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多索引散点图

[英]Multiindex scatter plot

Suppose I have the following data: 假设我有以下数据:

data = {'Value': {('1', 1): 3.0,
('1', 2): 4.0,
('1', 3): 51.0,
('1', 4): 10.0,
('1', 5): 2.0,
('1', 6): 17.0,
('1', 7): 14.0,
('1', 8): 7.0,
('1', 9): 2.0,
('1', 10): 1.0}}
df=pd.DataFrame(data)

Let's say this represents values for something for the first ten days in January. 假设这代表一月份前十天的值。 I want to plot this data, so I use: 我想绘制此数据,所以我使用:

df.plot()
plt.show()

Now, suppose I have another data set that has values for a subset of these dates with slightly different values but the same index values: 现在,假设我有另一个数据集,该数据集的这些日期的子集的值略有不同,但索引值相同:

df1 = df[df['Value']<10]
df1['Value'] = df1['Value']*2

My question is, how can I overlay a scatter plot of this data on the original line graph? 我的问题是,如何在原始折线图上叠加此数据的散点图?

Grab the axes handle of the first plot, then reindex df1 to align the data with the same indexes as df and plot df1 using ax=ax . 抓住第一个图的轴手柄,然后重新索引df1以使数据与df具有相同的索引,并使用ax=ax绘制df1。

ax = df.plot()
df1.reindex(df.index).plot(marker='o',linestyle='none',color='g', ax=ax)

Output: 输出:

在此处输入图片说明

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