rec.get_x() + rec.get_width() / 2, 
              rec.get_y() + height / 2,
              "{:.0f}%".format(height),
              ha='center', 
              va='bottom')
    
plt.show()

输出:


Subject English Mathematics Science
Name            
Alisa   33.333333   33.333333   33.333333
Bobby   33.333333   33.333333   33.333333

  • matplotlib 3.4.2 使用 matplotlib.pyplot.bar_label
    • 请参阅此 answer 以获得使用该方法的详尽解释以及其他示例。
    • 使用label_type='center'会注解每个段的值,label_type='edge'会注解段的累计和
  • 使用 pandas.DataFrame.plotkind='bar'stacked=True
  • 绘制堆积条是最简单的
  • 以矢量化方式获取百分比(没有.apply):
    1. 使用pd.crosstab
    2. 获取频率计数
    3. 沿 axis=0 除以 ct 除以 ct.sum(axis=1)
      • 使用 .div and .sum 指定正确的轴很重要。
    4. 乘以 100,四舍五入。
    • 最好使用 .crosstab 完成此操作,因为它会生成具有正确形状的数据框,用于绘制堆叠条形图。 .groupby 需要进一步重塑数据框。
  • 测试于 python 3.10pandas 1.3.4matplotlib 3.5.0
import pandas as pd
import matplotlib.pyplot as plt

# get a frequency count using crosstab
ct = pd.crosstab(df['Name'], df['Subject'])

# vectorized calculation of the percent per row 
ct = ct.div(ct.sum(axis=1), axis=0).mul(100).round(2)

# display(ct)
Subject  English  Mathematics  Science
Name                                  
Alisa      33.33        33.33    33.33
Bobby      33.33        33.33    33.33

# specify custom colors
pal = ["royalblue", "dodgerblue", "lightskyblue", "lightblue"]

# plot
ax = ct.plot(kind='bar', figsize=(10, 10), stacked=True, rot=0, color=pal, xlabel='Name', ylabel='Percent Distribution')

# move the legend
ax.legend(title='Subject', bbox_to_anchor=(1, 1.02), loc='upper left')

# iterate through each bar container
for c in ax.containers:

    # add the annotations
    ax.bar_label(c, fmt='%0.0f%%', label_type='center')

plt.show()

  • 使用label_type='edge' 以累计和注释