在大 pandas 分组之后绘制多个时间序列 [英] Plotting multiple time series after a groupby in pandas

问题描述

假设我在valgdata DataFrame上进行了分组，如下所示:

Suppose I made a groupby on the valgdata DataFrame like below:

grouped_valgdata = valgdata.groupby(['news_site','dato_uden_tid']).mean()

现在我明白了:

                                  sentiment
news_site          dato_uden_tid           
dr.dk              2015-06-15     54.777183
                   2015-06-16     54.703167
                   2015-06-17     54.948775
                   2015-06-18     54.424881
                   2015-06-19     53.290554
eb.dk              2015-06-15     53.279251
                   2015-06-16     53.285643
                   2015-06-17     53.558753
                   2015-06-18     52.854750
                   2015-06-19     54.415988
jp.dk              2015-06-15     56.590428
                   2015-06-16     55.313752
                   2015-06-17     53.771377
                   2015-06-18     53.218408
                   2015-06-19     54.392638
pol.dk             2015-06-15     54.759532
                   2015-06-16     55.182641
                   2015-06-17     55.001800
                   2015-06-18     56.004326
                   2015-06-19     54.649052

现在，我想为每个news_site建立一个时间序列，其中dato_uden_tid在X轴上，而情感在Y轴上.

Now I want to make a timeseries for each of the news_site, where dato_uden_tid is on the X axis and sentiment is on Y axis.

实现此目标的最佳和最简便的方法是什么?

What is the best and easiest way to accomplish that?

谢谢！

推荐答案

(有点逗乐，因为这个问题使我做了同样的事情.)

(Am a bit amused, as this question caught me doing the exact same thing.)

您可以做类似的事情

valgdata\
    .groupby([valgdata.dato_uden_tid.name, valgdata.news_site.name])\
    .mean()\
    .unstack()

将会

• 反转分组依据

• reverse the groupby

将新网站堆叠为列

要进行绘制，只需立即执行上一个代码片段，然后紧跟.plot():

To plot, just do the previous snippet immediately followed by .plot():

valgdata\
    .groupby([valgdata.dato_uden_tid.name, valgdata.news_site.name])\
    .mean()\
    .unstack()\
    .plot()

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