在堆积条形图Matplotlib中注释值

Question

我有以下数据集，并且我使用Matplotlib绘制了堆积条形图。

industry    Distribution    Manufacturing   Retail  Services
2017-09          1                4           12       7
2017-10          3                2            3       4
2017-11          1                0            2       1
2018-02          1                0            0       0

以下是生成图表的代码：

fig, ax = plt.subplots(1, figsize=(17,6))

part1 = ax.bar(industry_split.index.values, 'Retail', data=industry_split, color = 'darkblue', width=0.5, edgecolor=edgecolor, linewidth=linewidth)
part2 = ax.bar(industry_split.index.values, 'Services', data=industry_split, color = 'dodgerblue', edgecolor=edgecolor, linewidth=linewidth, width=0.5, bottom = industry_split.Retail)
part3 = ax.bar(industry_split.index.values, 'Manufacturing', data=industry_split, color = 'green', width=0.5, edgecolor=edgecolor, linewidth=linewidth, bottom = industry_split.Retail + industry_split.Services)
part4 = ax.bar(industry_split.index.values, 'Distribution', data=industry_split, color = 'orange', width=0.5, edgecolor=edgecolor, linewidth=linewidth, bottom = industry_split.Retail + industry_split.Services + industry_split.Manufacturing)

我需要在图表中注释值。例如，我需要每个条形的值显示在图形的条形图内。见下面的例子

Answer 1

使用以下代码：

# Adding Data Labels
for i, label in enumerate(list(industry_split.index.values)):
score1 = industry_split.loc[label]['Retail']
if score1 == 0:
    None
else:
    ax.annotate(str(score1), (i, score1 - 0.7), color='white', fontsize=12, weight='semibold')

score2 = industry_split.loc[label]['Services']
if score2 == 0:
    None
else:
    ax.annotate(str(score2), (i, score1 + score2 - 0.7), color='white', fontsize=12, weight='semibold')

score3 = industry_split.loc[label]['Manufacturing']
if score3 == 0:
    None
else:
    ax.annotate(str(score3), (i, score1 + score2 + score3 - 0.7), color='white', fontsize=12, weight='semibold')

score4 = industry_split.loc[label]['Distribution']
if score4 == 0:
    None
else:
    ax.annotate(str(score4), (i, score1 + score2 + score3 + score4 - 0.7), color='white', fontsize=12, weight='semibold')