In clemlaflemme/Oxom: Création de rapports à partir de données Weborama et Mediarithmics
library(knitr)
library(ggplot2)
library(tidyr)
library(dplyr)
knitr::opts_chunk$set(fig.path='figure/',
cache.path='cache/',
fig.width=6,
fig.height=3.5,
cache=TRUE)
Chargement des données datées
Weborama
# Set working directory (automatic with compilation)
setwd('/Volumes/Stockage/Google Drive/Oxom/Rapport/')
# import data
dt.prosp <- readxl::read_excel("../Data/skaze/Data/20161226_ReportingSkaze_SonVideo.xlsx", sheet = "Prospecting")
dt.prosp$Target <- 'Prospecting'
dt.retar <- readxl::read_excel("../Data/skaze/Data/20161226_ReportingSkaze_SonVideo.xlsx", sheet = "Retargeting")
dt.retar$Target <- 'Retargeting'
dt <- dt.prosp %>% bind_rows(dt.retar)
ventes.weborama <- dt[c('Date', 'TOTAL Vente')]
ventes.weborama$Total <- ventes.weborama$`TOTAL Vente`
ventes.weborama$`TOTAL Vente` <- NULL
ventes.weborama$DSP <- 'Weborama'
ventes.weborama$Date <- lubridate::as_date(ventes.weborama$Date)
Conversion des entrées textuelles en facteurs ou nombres
dt$Spent <- dt$Budget
dt$Budget <- NULL
dt$Date <- lubridate::ymd(dt$Date)
dt$Month <- format(dt$Date, "%B")
dt$Week <- format(dt$Date, "%V")
dt$NumDay <- format(dt$Date, "%j")
dt$NameDay <- format(dt$Date, "%A")
dt$DSP <- "Weborama"
Mediarithmics
# Mediaryhtmics
dt.media <- readxl::read_excel('../Data/skaze/Data/SONVIDEO - Mediarithmics.xlsx', sheet = 2)
dt.media$Impressions[is.na(dt.media$Impressions)] <- 0
dt.media$Clicks[is.na(dt.media$Clicks)] <- 0
dt.media$Spent[is.na(dt.media$Spent)] <- 0
dt.media$CPM <- dt.media$Spent/dt.media$Impressions*1000
dt.media$CPC <- dt.media$Spent/dt.media$Clicks
dt.media$CTR <- dt.media$Clicks/dt.media$Impressions*100
dt.media$Ad <- sapply(strsplit(dt.media$Ad, split = "_"), function(v) {
res <- tail(v, 1);
if(nchar(res)==1) res <- paste0("V", res)
res
})
dt.media$DSP <- "Mediarithmics"
dt.media$Date <- lubridate::as_date(dt.media$Date)
dt.media$Month <- format(dt.media$Date, "%B")
dt.media$Week <- format(dt.media$Date, "%V")
dt.media$NumDay <- format(dt.media$Date, "%j")
dt.media$NameDay <- format(dt.media$Date, "%A")
ventes.media <- readxl::read_excel('../Data/skaze/Data/SONVIDEO - Mediarithmics.xlsx', sheet = 1)[c('Date', 'Total')]
ventes.media$Date <- lubridate::as_date(ventes.media$Date)
ventes.media$DSP <- 'Mediarithmics'
ventes <- ventes.weborama %>% bind_rows(ventes.media)
Fusion Weboram et Mediarithmics
dt <- dt %>% bind_rows(dt.media)
Chargement des données sur les ad
perf.global <- readxl::read_excel("../Data/skaze/Data/20161226_SonVideo_Size.xlsx", sheet = "DataView")
perf.global$Date <- lubridate::ymd(perf.global$Date)
perf.global$Size <- perf.global$Insertion
perf.global$Insertion <- NULL
perf.global$Ad <- sapply(strsplit(perf.global$Creative, split = "[_-]"), function(v) {
if(length(v)==1) {res <- "V1";}
else {res <- tail(v, 1);}
if(nchar(res)==1) res <- paste0("V", res);
return(res)
})
perf.global$Ad <- factor(perf.global$Ad, levels = unique(sort(perf.global$Ad)))
perf.global$Impressions <- perf.global$Imp.
