State-wise.Rmd

---
title: "State wise Analysis"
output: html_document
---

```{r setup, include=FALSE}
suppressWarnings(suppressPackageStartupMessages(library(ggplot2)))
suppressWarnings(suppressPackageStartupMessages(library(dplyr)))
suppressWarnings(suppressPackageStartupMessages(library(plyr)))
suppressWarnings(suppressPackageStartupMessages(library(DT)))
suppressWarnings(suppressPackageStartupMessages(library(readr)))
suppressWarnings(suppressPackageStartupMessages(library(forecast)))
suppressWarnings(suppressPackageStartupMessages(library(fpp)))
suppressWarnings(suppressPackageStartupMessages(library(TTR)))
suppressWarnings(suppressPackageStartupMessages(library(tseries)))
library(knitr)
library(markdown)
library(rmarkdown)

```


# State 
```{r}
# run report for current car listed in loop in R file
s1 <- data[data$STATE==state,]
datatable(s1)
```


## Parameters - Mean values
```{r}
temp <- ddply(s1,~YEAR,summarise,mean=mean(as.numeric(as.double(mean_temp))))
ph <- ddply(s1,~YEAR,summarise,mean=mean(as.numeric(as.double(mean_ph))))
conductivity <- ddply(s1,~YEAR,summarise,mean=mean(as.numeric(as.double(mean_conductivity))))
bod <- ddply(s1,~YEAR,summarise,mean=mean(as.numeric(as.double(mean_bod))))
nitrate <- ddply(s1,~YEAR,summarise,mean=mean(as.numeric(as.double(mean_nitratenitrite))))
fecal <- ddply(s1,~YEAR,summarise,mean=mean(as.numeric(as.double(mean_fecalcoliform))))
```

## Parameter
```{r echo=FALSE}
temp1 <- temp$mean
ph1 <- ph$mean
conductivity1 <- conductivity$mean
bod1 <- bod$mean
nitrate1 <- nitrate$mean
fecal1 <- fecal$mean
```

## TimeSeries
```{r}
if(state == 'MAHARASHTRA' | state == 'ODISHA' | state == 'RAJASTHAN' | state == 'UTTAR PRADESH' | state == 'WEST BENGAL'){
## custom
    temp_ts <-ts(temp1, start=c(2011, 1), end=c(2014, 1), frequency=1)
    temp_ts
    ph_ts <-ts(ph1, start=c(2011, 1), end=c(2014, 1), frequency=1)
    ph_ts
    conductivity_ts <-ts(conductivity1, start=c(2011, 1), end=c(2014, 1), frequency=1)
    conductivity_ts
    bod_ts <- ts(bod1, start=c(2011, 1), end=c(2014, 1), frequency=1)
    bod_ts
    nitrate_ts <- ts(nitrate1,  start=c(min(nitrate$YEAR), 1),  end=c(max(nitrate$YEAR),1), frequency=1)
    nitrate_ts
    fecal_ts <- ts(fecal1,  start=c(2011, 1), end=c(2014, 1), frequency=1)
    fecal_ts
} else {
##Automate
  temp_ts <-ts(temp1,  start=c(min(temp$YEAR), 1), end=c(max(temp$YEAR),1), frequency=1)
  temp_ts
  ph_ts <-ts(ph1,  start=c(min(ph$YEAR), 1), end=c(max(ph$YEAR),1), frequency=1)
  ph_ts
  conductivity_ts <-ts(conductivity1, start=c(min(conductivity$YEAR), 1), end=c(max(conductivity$YEAR),1), frequency=1)
  conductivity_ts
  bod_ts <- ts(bod1,  start=c(min(bod$YEAR), 1), end=c(max(bod$YEAR),1), frequency=1)
  bod_ts
  nitrate_ts <- ts(nitrate1,  start=c(min(nitrate$YEAR), 1), end=c(max(nitrate$YEAR),1), frequency=1)
  nitrate_ts
  fecal_ts <- ts(fecal1,  start=c(min(fecal$YEAR), 1), end=c(max(fecal$YEAR),1), frequency=1)
  fecal_ts
}
```


