path <- file.choose()
df <- read.csv(path, skip = 6)
View(df)
df <- data<-na.omit(df)
library(lubridate)
library(prophet)
origin_date <- ymd("2019-01-01")
origin_date + ddays(1)
df$index <- as.numeric(rownames(df))-1
df$ds <- origin_date+ddays(df$index-1)
df$ds <- df$Day.Index
df$y <- df$Sessions
df$Sessions <- NULL
df$Day.Index <- NULL
#ggplot(df)
m <- prophet(df)
future <- make_future_dataframe(m, periods = 365)
# R
forecast <- predict(m, future)
tail(forecast[c('ds', 'yhat', 'yhat_lower', 'yhat_upper')])
# View(forecast)
plot(m, forecast)
prophet_plot_components(m, forecast)
dyplot.prophet(m, forecast)