检查这个链接 Matplotlib画廊 这就是我如何使用autolabel的代码片段。

    def autolabel(rects):
    """Attach a text label above each bar in *rects*, displaying its height."""
    for rect in rects:
        height = rect.get_height()
        ax.annotate('{}'.format(height),
                    xy=(rect.get_x() + rect.get_width() / 2, height),
                    xytext=(0, 3),  # 3 points vertical offset
                    textcoords="offset points",
                    ha='center', va='bottom')
        
temp = df_launch.groupby(['yr_mt','year','month'])['subs_trend'].agg(subs_count='sum').sort_values(['year','month']).reset_index()
_, ax = plt.subplots(1,1, figsize=(30,10))
bar = ax.bar(height=temp['subs_count'],x=temp['yr_mt'] ,color ='g')
autolabel(bar)

ax.set_title('Monthly Change in Subscribers from Launch Date')
ax.set_ylabel('Subscriber Count Change')
ax.set_xlabel('Time')
plt.show()

matplotlib 3.4.0新增功能

现在有一个内置的Axes。Bar_label helper方法来自动标记条形图:

fig, ax = plt.subplots()
bars = ax.barh(indexes, values)

ax.bar_label(bars)

注意，对于分组/堆叠的条形图，会有多个条形容器，它们都可以通过ax.containers访问:

for bars in ax.containers:
    ax.bar_label(bars)

更多的细节:

如何添加成千上万的分隔符(逗号)标签 如何应用f字符串标签 如何添加标签间距

对于任何想要把标签放在条形图底部的人，只需用v除以标签的值，像这样:

for i, v in enumerate(labels):
    axes.text(i-.25, 
              v/labels[i]+100, 
              labels[i], 
              fontsize=18, 
              color=label_color_list[i])

(注意:我加了100，所以它不是绝对在底部)

得到这样的结果:

检查这个链接 Matplotlib画廊 这就是我如何使用autolabel的代码片段。

    def autolabel(rects):
    """Attach a text label above each bar in *rects*, displaying its height."""
    for rect in rects:
        height = rect.get_height()
        ax.annotate('{}'.format(height),
                    xy=(rect.get_x() + rect.get_width() / 2, height),
                    xytext=(0, 3),  # 3 points vertical offset
                    textcoords="offset points",
                    ha='center', va='bottom')
        
temp = df_launch.groupby(['yr_mt','year','month'])['subs_trend'].agg(subs_count='sum').sort_values(['year','month']).reset_index()
_, ax = plt.subplots(1,1, figsize=(30,10))
bar = ax.bar(height=temp['subs_count'],x=temp['yr_mt'] ,color ='g')
autolabel(bar)

ax.set_title('Monthly Change in Subscribers from Launch Date')
ax.set_ylabel('Subscriber Count Change')
ax.set_xlabel('Time')
plt.show()

我也需要条形标签，注意我的y轴有一个使用y轴限制的缩放视图。将标签放在栏顶的默认计算仍然使用height(示例中的use_global_coordinate=False)。但是我想说明的是，使用matplotlib 3.0.2中的全局坐标，也可以在放大视图中将标签放在图的底部。希望它能帮助到别人。

def autolabel(rects,data):
"""
Attach a text label above each bar displaying its height
"""
c = 0
initial = 0.091
offset = 0.205
use_global_coordinate = True

if use_global_coordinate:
    for i in data:        
        ax.text(initial+offset*c, 0.05, str(i), horizontalalignment='center',
                verticalalignment='center', transform=ax.transAxes,fontsize=8)
        c=c+1
else:
    for rect,i in zip(rects,data):
        height = rect.get_height()
        ax.text(rect.get_x() + rect.get_width()/2., height,str(i),ha='center', va='bottom')

使用plot. text()将文本放入图中。

例子:

import matplotlib.pyplot as plt
N = 5
menMeans = (20, 35, 30, 35, 27)
ind = np.arange(N)

#Creating a figure with some fig size
fig, ax = plt.subplots(figsize = (10,5))
ax.bar(ind,menMeans,width=0.4)
#Now the trick is here.
#plt.text() , you need to give (x,y) location , where you want to put the numbers,
#So here index will give you x pos and data+1 will provide a little gap in y axis.
for index,data in enumerate(menMeans):
    plt.text(x=index , y =data+1 , s=f"{data}" , fontdict=dict(fontsize=20))
plt.tight_layout()
plt.show()

这将显示的图形为: