Pronosticando casos de coronavirus usando Prophet

Pronosticando casos de coronavirus usando Prophet.

#Call the Packages

library(prophet)

## Loading required package: Rcpp

## Loading required package: rlang

library(tidyverse)

## -- Attaching packages --------------------------------------- tidyverse 1.3.1 --

## v ggplot2 3.3.3     v purrr   0.3.4
## v tibble  3.1.1     v dplyr   1.0.6
## v tidyr   1.1.3     v stringr 1.4.0
## v readr   1.4.0     v forcats 0.5.1

## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x purrr::%@%()         masks rlang::%@%()
## x purrr::as_function() masks rlang::as_function()
## x dplyr::filter()      masks stats::filter()
## x purrr::flatten()     masks rlang::flatten()
## x purrr::flatten_chr() masks rlang::flatten_chr()
## x purrr::flatten_dbl() masks rlang::flatten_dbl()
## x purrr::flatten_int() masks rlang::flatten_int()
## x purrr::flatten_lgl() masks rlang::flatten_lgl()
## x purrr::flatten_raw() masks rlang::flatten_raw()
## x purrr::invoke()      masks rlang::invoke()
## x dplyr::lag()         masks stats::lag()
## x purrr::list_along()  masks rlang::list_along()
## x purrr::modify()      masks rlang::modify()
## x purrr::prepend()     masks rlang::prepend()
## x purrr::splice()      masks rlang::splice()

df1<- read.csv("E:/DailyCOVID.csv")
View(df1)
colnames(df1)=c("ds","y")
head(df1)

head(df1)

#Call the Prophet Function and Fit the Model

Model1 <- prophet(df1)

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

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

#Model1
future1 <- make_future_dataframe(Model1, periods = 30)
tail(future1)

#Forecast 

forecast1 <- predict(Model1, future1)
head(forecast1)

tail(forecast1[c('ds','yhat','yhat_lower','yhat_upper')])

#Plot the Estimates

dyplot.prophet(Model1, forecast1)

## Warning: `select_()` was deprecated in dplyr 0.7.0.
## Please use `select()` instead.

prophet_plot_components(Model1,forecast1)

#Cumulative Coronavirus Cases
df2 <- read.csv("E:/TotalCOVID.csv")
View(df2)
#df2 <- read.csv(file.choose())
head(df2)

colnames(df2)=c("ds","y")
head(df2)

#Call the Prophet Function and Fit the Model

Model2 <- prophet(df2)

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

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

future2 <- make_future_dataframe(Model2, periods = 30)
tail(future2)

#Forecast 

forecast2 <- predict(Model2, future2)
tail(forecast2[c('ds','yhat','yhat_lower','yhat_upper')])

#Plot the Estimates

dyplot.prophet(Model2, forecast2)

prophet_plot_components(Model2,forecast2)