Row {data-height=60}

fertilizerAdviseTable()
#source("fertilizer advise table.R")
knitr::include_graphics("alogo.png")

Row {data-height=160}

What you told us

#library(kableExtra)

knitr::opts_chunk$set(echo = TRUE)
options(knitr.kable.NA = '')

personalized_info <- read.csv("MarkDownTextD.csv", stringsAsFactors = FALSE)

 if (file.exists("datall1.csv")) {
  da1<-read.csv("datall1.csv", stringsAsFactors = FALSE)
  costt <- formatC(signif(da1$total_cost1, digits=3), format="f", big.mark=",", digits=0)
  da1title1 <-  paste("Urea application:  ", da1$kgs1, " kg for ", da1$field_area, " (~",  da1$bags1," bags of 50 kg)", " = ",
                    costt, da1$currency, sep=" ")
  da1bag <-da1[,c("rep1")]

}else{
  da1 <- NULL
}

if (file.exists("datall2.csv")){
  da2 <-read.csv("datall2.csv", stringsAsFactors = FALSE)
  cost2 <- formatC(signif(da2$total_cost2, digits=3), format="f", big.mark=",", digits=0)
  da2title1 <- paste( "NPK 15:15:15; ", da2$kgs2, " kg for ", da2$field_area, " (~",  da2$bags2," bags of 50 kg)", " = ",
                      cost2, da2$currency, sep=" ")
  da2bag <-da2[,c("rep2")]
} else{
  da2 <- NULL
}
if (file.exists("datall3.csv")){
  da3<-read.csv("datall3.csv", stringsAsFactors = FALSE)
  cost3 <- formatC(signif(da3$total_cost3, digits=3), format="f", big.mark=",", digits=0)
 da3title1 <- paste("NPK 20:10:10; ", da3$kgs3, " kg for ", da3$field_area, " (~",  da3$bags3," bags of 50 kg)", " = ",
                    cost3,   da3$currency, sep=" ")
  da3bag <-da3[,c("rep3")]
}else{
  da3 <- NULL
}
if (file.exists("datall4.csv")) {
  da4<-read.csv("datall4.csv", stringsAsFactors = FALSE)
  cost4 <- formatC(signif(da4$total_cost4, digits=3), format="f", big.mark=",", digits=0)
  da4title1 <- paste("MOP application: ", da4$kgs4, " kg for ", da4$field_area, " (~",  da4$bags4," bags of 50 kg)"," = ",
                    cost4,   da4$currency, sep=" ")
  da4bag <-da4[,c("rep4")]
}else{
  da4 <- NULL
}

totalRevenuemoney <-read.csv("totalRevenuemoney.csv")
totalSalemoney <-read.csv("totalSalemoney.csv")
totalCostmoney <-read.csv("totalCostmoney.csv")



# for (i in 1:nrow(personalized_info)){
# # 
 name <- personalized_info$name
   phone <- as.character(personalized_info$phone)
   field <- personalized_info$field
  field_area <- personalized_info$field_area
   plant_date <- personalized_info$plant_date
   hvst_date <- personalized_info$hvst_date
   current_yield<- personalized_info$current_yield

Your name: r name,

Phone: r phone

Your field: r field

Field area: r field_area

Planting date: r plant_date

Harvest date: r hvst_date

Your current yield: r current_yield

Available fertilizers

personalized_info <- read.csv("MarkDownTextD.csv", stringsAsFactors = FALSE)

