preserve4879cf1bc334c7f2
preservec5a5399d168473cf
preserve1bbe5eee3b43e27f
preserve5e125d2e246c0195
preserve00a2b67783e1f9e3
Om rapporten
========================================
Laget av: Robert Ruud for PointOut AS
Oslo, desember 2019
Arbeidet er gjort i Rstudio og programmer benyttet er:
RStudio Team (2015). RStudio: Integrated Development for R. RStudio, Inc., Boston, MA URL http://www.rstudio.com/.
<div class="knitr-options" data-fig-width="576" data-fig-height="460"></div>
To cite R in publications use:
R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
A BibTeX entry for LaTeX users is
@Manual{, title = {R: A Language and Environment for Statistical Computing}, author = {{R Core Team}}, organization = {R Foundation for Statistical Computing}, address = {Vienna, Austria}, year = {2019}, url = {https://www.R-project.org/}, }
We have invested a lot of time and effort in creating R, please cite it when using it for data analysis. See also ‘citation(“pkgname”)’ for citing R packages.
To cite package ‘dplyr’ in publications use:
Hadley Wickham, Romain François, Lionel Henry and Kirill Müller (2019). dplyr: A Grammar of Data Manipulation. http://dplyr.tidyverse.org, https://github.com/tidyverse/dplyr.
A BibTeX entry for LaTeX users is
@Manual{, title = {dplyr: A Grammar of Data Manipulation}, author = {Hadley Wickham and Romain François and Lionel Henry and Kirill Müller}, year = {2019}, note = {http://dplyr.tidyverse.org, https://github.com/tidyverse/dplyr}, }
To cite ggplot2 in publications, please use:
H. Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2016.
A BibTeX entry for LaTeX users is
@Book{, author = {Hadley Wickham}, title = {ggplot2: Elegant Graphics for Data Analysis}, publisher = {Springer-Verlag New York}, year = {2016}, isbn = {978-3-319-24277-4}, url = {https://ggplot2.tidyverse.org}, }
To cite plotly in publications use:
Carson Sievert (2018) plotly for R. https://plotly-r.com
A BibTeX entry for LaTeX users is
@Manual{, title = {plotly for R}, author = {Carson Sievert}, year = {2018}, url = {https://plotly-r.com}, } ```
---
title: "MDN Dashboard"
output:
flexdashboard::flex_dashboard:
source_code: embed
theme: spacelab
---
```{r setup, include=FALSE}
library(flexdashboard)
library(knitr)
library(ggplot2)
library(plotly)
library(dplyr)
library(tidyverse)
library(rsconnect)
library(shiny)
library(ggradar)
```
```{r}
load("mdn13test.Rdata")
load("prosentfil.Rdata")
```
MDN dashboard
=====================================
Row
-------------------------------
### Kampanje recall
```{r echo=FALSE}
k1 <- mdn13test %>% group_by(Kino=factor(kino3u), recall=factor(recall)) %>% tally %>% complete(recall) %>% mutate(pct=n/sum(n)*100) %>% filter(Kino=="1" & recall=="1") %>% mutate(navn = paste("Kino"))
k2 <- mdn13test %>% group_by(TV=factor(TVuke), recall=factor(recall)) %>% tally %>% complete(recall) %>% mutate(pct=n/sum(n)*100) %>% filter(TV=="1" & recall=="1") %>% mutate(navn = paste("TV"))
k3 <- mdn13test %>% group_by(OLV=factor(OLVuke), recall=factor(recall)) %>% tally %>% complete(recall) %>% mutate(pct=n/sum(n)*100) %>% filter(OLV=="1" & recall=="1") %>% mutate(navn = paste("OLV"))
k4 <- mdn13test %>% group_by(OOH=factor(OOHuke), recall=factor(recall)) %>% tally %>% complete(recall) %>% mutate(pct=n/sum(n)*100) %>% filter(OOH=="1" & recall=="1") %>% mutate(navn = paste("OOH"))
