Nothing
R/ChannelAttributionApp.R
In ChannelAttributionApp: Shiny Web Application for the Multichannel Attribution Problem
Defines functions
CAapp
Documented in
CAapp
# ChannelAttribution: Markov model for online multi-channel attribution
# Copyright (C) 2015 - 2020 Davide Altomare and David Loris <http://www.channelattribution.net>
# ChannelAttribution is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# ChannelAttribution is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with ChannelAttribution. If not, see <http://www.gnu.org/licenses/>.
require(ChannelAttribution)
require(shiny)
require(DT)
require(data.table)
require(ggplot2)
env0=new.env()
env0$exe_demo=0
env0$R=0
data(PathData,envir=env0)
CAapp=function(){
ca_app=shinyApp(
ui = bootstrapPage(
navbarPage(strong("CHANNEL ATTRIBUTION TOOL"), id="InOut",
tabPanel("Input",
fluidPage(
fluidRow(
column(2, "SELECT INPUT",
tags$hr(),
actionButton("demoData", "Load Demo Data"),
tags$hr(),
fileInput('file1', 'Load Input File',
accept=c('text/csv', 'text/comma-separated-values,text/plain', '.csv')),
radioButtons('sep', 'Path Separator', c(Comma=',',Semicolon=';',Tab='\t'),'Semicolon'),
tags$hr(),
uiOutput('var_path'),
uiOutput('var_conv'),
uiOutput('var_value'),
uiOutput('var_null'),
tags$hr(),
selectInput("order", "Markov model order:",c("1","2","3","4","5"),"1"),
tags$hr(),
actionButton(inputId="runButton", "Run")
),
column(10, "VIEW INPUT (FIRST 100 ROW)", tags$hr(),
tabPanel('Data', dataTableOutput('Data'))
)
)#end fluidrow
)#end fluidpage
),#end tabpanel
tabPanel("Output",
fluidPage(
fluidRow(
column(3,
selectInput("dataout", "Choose Output:", choices=c("Results")),
downloadButton('downloadData', 'Download')
),
column(8, "View Output", tags$hr(),
plotOutput('plot1'),
br(),
br(),
plotOutput('plot2'),
br(),
br(),
tabPanel('Results', dataTableOutput('R'))
)
)
)
)#end tabsetpanel
)#end navbarpage
), #end ui
server=function(input, output, session){
observe({
if(input$runButton>0) {
updateTabsetPanel(session, "InOut", selected = "Output")
}else{
updateTabsetPanel(session, "InOut", selected = "Input")
}
})
#Demo Data
execute=observeEvent(input$demoData, {
env0$exe_demo=1
output$Data=renderDataTable({
env0$Data
}, options=list(pageLength=10))
output$var_path=renderUI({
selectInput('var_path', 'Path Variable',c("",colnames(env0$Data)),selected="path")
})
output$var_conv=renderUI({
selectInput('var_conv', 'Conversion Variable',c("",colnames(env0$Data)),selected="total_conversions")
})
output$var_value=renderUI({
selectInput('var_value', 'Value Variable',c("",colnames(env0$Data)),selected="total_conversion_value")
})
output$var_null=renderUI({
selectInput('var_null', 'Null Variable',c("",colnames(env0$Data)),selected="total_null")
})
})
execute=observeEvent(input$file1, {
env0$exe_demo=0
#Load Data
output$Data=renderDataTable({
inFile=input$file1
if(is.null(inFile)){return(NULL)}
#tmp0=readLines(con=inFile$datapath, n=200)
tab0=fread(inFile$datapath,sep=input$sep,nrows=200)
#tab0=fread(paste0(tmp0,collapse="\n "),sep=input$sep,nrows=100)
}, options=list(pageLength=10))
output$var_path=renderUI({
inFile=input$file1
if(is.null(inFile)){return(NULL)}
