Python Pandas 数据框分组图
声明：本页面是StackOverFlow热门问题的中英对照翻译，遵循CC BY-SA 4.0协议，如果您需要使用它，必须同样遵循CC BY-SA许可，注明原文地址和作者信息，同时你必须将它归于原作者（不是我）：StackOverFlow
原文地址: http://stackoverflow.com/questions/41494942/
Warning: these are provided under cc-by-sa 4.0 license. You are free to use/share it, But you must attribute it to the original authors (not me):
StackOverFlow
Pandas dataframe groupby plot
提问by MCM
I have a dataframe which is structured as:
我有一个数据框，其结构如下：
Date ticker adj_close
0 2016-11-21 AAPL 111.730
1 2016-11-22 AAPL 111.800
2 2016-11-23 AAPL 111.230
3 2016-11-25 AAPL 111.790
4 2016-11-28 AAPL 111.570
...
8 2016-11-21 ACN 119.680
9 2016-11-22 ACN 119.480
10 2016-11-23 ACN 119.820
11 2016-11-25 ACN 120.740
...
How can I plot based on the ticker the adj_closeversus Date?
我怎样才能情节基础上，股票的adj_close对比Date？
回答by Julien Marrec
Simple plot,
简单的剧情，
you can use:
您可以使用：
df.plot(x='Date',y='adj_close')
Or you can set the index to be Datebeforehand, then it's easy to plot the column you want:
或者你可以Date预先设置索引，然后很容易绘制你想要的列：
df.set_index('Date', inplace=True)
df['adj_close'].plot()
If you want a chart with one series by tickeron it
如果你想用一个系列的图表由ticker上
You need to groupbybefore:
您需要先分组：
df.set_index('Date', inplace=True)
df.groupby('ticker')['adj_close'].plot(legend=True)
If you want a chart with individual subplots:
如果你想要一个带有单独子图的图表：
grouped = df.groupby('ticker')
ncols=2
nrows = int(np.ceil(grouped.ngroups/ncols))
fig, axes = plt.subplots(nrows=nrows, ncols=ncols, figsize=(12,4), sharey=True)
for (key, ax) in zip(grouped.groups.keys(), axes.flatten()):
grouped.get_group(key).plot(ax=ax)
ax.legend()
plt.show()
回答by Yaakov Bressler
Similar to Julien's answer above, I had success with the following:
与上述 Julien 的回答类似，我在以下方面取得了成功：
fig, ax = plt.subplots(figsize=(10,4))
for key, grp in df.groupby(['ticker']):
ax.plot(grp['Date'], grp['adj_close'], label=key)
ax.legend()
plt.show()
This solution might be more relevant if you want more control in matlab.
如果您想在 matlab 中进行更多控制，则此解决方案可能更相关。
Solution inspired by: https://stackoverflow.com/a/52526454/10521959
解决方案灵感来自：https: //stackoverflow.com/a/52526454/10521959
