[英]Pandas: How to plot a barchar with dataframes with labels?
I have the following dataframe df
: 我有以下数据帧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
I would like to achieve a barchart like the following 我想实现如下的条形图 Where instead of a,b,c,d
there would be the labels in the column ObjectID
the y-axis should correspond to the column result
and x-axis should be the values grouped of the column timestamp
. 而不是a,b,c,d
在ObjectID
列中将有标签,y轴应该对应于列result
而x轴应该是列timestamp
分组的值。
I tried several things but nothing worked. 我尝试了几件事,但没有任何效果。 This was the closest, but the plot()
method doesn't take any customisation via parameters (eg kind='bar'
doesn't work). 这是最接近的,但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()
Any other idea? 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 );
The answer of @NaderHisham is a very easy solution! @NaderHisham的答案是一个非常简单的解决方案!
But just as a reference, if you for some reason cannot use seaborn, this is a pure pandas/matplotlib solution: 但仅作为参考,如果由于某种原因不能使用seaborn,这是一个纯粹的pandas / matplotlib解决方案:
You need to reshape your data, so the different objectIds becomes the columns: 您需要重塑数据,因此不同的objectIds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
If you make a bar plot of this, you get the desired result: 如果你制作一个条形图,你会得到所需的结果:
In [24]: df.set_index(['timestamp', 'objectId'])['result'].unstack().plot(kind='bar')
Out[24]: <matplotlib.axes._subplots.AxesSubplot at 0xc44a5c0>
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