#tmp0=readLines(con=inFile$datapath, n=200)
# tab0=fread(inFile$datapath,sep=input$sep,nrows=200)
tab0=fread(inFile$datapath,sep=input$sep,nrows=1)
selectInput('var_path', 'Path Variable', c("",colnames(tab0)))
})
output$var_conv=renderUI({
inFile=input$file1
if(is.null(inFile)){return(NULL)}
#tmp0=readLines(con=inFile$datapath, n=200)
tab0=fread(inFile$datapath,sep=input$sep,nrows=1)
#tab0=fread(paste0(tmp0,collapse="\n "),sep=input$sep,nrows=1)
selectInput('var_conv', 'Conversion Variable', c("",colnames(tab0)))
})
output$var_value=renderUI({
inFile=input$file1
if(is.null(inFile)){return(NULL)}
#tmp0=readLines(con=inFile$datapath, n=200)
tab0=fread(inFile$datapath,sep=input$sep,nrows=1)
#tab0=fread(paste0(tmp0,collapse="\n "),sep=input$sep,nrows=1)
selectInput('var_value', 'Value Variable', c("",colnames(tab0)))
})
output$var_null=renderUI({
inFile=input$file1
#tmp0=readLines(con=inFile$datapath, n=200)
tab0=fread(inFile$datapath,sep=input$sep,nrows=1)
#tab0=fread(paste0(tmp0,collapse="\n "),sep=input$sep,nrows=1)
selectInput('var_null', 'Null Variable', c("",colnames(tab0)))
})
})
datasetOutput=reactive({
switch(input$dataout,
"Results" = "R")
})
output$downloadData=downloadHandler(
filename = function(){
paste0(input$dataout, '.csv')
},
content=function(file){
#out=fread(paste0(datasetOutput(),".csv"), header=TRUE, sep=";")
write.table(env0$R, file, col.names=TRUE, row.names=FALSE, quote=FALSE, sep=";")
}
)
execute=observeEvent(input$runButton, {
withProgress(message = 'Executing: ', value = 0, {
incProgress(1/2, detail="Start (1/2)")
if(env0$exe_demo==0){
env0$Data=fread(input$file1$datapath, header=TRUE, sep=input$sep)
}
if(input$var_null!=""){var_null=input$var_null}else{var_null=NULL}
if(input$var_value!=""){var_value=input$var_value}else{var_value=NULL}
#HEURISTIC MODELS
H=heuristic_models(env0$Data,input$var_path,input$var_conv,var_value=var_value)
setDT(H)
#MARKOV MODEL
M=markov_model(env0$Data,input$var_path,input$var_conv,var_value=var_value,var_null=var_null,order=as.numeric(input$order))
setDT(M)
setkeyv(H,"channel_name")
setkeyv(M,"channel_name")
env0$R=merge(H,M,all=TRUE)
if(input$var_value!=""){
setnames(env0$R,c("total_conversion","total_conversion_value"),c("markov_conversions","markov_value"))
}else{
setnames(env0$R,c("first_touch","last_touch","linear_touch","total_conversions"),c("first_touch_conversions","last_touch_conversions","linear_touch_conversions","markov_conversions"))
}
# write.table(env0$R, "R.csv", col.names=TRUE, row.names=FALSE, quote=FALSE, sep=";")
#PLOT TOTAL CONVERSIONS
R1=env0$R[,c("channel_name","first_touch_conversions","last_touch_conversions","linear_touch_conversions","markov_conversions"),with=FALSE]
lnm=length(colnames(R1))
setnames(R1,c("channel_name","first_touch","last_touch","linear_touch","markov_model"))
R1=melt(R1,id="channel_name")
P1=ggplot(R1, aes_string("channel_name", "value", fill = "variable"))
P1=P1 +
geom_bar(stat="identity", position = "dodge") +
ggtitle("Total Conversions") +
theme(axis.title.x = element_text(vjust=-2))+
theme(axis.title.y = element_text(vjust=+2))+
theme(title = element_text(vjust=2))+
theme(text = element_text(size=16)) +