k5 <- mdn13test %>% group_by(SoMe=factor(SoMeuke), recall=factor(recall)) %>% tally %>% complete(recall) %>% mutate(pct=n/sum(n)*100) %>% filter(SoMe=="1" & recall=="1") %>% mutate(navn = paste("SoMe"))
k6 <- mdn13test %>% group_by(Avis=factor(AVISuke), recall=factor(recall)) %>% tally %>% complete(recall) %>% mutate(pct=n/sum(n)*100) %>% filter(Avis=="1" & recall=="1") %>% mutate(navn = paste("Avis"))
k7 <- mdn13test %>% group_by(Display=factor(DISPLAYuke), recall=factor(recall)) %>% tally %>% complete(recall) %>% mutate(pct=n/sum(n)*100) %>% filter(Display=="1" & recall=="1") %>% mutate(navn = paste("Display"))
k8 <- mdn13test %>% group_by(Magasin=factor(Magasinuke), recall=factor(recall)) %>% tally %>% complete(recall) %>% mutate(pct=n/sum(n)*100) %>% filter(Magasin=="1" & recall=="1") %>% mutate(navn = paste("Magasin"))
k9 <- mdn13test %>% group_by(Radio=factor(Radiouke), recall=factor(recall)) %>% tally %>% complete(recall) %>% mutate(pct=n/sum(n)*100) %>% filter(Radio=="1" & recall=="1") %>% mutate(navn = paste("Radio"))
kanaltab <- rbind(k1,k2,k3,k4,k5,k6,k7,k8,k9)
```
```{r}
KinoNei <-
mdn13test %>% group_by(
Kino = factor(kino3u),
testmedie = factor(medium),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(Kino ==
"0" &
testmedie == "Video 31+ sek" &
recall == "1") %>% mutate(navn = paste("Ikke kino siste 3 uker"))
KinoJa <-
mdn13test %>% group_by(
Kino = factor(kino3u),
testmedie = factor(medium),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(Kino ==
"1" &
testmedie == "Video 31+ sek" &
recall == "1") %>% mutate(navn = paste("Kino siste 3 uker"))
TVNei <-
mdn13test %>% group_by(
TV = factor(TVuke),
testmedie = factor(medium),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(TV ==
"0" &
testmedie == "Video 31+ sek" &
recall == "1") %>% mutate(navn = paste("Ikke TV sist uke"))
TVJa <-
mdn13test %>% group_by(
TV = factor(TVuke),
testmedie = factor(medium),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(TV ==
"1" &
testmedie == "Video 31+ sek" &
recall == "1") %>% mutate(navn = paste("TV sist uke"))
TVogKinoJa <-
mdn13test %>% group_by(
TV = factor(TVuke),
Kino = factor(kino3u),
testmedie = factor(medium),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(TV ==
"1" &
Kino == "1" &
testmedie == "Video 31+ sek" &
recall == "1") %>% mutate(navn = paste("TV sist uke og kino siste 3"))
tvkino <- rbind(KinoNei,KinoJa,TVNei,TVJa,TVogKinoJa)
```
```{r echo=FALSE}
plotkanal <- ggplot(data = tvkino, mapping = aes(x = navn, y = pct, fill = pct))
plotkanal <- plotkanal + geom_bar(stat = "identity", colour = "#FF6666", fill = "#FF6666" , position = "dodge") + theme_dark() + ggtitle("Recall hos Kino og TV publikum - filmlengde 31+ sek") + xlab("") + ylab("Recall %")+ geom_hline(yintercept=mean(kanaltab$pct), linetype="dotted", color = "yellow") + geom_text(aes(label = round(pct, 1)))+theme(axis.text.x=element_text(angle=45,hjust=1))+ coord_cartesian(
ylim = c(20, 70))
ggplotly(plotkanal)
```
Row
-------------------------------
```{r echo=FALSE}
plot1 <- ggplot(subset(prosentfil, kanal %in% c("TV","Radio","Kino","SoMe","Nettavis","Avis")),aes(x = utsagn, y = value, fill = factor(kanal))) +
geom_col(aes(y = value)+ position_stack(reverse = TRUE)) + scale_fill_manual(values=c("#999999","#ff6666","#26927b","#ffc000","#993300","#1c5b72"))+