perf.global$Imp. <- NULL
perf.global$Impressions[is.na(perf.global$Impressions)] <- 0
perf.global$Clicks <- as.numeric(gsub(pattern = "-", replacement = "0", x = perf.global$Clicks))
perf.global <- perf.global %>% group_by(Ad, Size) %>% summarise(Clicks = sum(Clicks), Impressions = sum(Impressions), CTR = sum(Clicks)/sum(Impressions)*100)
perf.global$DSP <- "Weborama"
perf.media <- dt.media %>% select(Ad, Size, Clicks, Impressions, Spent) %>% group_by(Ad, Size) %>% summarise_all(.funs='sum')
perf.media$DSP <- "Mediarithmics"
perf.global <- perf.global %>% bind_rows(perf.media) %>% select(Ad, Size, Clicks, Impressions, Spent, DSP)
perf.global$Ad <- factor(perf.global$Ad)
perf.global$Campaign <- NA
perf.global$`Ad group` <- NA
perf.global$Ventes <- NA
perf.global$CPC <- round(perf.global$Spent/perf.global$Clicks, 2)
perf.global$CPM <- round(perf.global$Spent/perf.global$Impressions*1000, 2)
perf.global$CTR <- round(perf.global$Clicks/perf.global$Impressions*100, 2)
perf.global$Spent <- round(perf.global$Spent, 2)
perf.global$CPA <- ''
df.names <- c('Campaign', 'DSP', 'Ad', 'Size', 'Impressions', 'Clicks', 'Ventes', 'Spent', 'CPC', 'CPM', 'CTR', 'CPA')
perf.global <- perf.global[df.names]
Création des tableaux à sortir
# create daily perf
perf.quot <- dt %>%
group_by(Date = as.numeric(NumDay)) %>%
summarise(Clicks = sum(Clicks), Spent = sum(Spent), Impressions = sum(Impressions)) %>%
merge(data.frame(Date = seq(from = min(as.numeric(dt$NumDay)), to = max(as.numeric(dt$NumDay)))), all = TRUE) %>%
mutate(Date = lubridate::as_date(strptime(Date, format = "%j"))) %>%
left_join(ventes %>%
group_by(Date) %>%
summarise(Ventes = sum(Total))) %>%
mutate(CPC = Spent/Clicks,
CPM = Spent/Impressions*1000,
CTR = Clicks/Impressions*100,
CPA = Spent/Ventes) %>%
mutate_all(.funs = function(x) round(x, digits = 2))
perf.quot$Date <- as.character(perf.quot$Date)
perf.hebdo <- dt %>%
group_by(Week = as.numeric(Week)) %>%
summarise(Clicks = sum(Clicks), Spent = sum(Spent), Impressions = sum(Impressions)) %>%
merge(data.frame(Week = seq(from = min(as.numeric(dt$Week)), to = max(as.numeric(dt$Week)))), all = TRUE) %>%
left_join(ventes %>%
group_by(Week = as.numeric(format(Date, "%V"))) %>%
summarise(Ventes = sum(Total))) %>%
mutate(CPC = Spent/Clicks,
CPM = Spent/Impressions*1000,
CTR = Clicks/Impressions*100,
CPA = Spent/Ventes) %>%
mutate_all(.funs = function(x) round(x, digits = 2))
perf.mens <- dt %>%
group_by(Month = factor(Month, levels = month.name)) %>%
summarise(Clicks = sum(Clicks), Spent = sum(Spent), Impressions = sum(Impressions)) %>%
left_join(ventes %>%
group_by(Month = factor(format(Date, "%B"), levels = month.name)) %>%
summarise(Ventes = sum(Total))) %>%
mutate(CPC = Spent/Clicks,
CPM = Spent/Impressions*1000,
CTR = Clicks/Impressions*100,
CPA = Spent/Ventes) %>%
mutate_at(.cols = vars(Spent, CPC, CPM, CTR, CPA), .funs = function(x) round(x, digits = 2))
perf <- list(quot = perf.quot, hebdo = perf.hebdo, mens = perf.mens, global = perf.global)
# perf par nom de l'ad
perf.ad <- perf.global %>% group_by(Ad) %>% summarise(