theme(plot.title=element_text(size=20)) +
labs(fill="") +
ylab("") +
xlab("")
#PLOT TOTAL VALUE
if(input$var_value!=""){
R2=env0$R[,c("channel_name","first_touch_value","last_touch_value","linear_touch_value","markov_value"),with=FALSE]
lnm=length(colnames(R2))
setnames(R2,1:lnm,c("channel_name","first_touch","last_touch","linear_touch","markov_model"))
}else{
R2=env0$R[,c("channel_name","first_touch_conversions","last_touch_conversions","linear_touch_conversions","markov_conversions"),with=FALSE]
lnm=length(colnames(R2))
setnames(R2,1:lnm,c("channel_name","first_touch","last_touch","linear_touch","markov_model"))
R2[,c("first_touch","last_touch","linear_touch","markov_model"):=0]
}
R2=melt(R2,id="channel_name")
P2=ggplot(R2, aes_string("channel_name", "value", fill = "variable"))
P2=P2 +
geom_bar(stat="identity", position = "dodge") +
ggtitle("Total Conversion Value") +
theme(axis.title.x = element_text(vjust=-2))+
theme(axis.title.y = element_text(vjust=+2))+
theme(title = element_text(vjust=2))+
theme(text = element_text(size=16)) +
theme(plot.title=element_text(size=20)) +
labs(fill="") +
ylab("") +
xlab("")
incProgress(2/2, detail="End (2/2)")
})
output$plot1=renderPlot({
P1
})
output$plot2=renderPlot({
P2
})
output$R=renderDataTable({
env0$R
}, options=list(pageLength=10))
observe({
updateTabsetPanel(session, "tabsetId", selected = "Output")
})
})
}#end server
)#end App
runApp(ca_app,launch.browser=TRUE)
}
Try the ChannelAttributionApp package in your browser
Any scripts or data that you put into this service are public.
ChannelAttributionApp documentation built on July 14, 2020, 5:07 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions CAapp
Documented in CAapp
# ChannelAttribution: Markov model for online multi-channel attribution
# Copyright (C) 2015 - 2020 Davide Altomare and David Loris <http://www.channelattribution.net>
# ChannelAttribution is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# ChannelAttribution is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with ChannelAttribution. If not, see <http://www.gnu.org/licenses/>.
require(ChannelAttribution)
require(shiny)
require(DT)
require(data.table)
require(ggplot2)
env0=new.env()
env0$exe_demo=0
env0$R=0
data(PathData,envir=env0)
CAapp=function(){
ca_app=shinyApp(
ui = bootstrapPage(
navbarPage(strong("CHANNEL ATTRIBUTION TOOL"), id="InOut",
tabPanel("Input",
fluidPage(
fluidRow(
column(2, "SELECT INPUT",
tags$hr(),
actionButton("demoData", "Load Demo Data"),
tags$hr(),
fileInput('file1', 'Load Input File',
accept=c('text/csv', 'text/comma-separated-values,text/plain', '.csv')),
radioButtons('sep', 'Path Separator', c(Comma=',',Semicolon=';',Tab='\t'),'Semicolon'),
tags$hr(),
uiOutput('var_path'),
uiOutput('var_conv'),
uiOutput('var_value'),
uiOutput('var_null'),
tags$hr(),
selectInput("order", "Markov model order:",c("1","2","3","4","5"),"1"),
tags$hr(),
actionButton(inputId="runButton", "Run")
),
column(10, "VIEW INPUT (FIRST 100 ROW)", tags$hr(),
tabPanel('Data', dataTableOutput('Data'))
)
)#end fluidrow
)#end fluidpage
),#end tabpanel
tabPanel("Output",
fluidPage(
fluidRow(
column(3,