ggtitle("Holdning til reklame i forskjellige kanaler") + coord_flip() + theme(legend.position="bottom") + scale_y_continuous(labels = scales::percent)
```
```{r echo=FALSE}
ggplotly(plot1)
```
Column {.tabset .tabset-fade}
-------------------------------------
### Alder 15-34
```{r echo=FALSE}
k11534 <-
mdn13test %>% filter(aldgrp == "15-34") %>% group_by(
Kino = factor(kino3u),
medium = factor(medium),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(Kino == "1" & medium=="Video 31+ sek" & recall == "1") %>% mutate(navn = paste("Kino"))
k21534 <-
mdn13test %>% filter(aldgrp == "15-34") %>% group_by(
TV = factor(TVuke),
video = factor(video),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(TV == "1" & video=="1" & recall == "1") %>% mutate(navn = paste("TV"))
k31534 <-
mdn13test %>% filter(aldgrp == "15-34") %>% group_by(
OLV = factor(OLVuke),
medium = factor(medium),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(OLV ==
"1" & medium=="OLV" & recall == "1") %>% mutate(navn = paste("OLV"))
k41534 <-
mdn13test %>% filter(aldgrp == "15-34") %>% group_by(
OOH = factor(OOHuke),
medium = factor(medium),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(OOH ==
"1" & medium=="OOH" & recall == "1") %>% mutate(navn = paste("OOH"))
k51534 <-
mdn13test %>% filter(aldgrp == "15-34") %>% group_by(
SoMe = factor(SoMeuke),
medium = factor(medium),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(SoMe ==
"1" & medium=="SoMe" & recall == "1") %>% mutate(navn = paste("SoMe"))
k61534 <-
mdn13test %>% filter(aldgrp == "15-34") %>% group_by(
Avis = factor(AVISuke),
medium = factor(medium),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(Avis ==
"1" & medium=="Avis" & recall == "1") %>% mutate(navn = paste("Avis"))
k71534 <-
mdn13test %>% filter(aldgrp == "15-34") %>% group_by(
Display = factor(DISPLAYuke),
medium = factor(medium),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(Display ==
"1" & medium=="Web" & recall == "1") %>% mutate(navn = paste("Display"))
k81534 <-
mdn13test %>% filter(aldgrp == "15-34") %>% group_by(
Magasin = factor(Magasinuke),
medium = factor(medium),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(Magasin ==
"1" & medium=="Magasin" & recall == "1") %>% mutate(navn = paste("Magasin"))
k91534 <-
mdn13test %>% filter(aldgrp == "15-34") %>% group_by(
Radio = factor(Radiouke),
audio = factor(audio),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(Radio ==
"1" & audio=="1" & recall == "1") %>% mutate(navn = paste("Radio"))
kanaltab1534 <-
rbind(
k11534,
k21534,
k31534,
k41534,
k51534,
k61534,
k71534,
k81534,
k91534
)
```
```{r echo=FALSE}
plotkanal1534 <- ggplot(data = kanaltab1534, mapping = aes(x = navn, y = pct, fill = pct))
plotkanal1534 <- plotkanal1534 + geom_bar(stat = "identity", colour = "#FF6666", fill = "#FF6666" , position = "dodge") + theme_dark() + ggtitle("Recall 15-34 kanaler brukt siste uke") + xlab("kampanjer") + ylab("Recall %") + geom_hline(yintercept=mean(kanaltab$pct), linetype="dotted", color = "yellow") + geom_text(aes(label = round(pct, 1)))+theme(axis.text.x=element_text(angle=45,hjust=1))+ coord_cartesian(
ylim = c(0, 60))
ggplotly(plotkanal1534)
```
### Alder 35-48
```{r echo=FALSE}
k13548 <-
mdn13test %>% filter(aldgrp == "35-48") %>% group_by(
