Electricity price prediction

Y =read_delim("C:/Users/drkos/Desktop/Tok.csv", 
     delim = ";", escape_double = FALSE, col_types = cols(date = col_date(format = "%d.%m.%Y")), 
     trim_ws = TRUE) %>% 
     dplyr::rename(ds= date, 
                   y= price)

Model1 <- prophet(Y)

## Disabling yearly seasonality. Run prophet with yearly.seasonality=TRUE to override this.

## Disabling daily seasonality. Run prophet with daily.seasonality=TRUE to override this.

Future1 <- make_future_dataframe(Model1, periods = 130)
tail(Future1)

##             ds
## 518 2022-05-02
## 519 2022-05-03
## 520 2022-05-04
## 521 2022-05-05
## 522 2022-05-06
## 523 2022-05-07

Forecast1 <- predict(Model1, Future1)
tail(Forecast1[c('ds','yhat','yhat_lower','yhat_upper')])

##             ds     yhat yhat_lower yhat_upper
## 518 2022-05-02 729.4849   663.8574   800.2834
## 519 2022-05-03 738.9084   672.6008   806.2538
## 520 2022-05-04 752.3496   685.6424   820.8900
## 521 2022-05-05 744.7606   676.8784   811.9447
## 522 2022-05-06 741.0796   673.8407   808.7190
## 523 2022-05-07 715.9228   643.9840   782.1696

dyplot.prophet(Model1, Forecast1)

## Warning: `select_()` was deprecated in dplyr 0.7.0.
## Please use `select()` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was generated.

prophet_plot_components(Model1, Forecast1)

Габриела омъжи се за мен, роди ми деца! Преди цената на тока да еректира!