Covid 19 Philippines: January 2020- June 13, 2021 report and Forecast

Last update : June 13, 2021 Data : Jan 2021 - May EOM, 2021 FOrecast : Data + 30 Days

Weekly Consolidated Daily Report and 30 days forecast

DATA RETRIEVAL

setwd("C:/Users/admin/Desktop/DATA SCIENCE/R Files")
dohacc <- read.csv("dohacc.csv")
dohacc$date <- as.Date(dohacc$date, "%m/%d/%Y")
dohacc$year <- format(dohacc$date, format = "%Y")
dohacc$month<- format(dohacc$date, format = "%m/%Y")
dohacc$confirm <- as.numeric(dohacc$confirm)

DATA STRUCTURE AND SUMMARY

dohacc$accumulate <- as.numeric(dohacc$accumulate)
str(dohacc)

'data.frame':   468 obs. of  5 variables:
 $ date      : Date, format: "2020-01-30" "2020-02-03" ...
 $ confirm   : num  1 1 1 2 1 4 14 9 16 3 ...
 $ accumulate: num  1 2 3 5 6 10 24 33 49 52 ...
 $ year      : chr  "2020" "2020" "2020" "2020" ...
 $ month     : chr  "01/2020" "02/2020" "02/2020" "03/2020" ...

dohacc

total <- sum(dohacc$confirm)
total

[1] 1318003

dohacc %>%  ggplot(aes(date,confirm, color="red")) + geom_line() + ggtitle("Daily Confimed Cases from Jan 2020- June 13, 2021")

dohacc %>%  ggplot(aes(date,accumulate)) + geom_point() + ggtitle("Accumulated Confimed Cases from Jan 2020- June 13, 2021")

FILTER DATA TO 2021 CASES ONLY

#filter 2021 cases only
cases2021 <- dohacc %>% filter(year==2021)
tail(cases2021)

PREDICTION AND FORCASTING MODEL

#Forecasting
ds <- cases2021$date
y <- cases2021$confirm
df <- data.frame(ds,y)
m <- prophet(df)

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

future <- make_future_dataframe(m, periods=30)
forecast <- predict(m,future)
summary(forecast)

       ds                          trend          additive_terms     
 Min.   :2021-01-01 00:00:00   Min.   :  -1.074   Min.   :-1051.941  
 1st Qu.:2021-02-18 06:00:00   1st Qu.:3319.902   1st Qu.: -981.680  
 Median :2021-04-07 12:00:00   Median :5733.532   Median :  176.949  
 Mean   :2021-04-07 12:00:00   Mean   :5173.026   Mean   :    3.962  
 3rd Qu.:2021-05-25 18:00:00   3rd Qu.:7151.762   3rd Qu.:  672.133  
 Max.   :2021-07-13 00:00:00   Max.   :8219.886   Max.   :  835.450  
 additive_terms_lower additive_terms_upper     weekly           weekly_lower      
 Min.   :-1051.941    Min.   :-1051.941    Min.   :-1051.941   Min.   :-1051.941  
 1st Qu.: -981.680    1st Qu.: -981.680    1st Qu.: -981.680   1st Qu.: -981.680  
 Median :  176.949    Median :  176.949    Median :  176.949   Median :  176.949  
 Mean   :    3.962    Mean   :    3.962    Mean   :    3.962   Mean   :    3.962  
 3rd Qu.:  672.133    3rd Qu.:  672.133    3rd Qu.:  672.133   3rd Qu.:  672.133  
 Max.   :  835.450    Max.   :  835.450    Max.   :  835.450   Max.   :  835.450  
  weekly_upper       multiplicative_terms multiplicative_terms_lower
 Min.   :-1051.941   Min.   :0            Min.   :0                 
 1st Qu.: -981.680   1st Qu.:0            1st Qu.:0                 
 Median :  176.949   Median :0            Median :0                 
 Mean   :    3.962   Mean   :0            Mean   :0                 
 3rd Qu.:  672.133   3rd Qu.:0            3rd Qu.:0                 
 Max.   :  835.450   Max.   :0            Max.   :0                 
 multiplicative_terms_upper   yhat_lower      yhat_upper     trend_lower      
 Min.   :0                  Min.   :-2788   Min.   : 1373   Min.   :  -1.074  
 1st Qu.:0                  1st Qu.: 1389   1st Qu.: 5520   1st Qu.:3319.902  
 Median :0                  Median : 3701   Median : 7748   Median :5701.297  
 Mean   :0                  Mean   : 3153   Mean   : 7203   Mean   :5143.739  
 3rd Qu.:0                  3rd Qu.: 5124   3rd Qu.: 9109   3rd Qu.:7151.762  
 Max.   :0                  Max.   : 6980   Max.   :11129   Max.   :8219.886  
  trend_upper            yhat       
 Min.   :  -1.074   Min.   :-714.7  
 1st Qu.:3319.902   1st Qu.:3445.4  
 Median :5773.834   Median :5711.4  
 Mean   :5203.102   Mean   :5177.0  
 3rd Qu.:7151.762   3rd Qu.:7144.4  
 Max.   :8219.886   Max.   :9028.7  

MONTHLY CASES 2021 AS OF APRIL MTD

upmonth <- cases2021 %>% mutate(month_ = month(date, label = T) )

upmonth %>%  ggplot(aes(month_,confirm, fill="red")) +  geom_bar(stat = "identity") + scale_y_continuous(labels=scales::comma) + ggtitle("Covid-19 Daily Confirmed Cases group by monthly, Philippines 2021")

upmonth %>% group_by(month_) %>%  summarise(Monthly2021_cases=sum(confirm), Avg_cases=mean(confirm))

June2021 <- upmonth %>% filter(month_=="Jun")
max(June2021$confirm)

[1] 8003

min(June2021$confirm)

[1] 4769

PLOT MODEL

dyplot.prophet(m, forecast, 
               main= "Jan 2021 - June 13, 2021 Data + 30 days forecast")

`select_()` was deprecated in dplyr 0.7.0.
Please use `select()` instead.Registered S3 method overwritten by 'htmlwidgets':
  method           from         
  print.htmlwidget tools:rstudio

Prepared by Dodgecarl Incila