Size = '',
Impressions = sum(Impressions),
Clicks = sum(Clicks),
Spent = sum(Spent)) %>%
mutate(CPC = Spent/Clicks,
CPM = Spent/Impressions*1000,
CTR = Clicks/Impressions*100,
Ventes = '',
CPA = '') %>%
mutate_at(.cols = vars(Spent, CPC, CPM, CTR), function(x) round(x, digits = 2))
perf.ad <- perf.ad[tail(names(perf.global), -2)]
relevant.ad <- perf.ad$Ad[perf.ad$Impressions>0.1*mean(perf.ad$Impressions)]
# perf par taille de l'ad
perf.size <- perf.global %>% group_by(Size) %>% summarise(
Impressions = sum(Impressions),
Clicks = sum(Clicks),
Spent = sum(Spent)) %>%
mutate(CPC = Spent/Clicks,
CPM = Spent/Impressions*1000,
CTR = Clicks/Impressions*100,
Ventes = '',
CPA = '') %>%
mutate_at(.cols = vars(Spent, CPC, CPM, CTR), function(x) round(x, digits = 2))
perf.size <- perf.size[tail(names(perf.global), -3)]
# perf par DSP
perf.dsp <- perf.global %>% group_by(DSP) %>% summarise(
Ad = '',
Size = '',
Impressions = sum(Impressions),
Clicks = sum(Clicks),
Spent = sum(Spent))
# hack manque de donnees
perf.dsp[perf.dsp$DSP=='Weborama',]$Spent <- sum(dt[dt$DSP=="Weborama",]$Spent)
perf.dsp <- perf.dsp %>%
mutate(CPC = Spent/Clicks,
CPM = Spent/Impressions*1000,
CTR = Clicks/Impressions*100) %>%
mutate_at(.cols = vars(Spent, CPC, CPM, CTR), function(x) round(x, digits = 2)) %>%
left_join(ventes %>% group_by(DSP) %>% summarise(Ventes = sum(Total))) %>%
mutate(CPA = round(Spent/Ventes, digits = 2))
perf.dsp <- perf.dsp[tail(names(perf.global), -1)]
Write excel file
library(xlsx)
library(r2excel)
skaze.darkblue <- rgb(36/255, 116/255, 152/255)
skaze.grey <- rgb(217/255, 217/255, 217/255)
skaze.lightblue <- rgb(114/255, 179/255, 199/255)
skaze.palette <- colorRampPalette(c(skaze.lightblue, skaze.darkblue))
wb <- xlsx::loadWorkbook('../Rapport/Template.xlsx')
sheets <- xlsx::getSheets(wb)
suivi.global <- sheets$`Suivi Global`
suivi.quot <- sheets$`Suivi Quotidien`
suivi.hebdo <- sheets$`Suivi Hebdo`
suivi.mens <- sheets$`Suivi Mensuel`
suivi <- list(global = suivi.global, quot = suivi.quot, hebdo = suivi.hebdo, mens = suivi.mens)
campaign <- "Son-video"
ad_group <- "Retargeting + Prospect"
lapply(names(suivi), function(name){
if(name!="global"){
head <- paste("Campagne :", campaign, "; Ad group :", ad_group)
}
else {
head <- paste("Résultats globaux du", min(dt$Date), "au", max(dt$Date))
}
xlsx.addHeader(wb, suivi[[name]], value = head, startRow = 6, level = 3)
xlsx.addTable(wb, suivi[[name]], data = matrix(names(perf[[name]]), nrow = 1),
startRow = 8, startCol = 1, row.names = FALSE, col.names = FALSE,
fontColor = rgb(0, 0, 0), fontSize = 12, rowFill = skaze.darkblue)
xlsx.addTable(wb, suivi[[name]], data = as.data.frame(perf[[name]]),
startRow = 9, startCol = 1, row.names = FALSE, col.names = FALSE,
fontColor='grey30', fontSize=12,
rowFill=c(skaze.lightblue, skaze.grey)
)
})
start.row <- 9 + nrow(perf.global) + 1
xlsx.addTable(wb, suivi.global, data = as.data.frame(perf.dsp),
startRow = start.row, startCol = 2, row.names = FALSE, col.names = FALSE,
fontColor='grey30', fontSize=12,