## TimeSeries Plots
```{r}
plot(temp_ts)
plot(ph_ts)
plot(conductivity_ts)
plot(bod_ts)
plot(nitrate_ts)
plot(fecal_ts)
```


# Holt Winters


## Temprature
```{r}
fit_temp_ts <- HoltWinters(temp_ts, gamma=FALSE)
fit_temp_ts 
pred_temp_ts <- forecast(fit_temp_ts,3)

flag <- FALSE
for ( i in pred_temp_ts$mean)  if ( i < 0) flag <- TRUE
if (flag == TRUE)
  fit_temp_ts <- HoltWinters(temp_ts, beta = FALSE, gamma=FALSE)
  fit_temp_ts 
  pred_temp_ts <- forecast(fit_temp_ts,3)
  
plot(pred_temp_ts)
pred_temp_ts 

```

## pH 

```{r}
fit_ph_ts <- HoltWinters(ph_ts, gamma=FALSE)
fit_ph_ts 
pred_ph_ts <- forecast(fit_ph_ts,3)


flag <- FALSE
for ( i in pred_ph_ts$mean)  if ( i < 0) flag <- TRUE
if (flag == TRUE)
  fit_ph_ts <- HoltWinters(ph_ts, beta = FALSE, gamma=FALSE)
  fit_ph_ts 
  pred_ph_ts <- forecast(fit_ph_ts,3)

plot(pred_ph_ts)
pred_ph_ts 
  
```

## Conductivity

```{r}
fit_conductivity_ts <- HoltWinters(conductivity_ts, gamma=FALSE)
fit_conductivity_ts 
pred_conductivity_ts <- forecast(fit_conductivity_ts,3)


flag <- FALSE
for ( i in pred_conductivity_ts$mean)  if ( i < 0) flag <- TRUE
if (flag == TRUE)
  fit_conductivity_ts <- HoltWinters(conductivity_ts,beta = FALSE, gamma=FALSE)
  fit_conductivity_ts 
  pred_conductivity_ts <- forecast(fit_conductivity_ts,3)

plot(pred_conductivity_ts)
pred_conductivity_ts
```

## BOD 

```{r}
fit_bod_ts <- HoltWinters(bod_ts, gamma=FALSE)
fit_bod_ts 
pred_bod_ts <- forecast(fit_bod_ts,3)


flag <- FALSE
for ( i in pred_bod_ts$mean)  if ( i < 0) flag <- TRUE
if (flag == TRUE)
  fit_bod_ts <- HoltWinters(bod_ts, beta = FALSE,gamma=FALSE)
  fit_bod_ts 
  pred_bod_ts <- forecast(fit_bod_ts,3)  
plot(pred_bod_ts)
pred_bod_ts

```

## Nitrate

```{r}
fit_nitrate_ts <- HoltWinters(nitrate_ts, gamma=FALSE)
fit_nitrate_ts 
pred_nitrate_ts <- forecast(fit_nitrate_ts,3)


flag <- FALSE
for ( i in pred_nitrate_ts$mean)  if ( i < 0) flag <- TRUE
if (flag == TRUE)
  fit_nitrate_ts <- HoltWinters(nitrate_ts,beta = FALSE, gamma=FALSE)
  fit_nitrate_ts 
  pred_nitrate_ts <- forecast(fit_nitrate_ts,3)  

plot(pred_nitrate_ts)
pred_nitrate_ts

```

## Fecal

```{r}
fit_fecal_ts <- HoltWinters(fecal_ts, gamma=FALSE)
fit_fecal_ts 
pred_fecal_ts <- forecast(fit_fecal_ts,3)


flag <- FALSE
for ( i in pred_fecal_ts$mean)  if ( i < 0) flag <- TRUE
if (flag == TRUE)
  fit_fecal_ts <- HoltWinters(fecal_ts, beta = FALSE, gamma=FALSE)
  fit_fecal_ts 
  pred_fecal_ts <- forecast(fit_fecal_ts,3)
  
plot(pred_fecal_ts)
pred_fecal_ts

```