selectInput("dataout", "Choose Output:", choices=c("Results")),
downloadButton('downloadData', 'Download')
),
column(8, "View Output", tags$hr(),
plotOutput('plot1'),
br(),
br(),
plotOutput('plot2'),
br(),
br(),
tabPanel('Results', dataTableOutput('R'))
)
)
)
)#end tabsetpanel
)#end navbarpage
), #end ui
server=function(input, output, session){
observe({
if(input$runButton>0) {
updateTabsetPanel(session, "InOut", selected = "Output")
}else{
updateTabsetPanel(session, "InOut", selected = "Input")
}
})
#Demo Data
execute=observeEvent(input$demoData, {
env0$exe_demo=1
output$Data=renderDataTable({
env0$Data
}, options=list(pageLength=10))
output$var_path=renderUI({
selectInput('var_path', 'Path Variable',c("",colnames(env0$Data)),selected="path")
})
output$var_conv=renderUI({
selectInput('var_conv', 'Conversion Variable',c("",colnames(env0$Data)),selected="total_conversions")
})
output$var_value=renderUI({
selectInput('var_value', 'Value Variable',c("",colnames(env0$Data)),selected="total_conversion_value")
})
output$var_null=renderUI({
selectInput('var_null', 'Null Variable',c("",colnames(env0$Data)),selected="total_null")
})
})
execute=observeEvent(input$file1, {
env0$exe_demo=0
#Load Data
output$Data=renderDataTable({
inFile=input$file1
if(is.null(inFile)){return(NULL)}
#tmp0=readLines(con=inFile$datapath, n=200)
tab0=fread(inFile$datapath,sep=input$sep,nrows=200)
#tab0=fread(paste0(tmp0,collapse="\n "),sep=input$sep,nrows=100)
}, options=list(pageLength=10))
output$var_path=renderUI({
inFile=input$file1
if(is.null(inFile)){return(NULL)}
#tmp0=readLines(con=inFile$datapath, n=200)
# tab0=fread(inFile$datapath,sep=input$sep,nrows=200)
tab0=fread(inFile$datapath,sep=input$sep,nrows=1)
selectInput('var_path', 'Path Variable', c("",colnames(tab0)))
})
output$var_conv=renderUI({
inFile=input$file1
if(is.null(inFile)){return(NULL)}
#tmp0=readLines(con=inFile$datapath, n=200)
tab0=fread(inFile$datapath,sep=input$sep,nrows=1)
#tab0=fread(paste0(tmp0,collapse="\n "),sep=input$sep,nrows=1)
selectInput('var_conv', 'Conversion Variable', c("",colnames(tab0)))
})
output$var_value=renderUI({
inFile=input$file1
if(is.null(inFile)){return(NULL)}
#tmp0=readLines(con=inFile$datapath, n=200)
tab0=fread(inFile$datapath,sep=input$sep,nrows=1)
#tab0=fread(paste0(tmp0,collapse="\n "),sep=input$sep,nrows=1)
selectInput('var_value', 'Value Variable', c("",colnames(tab0)))
})
output$var_null=renderUI({
inFile=input$file1
#tmp0=readLines(con=inFile$datapath, n=200)
tab0=fread(inFile$datapath,sep=input$sep,nrows=1)
#tab0=fread(paste0(tmp0,collapse="\n "),sep=input$sep,nrows=1)
selectInput('var_null', 'Null Variable', c("",colnames(tab0)))
})
})
datasetOutput=reactive({
switch(input$dataout,
"Results" = "R")
})
output$downloadData=downloadHandler(
filename = function(){
paste0(input$dataout, '.csv')
},
content=function(file){
#out=fread(paste0(datasetOutput(),".csv"), header=TRUE, sep=";")
write.table(env0$R, file, col.names=TRUE, row.names=FALSE, quote=FALSE, sep=";")
}
)
execute=observeEvent(input$runButton, {
withProgress(message = 'Executing: ', value = 0, {
incProgress(1/2, detail="Start (1/2)")
if(env0$exe_demo==0){
