如何将异常值作为单独的彩色标记添加到线图中

Question

val             time
5.6     2021-11-18 03:00:00
2.034   2021-11-18 05:00:00
1.171   2021-11-18 07:00:00
3.023   2021-11-18 09:00:00
4.202   2021-11-18 16:00:00
1.202   2021-11-18 17:00:00
5.202   2021-11-18 18:00:00
7.202   2021-11-18 19:00:00
2.202   2021-11-18 20:00:00
12.202  2021-11-18 21:00:00
1.202   2021-11-18 21:00:00

上面是我的数据框，我想绘制它 (x=time,y=value)，并在 (val>5) 处将值绘制为红色。

plt.plot(ab['time'], ab['value'], '-gD', markevery=marks, label='line with select markers')

其中标记 [7.202,12.202] 是我手动创建的列表。但这不起作用。 error -: markevery is iterable but not a valid numpy fancy index

我在这里找到了，但是要是积分多的话，这个比较费时间

Answer 1

最简单的解决方案是使用 Boolean indexing to create a separate dataframe for values greater then 5, and then plot them as a scatter plot with pandas.DataFrame.plot
x 轴自动格式化为 %M-%d %H。当有更多数据时格式会改变，还有其他答案讨论如何格式化 pandas 日期时间轴。

import pandas as pd
import matplotlib.pyplot as plt

# sample data
data = {'val': [5.6, 2.034, 1.171, 3.023, 4.202, 1.202, 5.202, 7.202, 2.202, 12.202, 1.202], 'time': ['2021-11-18 03:00:00', '2021-11-18 05:00:00', '2021-11-18 07:00:00', '2021-11-18 09:00:00', '2021-11-18 16:00:00', '2021-11-18 17:00:00', '2021-11-18 18:00:00', '2021-11-18 19:00:00', '2021-11-18 20:00:00', '2021-11-18 21:00:00', '2021-11-18 21:00:00']}
df = pd.DataFrame(data)

# convert the time column to a datetime dtype
df.time = pd.to_datetime(df.time)

# get the values greater than 5
masked = df[df.val.gt(5)]

# plot the line plot
ax = df.plot(x='time', marker='o', figsize=(15, 5), zorder=0)

# plot those greater than 5
masked.plot(kind='scatter', x='time', y='val', color='red', ax=ax, s=30, label='outliers')

如何将异常值作为单独的彩色标记添加到线图中

How to add outliers as separate colored markers to a line plot

python

time-series

matplotlib

scatter-plot

pandas