如何修正Matplotlib与Pandas GroupBy折线图添加数据标签的报错？

问题描述 #

用户编写了以下代码，试图为Pandas GroupBy分组后绘制的Matplotlib折线图添加数据标签，但运行时抛出错误：

import matplotlib.pyplot as plt
import pandas as pd
from io import StringIO

csvfile = StringIO(
"""
Name    Year - Month    Score
Mike    2022-09 192
Mike    2022-08 708
Mike    2022-07 140
Mike    2022-05 144
Mike    2022-04 60
Mike    2022-03 108
Kate    2022-07 19850
Kate    2022-06 19105
Kate    2022-05 23740
Kate    2022-04 19780
Kate    2022-03 15495
Peter   2022-08 51
Peter   2022-07 39
Peter   2022-06 49
Peter   2022-05 49
Peter   2022-04 79
Peter   2022-03 13
Lily    2022-11 2
David   2022-11 3
David   2022-10 6
David   2022-08 2""")

df = pd.read_csv(csvfile, sep = '\t', engine='python')

for group_name, sub_frame in df.groupby("Name"):
    if sub_frame.shape[0] >= 2:
        sub_frame_sorted = sub_frame.sort_values('Year - Month')       # sort the data-frame by a column

        line_chart = sub_frame_sorted.plot("Year - Month", "Score")

        label = sub_frame_sorted['Score']
        line_chart.annotate(label, (sub_frame_sorted['Year - Month'], sub_frame_sorted['Score']), ha='center') 

plt.show()

错误信息 #

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

修正方案 #

错误根源在于matplotlib.axes.Axes.annotate()方法只能处理单个数据点的标注，不能直接传入Pandas Series作为参数。需要遍历排序后的数据框中的每一行，为每个点单独添加标签。

修正后的代码如下：

import matplotlib.pyplot as plt
import pandas as pd
from io import StringIO

csvfile = StringIO(
"""
Name    Year - Month    Score
Mike    2022-09 192
Mike    2022-08 708
Mike    2022-07 140
Mike    2022-05 144
Mike    2022-04 60
Mike    2022-03 108
Kate    2022-07 19850
Kate    2022-06 19105
Kate    2022-05 23740
Kate    2022-04 19780
Kate    2022-03 15495
Peter   2022-08 51
Peter   2022-07 39
Peter   2022-06 49
Peter   2022-05 49
Peter   2022-04 79
Peter   2022-03 13
Lily    2022-11 2
David   2022-11 3
David   2022-10 6
David   2022-08 2""")

df = pd.read_csv(csvfile, sep = '\t', engine='python')

for group_name, sub_frame in df.groupby("Name"):
    if sub_frame.shape[0] >= 2:
        sub_frame_sorted = sub_frame.sort_values('Year - Month')
        line_chart = sub_frame_sorted.plot("Year - Month", "Score", title=f"Score Trend for {group_name}")
        
        # 遍历每一行，逐个添加数据标签
        for x, y in zip(sub_frame_sorted['Year - Month'], sub_frame_sorted['Score']):
            line_chart.annotate(str(y), (x, y), ha='center', va='bottom', fontsize=8)

plt.tight_layout()
plt.show()

关键修改点 #

• 用zip()将x轴（年份月份）和y轴（分数）的元素一一配对，遍历每个数据点
• 调用annotate()时传入单个的标签值（转为字符串避免格式问题）、单个坐标点
• 添加va='bottom'参数让标签在数据点上方显示，避免重叠；可选调整fontsize让标签更美观
• 为每个子图添加标题，区分不同用户的趋势图
• 加入plt.tight_layout()自动调整子图间距，防止标签或标题被截断

内容的提问来源于stack exchange，提问作者Mark K