Forecast Example

library(tidyverse)
library(prophet)
library(forecast)
library(gridExtra)
library(Metrics)
library(tvReg)

data <- read_csv("data_library.csv") %>% filter(day!=26)

Parsed with column specification:
cols(
  ts = col_datetime(format = ""),
  name = col_character(),
  reading = col_double(),
  units = col_character(),
  cumulative = col_double(),
  day = col_double(),
  wday = col_double(),
  is_weekend = col_double(),
  month = col_double(),
  date = col_date(format = ""),
  time = col_character(),
  t = col_double(),
  rate = col_double(),
  occupancy = col_double(),
  day_type = col_character()
)

head(data)

tail(data)

train    <- data %>% filter(day!=25)
test     <- data %>% filter(day==25)
train.df <- train %>% select(ts, rate) %>% rename(ds=ts, y=rate)

y <- ts(train.df$y, start = 1, frequency = 144)
plot(y)

stlf(y) %>% autoplot()