python - 如何增加子图文本大小并添加自定义条形图注释

Question

我有以下数据框，表示每个地区每个部门/区域的员工总数。

               Finance   HR   IT  Marketing  Medical  Operations  Sales
Business Unit                                                          
Cardiology           0    2    1          0        3           0      0
Genetics             1    4    3          1        3           1      1
Imaging             34   74   70         38       68          18     33
Labs                63  130  131         66      130          32     68
Pathology            2    5   10          4        8           3      6

使用此数据框，我使用以下代码生成了波纹管图:

#Plot the graph
fig, ax = plt.subplots(1, 5, figsize=(30, 15), sharey = True)
iax = iter(ax.flatten())
for n, g in df.groupby('Business Unit'):
    g.loc[n, :].plot.bar(ax=next(iax),  title=f'{n}', stacked=True, legend = True, fontsize = 30)

如您所见，通知业务部门的子图的文本大小以及图例大小(在顶角)太小了。我怎样才能增加他们两个的文字？
另外，有没有一种方法可以在此代码中添加一种方法来显示每一列中总数的百分比？
非常感谢你的帮助!

Answer 1

我会用 pandas.DataFrame.plot ，它将索引绘制为 xaxis。因此，数据帧需要与 .T 转置

这使用 matplotlib和默认绘图后端

使用 subplots=True , df.plot分配给 axes ，这是一个 array的 arrays的 AxesSubplots

可以使用 .bar_label 添加注释，可以使用 labels= 自定义标签范围。以下链接提供自定义 labels 的示例.

Bar Label Demo

stack bar plot in matplotlib and add label to each section

How to add multiple annotations to a barplot

How to plot a horizontal stacked bar with annotations

在 pandas 1.3.0 中测试和 matplotlib 3.4.2

import pandas as pd

# load dataframe
data = {'Cardiology': {'Finance': 0, 'HR': 2, 'IT': 1, 'Marketing': 0, 'Medical': 3, 'Operations': 0, 'Sales': 0}, 'Genetics': {'Finance': 1, 'HR': 4, 'IT': 3, 'Marketing': 1, 'Medical': 3, 'Operations': 1, 'Sales': 1}, 'Imaging': {'Finance': 34, 'HR': 74, 'IT': 70, 'Marketing': 38, 'Medical': 68, 'Operations': 18, 'Sales': 33}, 'Labs': {'Finance': 63, 'HR': 130, 'IT': 131, 'Marketing': 66, 'Medical': 130, 'Operations': 32, 'Sales': 68}, 'Pathology': {'Finance': 2, 'HR': 5, 'IT': 10, 'Marketing': 4, 'Medical': 8, 'Operations': 3, 'Sales': 6}}
df = pd.DataFrame.from_dict(data, orient='index')

# get the total for each business unit; used to calculate percent
bu_total = df.sum(axis=1)

# get the total for each division; used to calculate percent
div_total = df.sum(axis=0)

# plot
axes = df.T.plot(kind='bar', subplots=True, layout=(1, 5), figsize=(22, 6), sharey=True, ylabel='Expenditures ($)')

# iterate through axes subplots
for ax in axes[0]:
    # title is used to get the total from bu_total
    title = ax.get_title()
    
    ax.legend(fontsize=15)
    ax.set_xticklabels(ax.get_xticklabels(), fontdict={'fontsize':24})
    ax.set_title(title, fontdict={'fontsize':24})
    ax.set_ylabel(ax.get_ylabel(), fontdict={'fontsize':24})
    
    # customized labels for % business unit total
    bu_labels = [f'{(v.get_height() / bu_total[title])*100 :.0f}%' for v in ax.containers[0]]
    
    # customized labels for % division total
    div_labels = [f'{(v.get_height() / div_total[i])*100 :.0f}%' for i, v in enumerate(ax.containers[0])]
    
    # annotate as desired: use bu_lables or div_labels
    ax.bar_label(ax.containers[0], labels=bu_labels, label_type='edge', fontsize=10)

    # pad the spacing between the number and the edge of the figure
    ax.margins(y=0.1)