我对一家购物中心的一些入口传感器数据进行了异常检测。我想为每个入口创建一个图,并突出显示异常值(在数据框中的异常值列中标记为True)
以下是两个入口的一小部分数据,时间跨度为六天:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
df = pd.DataFrame({"date": [1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6],
"mall": ["Mall1", "Mall1", "Mall1", "Mall1", "Mall1", "Mall1", "Mall1", "Mall1", "Mall1", "Mall1", "Mall1", "Mall1"],
"entrance": ["West", "West","West","West","West", "West", "East", "East", "East", "East", "East", "East"],
"in": [132, 140, 163, 142, 133, 150, 240, 250, 233, 234, 2000, 222],
"outlier": [False, False, False, False, False, False, False, False, False, False, True, False]})
为了创建几个图(完整数据中有20个入口),我在seaborn遇到了lmplot
sns.set_theme(style="darkgrid")
for i, group in df.groupby('entrance'):
sns.lmplot(x="date", y="in", data=group, fit_reg=False, hue = "entrance")
#pseudo code
#for the rows that have an outlier (outlier = True) create a red dot for that observation
plt.show()
我想在这里完成两件事:
seaborn.lmplot
是一个Facetgrid
,我认为在这种情况下,它更难使用李>备选方案
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