rowFill=c(skaze.lightblue, skaze.grey)
)
start.row <- start.row + nrow(perf.dsp) + 1
xlsx.addTable(wb, suivi.global, data = as.data.frame(perf.ad),
startRow = start.row, startCol = 3, row.names = FALSE, col.names = FALSE,
fontColor='grey30', fontSize=12,
rowFill=c(skaze.lightblue, skaze.grey)
)
start.row <- start.row + nrow(perf.ad) + 1
xlsx.addTable(wb, suivi.global, data = as.data.frame(perf.size),
startRow = start.row, startCol = 4, row.names = FALSE, col.names = FALSE,
fontColor='grey30', fontSize=12,
rowFill=c(skaze.lightblue, skaze.grey)
)
start.row <- start.row + nrow(perf.size) + 1
xlsx.plot <- function(var, legend, filter = TRUE) {
if(filter) perf.global <- perf.global %>% filter(Ad %in% relevant.ad)
text=paste0('p <- ggplot(perf.global, aes(x=Size, y=',var,')) + geom_col(aes(fill = Ad), position = "dodge") + xlab(\'Ad size\') + scale_fill_manual(values = skaze.palette(6)) + theme_bw()')
if(!legend) text <- paste0(text, " + theme(legend.position = \'none\') ")
eval(parse(text = text))
print(p)
}
xlsx.addPlot(wb, sheets$Graphiques, function(){xlsx.plot('Impressions', legend = FALSE)}, startRow = 1, width = 300)
xlsx.addPlot(wb, sheets$Graphiques, function(){xlsx.plot('Clicks', legend = FALSE)}, width = 300, startRow = 1, startCol = 5)
xlsx.addPlot(wb, sheets$Graphiques, function(){xlsx.plot('CTR', legend = TRUE)}, width = 400, startRow = 1, startCol = 8)
saveWorkbook(wb, file = "son-video3.xlsx")
# xlsx.openFile('test.xlsx') # open file
clemlaflemme/Oxom documentation built on May 13, 2019, 7:40 p.m.
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library(knitr) library(ggplot2) library(tidyr) library(dplyr) knitr::opts_chunk$set(fig.path='figure/', cache.path='cache/', fig.width=6, fig.height=3.5, cache=TRUE)
Chargement des données datées
Weborama
# Set working directory (automatic with compilation) setwd('/Volumes/Stockage/Google Drive/Oxom/Rapport/') # import data dt.prosp <- readxl::read_excel("../Data/skaze/Data/20161226_ReportingSkaze_SonVideo.xlsx", sheet = "Prospecting") dt.prosp$Target <- 'Prospecting' dt.retar <- readxl::read_excel("../Data/skaze/Data/20161226_ReportingSkaze_SonVideo.xlsx", sheet = "Retargeting") dt.retar$Target <- 'Retargeting' dt <- dt.prosp %>% bind_rows(dt.retar) ventes.weborama <- dt[c('Date', 'TOTAL Vente')] ventes.weborama$Total <- ventes.weborama$`TOTAL Vente` ventes.weborama$`TOTAL Vente` <- NULL ventes.weborama$DSP <- 'Weborama' ventes.weborama$Date <- lubridate::as_date(ventes.weborama$Date)
Conversion des entrées textuelles en facteurs ou nombres
dt$Spent <- dt$Budget dt$Budget <- NULL dt$Date <- lubridate::ymd(dt$Date) dt$Month <- format(dt$Date, "%B") dt$Week <- format(dt$Date, "%V") dt$NumDay <- format(dt$Date, "%j") dt$NameDay <- format(dt$Date, "%A") dt$DSP <- "Weborama"
Mediarithmics
