Pandas: 如何绘制带有标签数据框的条形图?

Pandas: How to plot a barchar with dataframes with labels?

我有以下数据框 df:

             timestamp      objectId  result
0  2015-11-24 09:00:00        Stress       3
1  2015-11-24 09:00:00  Productivity       0
2  2015-11-24 09:00:00     Abilities       4
3  2015-11-24 09:00:00     Challenge       0
4  2015-11-24 10:00:00  Productivity      87
5  2015-11-24 10:00:00     Abilities      84
6  2015-11-24 10:00:00     Challenge      58
7  2015-11-24 10:00:00        Stress      25
8  2015-11-24 11:00:00  Productivity      93
9  2015-11-24 11:00:00     Abilities      93
10 2015-11-24 11:00:00     Challenge      93
11 2015-11-24 11:00:00        Stress      19
12 2015-11-24 12:00:00     Challenge      90
13 2015-11-24 12:00:00     Abilities      96
14 2015-11-24 12:00:00        Stress      94
15 2015-11-24 12:00:00  Productivity      88
16 2015-11-24 13:00:00  Productivity      12
17 2015-11-24 13:00:00     Challenge      17
18 2015-11-24 13:00:00     Abilities      89
19 2015-11-24 13:00:00        Stress      13

我想实现如下的条形图a,b,c,d 列中有标签而不是 ObjectID 的地方,y 轴应该对应于 result 列,x 轴应该是 [=17] 列的分组值=].

我尝试了几件事,但没有任何效果。这是最接近的,但是 plot() 方法不通过参数进行任何自定义(例如 kind='bar' 不起作用)。

groups = df.groupby('objectId')
sgb = groups['result']
sgb.plot()

还有其他想法吗?

import seaborn as sns

In [36]:
df.timestamp = df.timestamp.factorize()[0]

In [39]:
df.objectId = df.objectId.map({'Stress' : 'a' , 'Productivity' : 'b' , 'Abilities' : 'c' , 'Challenge' : 'd'})

In [41]:
df
Out[41]:
   timestamp    objectId    result
0       0           a           3
1       0           b           0
2       0           c           4
3       0           d           0
4       1           b           87
5       1           c           84
6       1           d           58
7       1           a           25
8       2           b           93
9       2           c           93
10      2           d           93
11      2           a           19
12      3           d           90
13      3           c           96
14      3           a           94
15      3           b           88
16      4           b           12
17      4           d           17
18      4           c           89
19      4           a           13

In [40]:
sns.barplot(x = 'timestamp' , y = 'result' , hue = 'objectId' , data = df );

@NaderHisham 的回答是一个非常简单的解决方案!
但仅作为参考,如果您出于某种原因不能使用 seaborn,这是一个纯粹的 pandas/matplotlib 解决方案:

您需要重塑数据,因此不同的 objectId 成为列:

In [20]: df.set_index(['timestamp', 'objectId'])['result'].unstack()
Out[20]:
objectId   Abilities  Challenge  Productivity  Stress
timestamp
09:00:00           4          0             0       3
10:00:00          84         58            87      25
11:00:00          93         93            93      19
12:00:00          96         90            88      94
13:00:00          89         17            12      13

如果你制作一个条形图,你会得到想要的结果:

In [24]: df.set_index(['timestamp', 'objectId'])['result'].unstack().plot(kind='bar')
Out[24]: <matplotlib.axes._subplots.AxesSubplot at 0xc44a5c0>