Pandas: How to build a barchar with data frames with labels?

Question

I have the following data file 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 create a velvet, as shown below Where instead a,b,c,dthere would be labels in the column ObjectID, the y axis should correspond to the column result, and the x axis should be values ​​grouped by column timestamp.

I tried a few things, but nothing worked. This was the closest, but the method plot()does not require any configuration through the parameters (for example, it kind='bar'does not work).

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

Any other idea?

Answer 1

@NaderHisham - !
, , - , pandas/matplotlib:

, objectIds :

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

, :

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

Answer 2

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 );