# Mediaryhtmics dt.media <- readxl::read_excel('../Data/skaze/Data/SONVIDEO - Mediarithmics.xlsx', sheet = 2) dt.media$Impressions[is.na(dt.media$Impressions)] <- 0 dt.media$Clicks[is.na(dt.media$Clicks)] <- 0 dt.media$Spent[is.na(dt.media$Spent)] <- 0 dt.media$CPM <- dt.media$Spent/dt.media$Impressions*1000 dt.media$CPC <- dt.media$Spent/dt.media$Clicks dt.media$CTR <- dt.media$Clicks/dt.media$Impressions*100 dt.media$Ad <- sapply(strsplit(dt.media$Ad, split = "_"), function(v) { res <- tail(v, 1); if(nchar(res)==1) res <- paste0("V", res) res }) dt.media$DSP <- "Mediarithmics" dt.media$Date <- lubridate::as_date(dt.media$Date) dt.media$Month <- format(dt.media$Date, "%B") dt.media$Week <- format(dt.media$Date, "%V") dt.media$NumDay <- format(dt.media$Date, "%j") dt.media$NameDay <- format(dt.media$Date, "%A") ventes.media <- readxl::read_excel('../Data/skaze/Data/SONVIDEO - Mediarithmics.xlsx', sheet = 1)[c('Date', 'Total')] ventes.media$Date <- lubridate::as_date(ventes.media$Date) ventes.media$DSP <- 'Mediarithmics' ventes <- ventes.weborama %>% bind_rows(ventes.media)
Fusion Weboram et Mediarithmics
dt <- dt %>% bind_rows(dt.media)
Chargement des données sur les ad
perf.global <- readxl::read_excel("../Data/skaze/Data/20161226_SonVideo_Size.xlsx", sheet = "DataView") perf.global$Date <- lubridate::ymd(perf.global$Date) perf.global$Size <- perf.global$Insertion perf.global$Insertion <- NULL perf.global$Ad <- sapply(strsplit(perf.global$Creative, split = "[_-]"), function(v) { if(length(v)==1) {res <- "V1";} else {res <- tail(v, 1);} if(nchar(res)==1) res <- paste0("V", res); return(res) }) perf.global$Ad <- factor(perf.global$Ad, levels = unique(sort(perf.global$Ad))) perf.global$Impressions <- perf.global$Imp. perf.global$Imp. <- NULL perf.global$Impressions[is.na(perf.global$Impressions)] <- 0 perf.global$Clicks <- as.numeric(gsub(pattern = "-", replacement = "0", x = perf.global$Clicks)) perf.global <- perf.global %>% group_by(Ad, Size) %>% summarise(Clicks = sum(Clicks), Impressions = sum(Impressions), CTR = sum(Clicks)/sum(Impressions)*100) perf.global$DSP <- "Weborama" perf.media <- dt.media %>% select(Ad, Size, Clicks, Impressions, Spent) %>% group_by(Ad, Size) %>% summarise_all(.funs='sum') perf.media$DSP <- "Mediarithmics" perf.global <- perf.global %>% bind_rows(perf.media) %>% select(Ad, Size, Clicks, Impressions, Spent, DSP) perf.global$Ad <- factor(perf.global$Ad) perf.global$Campaign <- NA perf.global$`Ad group` <- NA perf.global$Ventes <- NA perf.global$CPC <- round(perf.global$Spent/perf.global$Clicks, 2) perf.global$CPM <- round(perf.global$Spent/perf.global$Impressions*1000, 2) perf.global$CTR <- round(perf.global$Clicks/perf.global$Impressions*100, 2) perf.global$Spent <- round(perf.global$Spent, 2) perf.global$CPA <- '' df.names <- c('Campaign', 'DSP', 'Ad', 'Size', 'Impressions', 'Clicks', 'Ventes', 'Spent', 'CPC', 'CPM', 'CTR', 'CPA') perf.global <- perf.global[df.names]
Création des tableaux à sortir
