Figure 1.0 - Average Day consumption for User ecenergy22 in 14 days |
Figure 2.0 - Average Day consumption for User ecenergy23 in 11 days |
Figure 3.0 - Average Day consumption for User ecenergy24 in 10 days |
Figure 4.0 - Average Day consumption for User ecenergy25 in 7 days |
Figure 5.0 - Average Day consumption for User ecenergy30 in 7 days |
Figure 6.0 - Average Day consumption for User ecenergy32 in 18 days |
Figure 7.0 - Average Day consumption for User ecenergy33 in 17 days |
Figure 8.0 - Average Day consumption for User ecenergy34 in 11 days |
Figure 9.0 - Average Day consumption for User ecenergy35 in 11 days |
Figure 10.0 - Average Day consumption for User ecenergy36 in 12 days |
Thank you. This looks interesting. Some users seem to be more predictable than others.
ReplyDeleteCan you try to calculate this again distinguishing week days and week-end days?
After that, it may be good to look into frequency.. not sure if the best would be to do it based on the user-generated events, or on the basis of power levels. If we measure how frequently power goes above x that would be an histogram. What about measuring the time it takes between two instants where power goes above x?