I am plotting a graph with datetime and power which can be seen in the big blue line on the attached image.

After plotting the image, I am trying to insert the 1-d list (only_unusual) in the same plot.

Actually df['power'] includes the values of the 1-d list (only_unusual).

But without including y axis alongside with only_unusual I can't plot the graph.

How can I plot the only_unusual list in the same plot so that it will be visible on the main blue line with a different color?

My code:

fig, ax = plt.subplots(figsize=(16,12))
ax.plot(pd.to_datetime(df['datetime']), df['power'], color='b',label='Normal')
ax.scatter(only_unusual ,  color='red', label='Unusual',marker='o')
ax.xaxis_date()
plt.xlabel('Date Time')
plt.ylabel('power')
plt.legend()
fig.autofmt_xdate()
plt.show()

My data:

only_unusual : [13.266, 4.213291, 2.756, 3.6722, 12.356, 12.193, 10.318, 12.203, 8.7549, 9.536, 9.10677, 1.417]




df :

        datetime              invno  power
0       2021-12-01 00:00:00    1     0.000
5       2021-12-01 01:00:00    1     0.000
10      2021-12-01 02:00:00    1     0.000
15      2021-12-01 03:00:00    1     0.000
20      2021-12-01 04:00:00    1     0.000
....     ...... ...... ....    ..     .....

1129    2021-12-10 09:00:00    5    2.914
1134    2021-12-10 10:00:00    5    10.318

...     ... ... ...
1149    2021-12-10 13:00:00    5     2.756
1154    2021-12-10 14:00:00    5     1.297
1159    2021-12-10 15:00:00    5     1.503
1164    2021-12-10 16:00:00   5      1.417
1169    2021-12-10 17:00:00    5     0.084
1170 rows × 3 columns

CodePudding user response：

If the list contains y values (power)

Normally we could find matching y values with

If the list contains x values (datetime)

1. We can just use isin to find matching datetime rows:

   matches = df[df['datetime'].isin(only_unusual)]
   

2. Then use these matches (instead of df) for the scatter plot:

   ax.scatter(pd.to_datetime(matches['datetime']), matches['power'], color='r', label='Unusual', marker='o')
   #                         ^^^^^^^               ^^^^^^^