# create daily perf perf.quot <- dt %>% group_by(Date = as.numeric(NumDay)) %>% summarise(Clicks = sum(Clicks), Spent = sum(Spent), Impressions = sum(Impressions)) %>% merge(data.frame(Date = seq(from = min(as.numeric(dt$NumDay)), to = max(as.numeric(dt$NumDay)))), all = TRUE) %>% mutate(Date = lubridate::as_date(strptime(Date, format = "%j"))) %>% left_join(ventes %>% group_by(Date) %>% summarise(Ventes = sum(Total))) %>% mutate(CPC = Spent/Clicks, CPM = Spent/Impressions*1000, CTR = Clicks/Impressions*100, CPA = Spent/Ventes) %>% mutate_all(.funs = function(x) round(x, digits = 2)) perf.quot$Date <- as.character(perf.quot$Date) perf.hebdo <- dt %>% group_by(Week = as.numeric(Week)) %>% summarise(Clicks = sum(Clicks), Spent = sum(Spent), Impressions = sum(Impressions)) %>% merge(data.frame(Week = seq(from = min(as.numeric(dt$Week)), to = max(as.numeric(dt$Week)))), all = TRUE) %>% left_join(ventes %>% group_by(Week = as.numeric(format(Date, "%V"))) %>% summarise(Ventes = sum(Total))) %>% mutate(CPC = Spent/Clicks, CPM = Spent/Impressions*1000, CTR = Clicks/Impressions*100, CPA = Spent/Ventes) %>% mutate_all(.funs = function(x) round(x, digits = 2)) perf.mens <- dt %>% group_by(Month = factor(Month, levels = month.name)) %>% summarise(Clicks = sum(Clicks), Spent = sum(Spent), Impressions = sum(Impressions)) %>% left_join(ventes %>% group_by(Month = factor(format(Date, "%B"), levels = month.name)) %>% summarise(Ventes = sum(Total))) %>% mutate(CPC = Spent/Clicks, CPM = Spent/Impressions*1000, CTR = Clicks/Impressions*100, CPA = Spent/Ventes) %>% mutate_at(.cols = vars(Spent, CPC, CPM, CTR, CPA), .funs = function(x) round(x, digits = 2)) perf <- list(quot = perf.quot, hebdo = perf.hebdo, mens = perf.mens, global = perf.global) # perf par nom de l'ad perf.ad <- perf.global %>% group_by(Ad) %>% summarise( Size = '', Impressions = sum(Impressions), Clicks = sum(Clicks), Spent = sum(Spent)) %>% mutate(CPC = Spent/Clicks, CPM = Spent/Impressions*1000, CTR = Clicks/Impressions*100, Ventes = '', CPA = '') %>% mutate_at(.cols = vars(Spent, CPC, CPM, CTR), function(x) round(x, digits = 2)) perf.ad <- perf.ad[tail(names(perf.global), -2)] relevant.ad <- perf.ad$Ad[perf.ad$Impressions>0.1*mean(perf.ad$Impressions)] # perf par taille de l'ad perf.size <- perf.global %>% group_by(Size) %>% summarise( Impressions = sum(Impressions), Clicks = sum(Clicks), Spent = sum(Spent)) %>% mutate(CPC = Spent/Clicks, CPM = Spent/Impressions*1000, CTR = Clicks/Impressions*100, Ventes = '', CPA = '') %>% mutate_at(.cols = vars(Spent, CPC, CPM, CTR), function(x) round(x, digits = 2)) perf.size <- perf.size[tail(names(perf.global), -3)] # perf par DSP perf.dsp <- perf.global %>% group_by(DSP) %>% summarise( Ad = '', Size = '', Impressions = sum(Impressions), Clicks = sum(Clicks), Spent = sum(Spent)) # hack manque de donnees perf.dsp[perf.dsp$DSP=='Weborama',]$Spent <- sum(dt[dt$DSP=="Weborama",]$Spent) perf.dsp <- perf.dsp %>% mutate(CPC = Spent/Clicks, CPM = Spent/Impressions*1000, CTR = Clicks/Impressions*100) %>% mutate_at(.cols = vars(Spent, CPC, CPM, CTR), function(x) round(x, digits = 2)) %>% left_join(ventes %>% group_by(DSP) %>% summarise(Ventes = sum(Total))) %>% mutate(CPA = round(Spent/Ventes, digits = 2)) perf.dsp <- perf.dsp[tail(names(perf.global), -1)]
Write excel file
