DDP Wk3 Plotly

Plotting Brisket Temperatures

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Sys.Date()

## [1] "2022-10-05"

We will plot Brisket Temperatures over time (measured in minutes) for four different cooks.

Slide with Plotly plot

library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(plotly)

## Loading required package: ggplot2

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
## 
##     layout

bdata <- read.csv("~/BData.txt")
bdata$DateTime <- as.POSIXct(bdata$DateTime)

startTimes <- summarize( group_by(bdata,Name), start = min(DateTime))

## `summarise()` ungrouping output (override with `.groups` argument)

bdata <- inner_join(bdata,startTimes)

## Joining, by = "Name"

bdata$time_in_minutes <- difftime(bdata$DateTime, bdata$start,units="mins")
bdata<-rename(bdata,MeatTemp_degF=MeatTemp,GrillTemp_degF=GrillTemp)

#bdata$Time <- (bdata$DateTime)$min
p <- plot_ly(bdata,x= ~time_in_minutes,y=~MeatTemp_degF)
#p1 <- add_markers(p, symbol=~Name,size=8,color=~GrillTemp_degF,symbols=c("circle","triangle-up","square","diamond","pentagon"))
#p1 <- add_paths(p1, linetype=~Phase, color=I("black"))  #="solid",width=as.integer(as.factor(bdata$Phase))*4)
p2 <- add_markers(p, symbol=~Phase,size=10,color=~GrillTemp_degF,symbols=c("circle","diamond"),colors="YlOrRd")
p3 <- add_paths(p2, linetype=~Name)   #, color=~Name, colors="Greys")    #="solid",width=as.integer(as.factor(bdata$Phase))*4)
#p1
p3