# personalized_info <- read.csv("MarkDownTextD.csv", stringsAsFactors = FALSE)
dds <- data.frame(fertname = as.character(personalized_info$fertilizer1), cost=c(personalized_info$cost1),
                  units = as.character(personalized_info$unit1), currency=as.character(personalized_info$currency))
dds <- rbind(dds, data.frame(fertname = as.character(personalized_info$fertilizer2), cost=c(personalized_info$cost2),
                  units = as.character(personalized_info$unit2), currency=personalized_info$currency))
dds <- rbind(dds, data.frame(fertname = as.character(personalized_info$fertilizer3), cost=c(personalized_info$cost3),
                             units = as.character(personalized_info$unit3), currency=personalized_info$currency))
dds <- rbind(dds, data.frame(fertname = as.character(personalized_info$fertilizer4), cost=c(personalized_info$cost4),
                             units = as.character(personalized_info$unit4), currency=personalized_info$currency))
dds <- droplevels(dds[!is.na(dds$cost), ])

dds$cost2 <- formatC(signif(dds$cost, digits=3), format="f", big.mark=",", digits=0)

intextText <- NULL
for(k in 1:nrow(dds)){
  dds2 <- data.frame(tbp = paste(" @", dds$cost2[k], " ", dds$currency[k], " per ", dds$units[k], sep=""))
  intextText <- rbind(intextText, dds2 )
}

ureatext <- intextText[1,]
npk151515text <- intextText[2,]
npk201010text <- intextText[3,]
MOPtext <- intextText[4,]

costcassava <- formatC(signif(personalized_info$costcassava, digits=3), format="f", big.mark=",", digits=0)
unitcassava <- personalized_info$unitcassava
maxinvest <- formatC(signif(personalized_info$maxinvest, digits=3), format="f", big.mark=",", digits=0)
area <- personalized_info$field_area
cas_unit <- personalized_info$unit_field 
currency <- personalized_info$currency

Urea r ureatext

NPK15:15:15 r npk151515text

NPK20:10:10 r npk201010text

MOP r MOPtext

Cassava sold perr unitcassava @ r costcassava r currency

Maximal investment: r maxinvest for r area

Your farm location

geodata <- read.csv("MarkDownTextD.csv", stringsAsFactors = FALSE)

#geodata <- read.csv(file = "MarkDownTextD.csv", header = TRUE,  sep = "," )
data <- subset(geodata[1,], select = c("name", "latitude", "longitude"))

minLong=data$longitude - 0.05
maxLong=data$longitude + 0.05
minLat=data$latitude - 0.05
maxLat=data$latitude + 0.05
library(leaflet)
library(mapview)
my_map <- data %>%
  #leaflet(width = "100%") %>%
  #leaflet(options= leafletOptions(minZoom = 3, maxZoom = 10)) %>%
  leaflet(options= leafletOptions(minZoom = 8, maxZoom = 10)) %>%
  addProviderTiles(providers$Esri.WorldImagery)%>%
  #setView(lng = -95.7129, lat = 37.0902, zoom = 4) %>%

  # addMarkers(~longitude, ~latitude
  #          )%>% 
  #addRectangles(lat1 = minLat, lng1 = minLong, lat2 = maxLat, lng2 = maxLong)%>% 
  addCircleMarkers(~longitude, ~latitude, color="white", fillColor = "transparent", weight = 10, radius = 30)%>% 

  addScaleBar()
#addTiles()
mm <- "my_map.png"
if (file.exists(mm)) file.remove(mm)

mapshot(my_map, file="my_map.png")

Row {data-height=240}

We recommend...

 options(knitr.table.format = 'markdown')

 if(!is.null(da1)){
   knitr::kable(da1title1, col.names = NULL, row.names = F) 
 }
wzxhzdk:5
wzxhzdk:6
wzxhzdk:7
wzxhzdk:8
wzxhzdk:9
wzxhzdk:10
wzxhzdk:11

Expected gain in total production:

currency<- personalized_info$currency
bags_total100<- (personalized_info$bags_total)*10
bags_total <- personalized_info$bags_total
product <- personalized_info$product
unitcassava <- personalized_info$unitcassava
final_cost<- personalized_info$totalSalePrice
revenue <- personalized_info$revenue

r bags_total tonnes of cassava roots: ~ r bags_total100 bags of 100 kg r product


Total cost: r totalCostmoney

Total calculated revenue: r totalSalemoney


Your expected net revenue: r totalRevenuemoney



fatelord/cropmanager documentation built on June 4, 2019, 4:06 p.m.