library(xlsx) library(r2excel) skaze.darkblue <- rgb(36/255, 116/255, 152/255) skaze.grey <- rgb(217/255, 217/255, 217/255) skaze.lightblue <- rgb(114/255, 179/255, 199/255) skaze.palette <- colorRampPalette(c(skaze.lightblue, skaze.darkblue)) wb <- xlsx::loadWorkbook('../Rapport/Template.xlsx') sheets <- xlsx::getSheets(wb) suivi.global <- sheets$`Suivi Global` suivi.quot <- sheets$`Suivi Quotidien` suivi.hebdo <- sheets$`Suivi Hebdo` suivi.mens <- sheets$`Suivi Mensuel` suivi <- list(global = suivi.global, quot = suivi.quot, hebdo = suivi.hebdo, mens = suivi.mens) campaign <- "Son-video" ad_group <- "Retargeting + Prospect" lapply(names(suivi), function(name){ if(name!="global"){ head <- paste("Campagne :", campaign, "; Ad group :", ad_group) } else { head <- paste("Résultats globaux du", min(dt$Date), "au", max(dt$Date)) } xlsx.addHeader(wb, suivi[[name]], value = head, startRow = 6, level = 3) xlsx.addTable(wb, suivi[[name]], data = matrix(names(perf[[name]]), nrow = 1), startRow = 8, startCol = 1, row.names = FALSE, col.names = FALSE, fontColor = rgb(0, 0, 0), fontSize = 12, rowFill = skaze.darkblue) xlsx.addTable(wb, suivi[[name]], data = as.data.frame(perf[[name]]), startRow = 9, startCol = 1, row.names = FALSE, col.names = FALSE, fontColor='grey30', fontSize=12, rowFill=c(skaze.lightblue, skaze.grey) ) }) start.row <- 9 + nrow(perf.global) + 1 xlsx.addTable(wb, suivi.global, data = as.data.frame(perf.dsp), startRow = start.row, startCol = 2, row.names = FALSE, col.names = FALSE, fontColor='grey30', fontSize=12, rowFill=c(skaze.lightblue, skaze.grey) ) start.row <- start.row + nrow(perf.dsp) + 1 xlsx.addTable(wb, suivi.global, data = as.data.frame(perf.ad), startRow = start.row, startCol = 3, row.names = FALSE, col.names = FALSE, fontColor='grey30', fontSize=12, rowFill=c(skaze.lightblue, skaze.grey) ) start.row <- start.row + nrow(perf.ad) + 1 xlsx.addTable(wb, suivi.global, data = as.data.frame(perf.size), startRow = start.row, startCol = 4, row.names = FALSE, col.names = FALSE, fontColor='grey30', fontSize=12, rowFill=c(skaze.lightblue, skaze.grey) ) start.row <- start.row + nrow(perf.size) + 1 xlsx.plot <- function(var, legend, filter = TRUE) { if(filter) perf.global <- perf.global %>% filter(Ad %in% relevant.ad) text=paste0('p <- ggplot(perf.global, aes(x=Size, y=',var,')) + geom_col(aes(fill = Ad), position = "dodge") + xlab(\'Ad size\') + scale_fill_manual(values = skaze.palette(6)) + theme_bw()') if(!legend) text <- paste0(text, " + theme(legend.position = \'none\') ") eval(parse(text = text)) print(p) }
xlsx.addPlot(wb, sheets$Graphiques, function(){xlsx.plot('Impressions', legend = FALSE)}, startRow = 1, width = 300) xlsx.addPlot(wb, sheets$Graphiques, function(){xlsx.plot('Clicks', legend = FALSE)}, width = 300, startRow = 1, startCol = 5) xlsx.addPlot(wb, sheets$Graphiques, function(){xlsx.plot('CTR', legend = TRUE)}, width = 400, startRow = 1, startCol = 8)
saveWorkbook(wb, file = "son-video3.xlsx") # xlsx.openFile('test.xlsx') # open file
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