env0$Data=fread(input$file1$datapath, header=TRUE, sep=input$sep)
}
if(input$var_null!=""){var_null=input$var_null}else{var_null=NULL}
if(input$var_value!=""){var_value=input$var_value}else{var_value=NULL}
#HEURISTIC MODELS
H=heuristic_models(env0$Data,input$var_path,input$var_conv,var_value=var_value)
setDT(H)
#MARKOV MODEL
M=markov_model(env0$Data,input$var_path,input$var_conv,var_value=var_value,var_null=var_null,order=as.numeric(input$order))
setDT(M)
setkeyv(H,"channel_name")
setkeyv(M,"channel_name")
env0$R=merge(H,M,all=TRUE)
if(input$var_value!=""){
setnames(env0$R,c("total_conversion","total_conversion_value"),c("markov_conversions","markov_value"))
}else{
setnames(env0$R,c("first_touch","last_touch","linear_touch","total_conversions"),c("first_touch_conversions","last_touch_conversions","linear_touch_conversions","markov_conversions"))
}
# write.table(env0$R, "R.csv", col.names=TRUE, row.names=FALSE, quote=FALSE, sep=";")
#PLOT TOTAL CONVERSIONS
R1=env0$R[,c("channel_name","first_touch_conversions","last_touch_conversions","linear_touch_conversions","markov_conversions"),with=FALSE]
lnm=length(colnames(R1))
setnames(R1,c("channel_name","first_touch","last_touch","linear_touch","markov_model"))
R1=melt(R1,id="channel_name")
P1=ggplot(R1, aes_string("channel_name", "value", fill = "variable"))
P1=P1 +
geom_bar(stat="identity", position = "dodge") +
ggtitle("Total Conversions") +
theme(axis.title.x = element_text(vjust=-2))+
theme(axis.title.y = element_text(vjust=+2))+
theme(title = element_text(vjust=2))+
theme(text = element_text(size=16)) +
theme(plot.title=element_text(size=20)) +
labs(fill="") +
ylab("") +
xlab("")
#PLOT TOTAL VALUE
if(input$var_value!=""){
R2=env0$R[,c("channel_name","first_touch_value","last_touch_value","linear_touch_value","markov_value"),with=FALSE]
lnm=length(colnames(R2))
setnames(R2,1:lnm,c("channel_name","first_touch","last_touch","linear_touch","markov_model"))
}else{
R2=env0$R[,c("channel_name","first_touch_conversions","last_touch_conversions","linear_touch_conversions","markov_conversions"),with=FALSE]
lnm=length(colnames(R2))
setnames(R2,1:lnm,c("channel_name","first_touch","last_touch","linear_touch","markov_model"))
R2[,c("first_touch","last_touch","linear_touch","markov_model"):=0]
}
R2=melt(R2,id="channel_name")
P2=ggplot(R2, aes_string("channel_name", "value", fill = "variable"))
P2=P2 +
geom_bar(stat="identity", position = "dodge") +
ggtitle("Total Conversion Value") +
theme(axis.title.x = element_text(vjust=-2))+
theme(axis.title.y = element_text(vjust=+2))+
theme(title = element_text(vjust=2))+
theme(text = element_text(size=16)) +
theme(plot.title=element_text(size=20)) +
labs(fill="") +
ylab("") +
xlab("")
incProgress(2/2, detail="End (2/2)")
})
output$plot1=renderPlot({
P1
})
output$plot2=renderPlot({
P2
})
output$R=renderDataTable({
env0$R
}, options=list(pageLength=10))
observe({
updateTabsetPanel(session, "tabsetId", selected = "Output")
})
})
}#end server
)#end App
runApp(ca_app,launch.browser=TRUE)
}
Try the ChannelAttributionApp package in your browser
Any scripts or data that you put into this service are public.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.