Kino = factor(kino3u),
medium = factor(medium),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(Kino == "1" & medium=="Video 31+ sek" & recall == "1") %>% mutate(navn = paste("Kino"))
k23548 <-
mdn13test %>% filter(aldgrp == "35-48") %>% group_by(
TV = factor(TVuke),
video = factor(video),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(TV == "1" & video=="1" & recall == "1") %>% mutate(navn = paste("TV"))
k33548 <-
mdn13test %>% filter(aldgrp == "35-48") %>% group_by(
OLV = factor(OLVuke),
medium = factor(medium),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(OLV ==
"1" & medium=="OLV" & recall == "1") %>% mutate(navn = paste("OLV"))
k43548 <-
mdn13test %>% filter(aldgrp == "35-48") %>% group_by(
OOH = factor(OOHuke),
medium = factor(medium),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(OOH ==
"1" & medium=="OOH" & recall == "1") %>% mutate(navn = paste("OOH"))
k53548 <-
mdn13test %>% filter(aldgrp == "35-48") %>% group_by(
SoMe = factor(SoMeuke),
medium = factor(medium),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(SoMe ==
"1" & medium=="SoMe" & recall == "1") %>% mutate(navn = paste("SoMe"))
k63548 <-
mdn13test %>% filter(aldgrp == "35-48") %>% group_by(
Avis = factor(AVISuke),
medium = factor(medium),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(Avis ==
"1" & medium=="Avis" & recall == "1") %>% mutate(navn = paste("Avis"))
k73548 <-
mdn13test %>% filter(aldgrp == "35-48") %>% group_by(
Display = factor(DISPLAYuke),
medium = factor(medium),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(Display ==
"1" & medium=="Web" & recall == "1") %>% mutate(navn = paste("Display"))
k83548 <-
mdn13test %>% filter(aldgrp == "35-48") %>% group_by(
Magasin = factor(Magasinuke),
medium = factor(medium),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(Magasin ==
"1" & medium=="Magasin" & recall == "1") %>% mutate(navn = paste("Magasin"))
k93548 <-
mdn13test %>% filter(aldgrp == "35-48") %>% group_by(
Radio = factor(Radiouke),
audio = factor(audio),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(Radio ==
"1" & audio=="1" & recall == "1") %>% mutate(navn = paste("Radio"))
kanaltab3548 <-
rbind(
k13548,
k23548,
k33548,
k43548,
k53548,
k63548,
k73548,
k83548,
k93548
)
```
```{r echo=FALSE}
plotkanal3548 <- ggplot(data = kanaltab3548, mapping = aes(x = navn, y = pct, fill = pct))
plotkanal3548 <- plotkanal3548 + geom_bar(stat = "identity", colour = "#FF6666", fill = "#FF6666" , position = "dodge") + theme_dark() + ggtitle("Recall 35-48 kanaler brukt siste uke") + xlab("kampanjer") + ylab("Recall %") + geom_hline(yintercept=mean(kanaltab$pct), linetype="dotted", color = "yellow") + geom_text(aes(label = round(pct, 1)))+theme(axis.text.x=element_text(angle=45,hjust=1))+ coord_cartesian(
ylim = c(0, 70))
ggplotly(plotkanal3548)
```
### Alder 49+
```{r echo=FALSE}
k149pluss <-
mdn13test %>% filter(aldgrp == "49+") %>% group_by(
Kino = factor(kino3u),
medium = factor(medium),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(Kino == "1" & medium=="Video 31+ sek" & recall == "1") %>% mutate(navn = paste("Kino"))
k249pluss <-
mdn13test %>% filter(aldgrp == "49+") %>% group_by(
TV = factor(TVuke),
video = factor(video),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(TV == "1" & video=="1" & recall == "1") %>% mutate(navn = paste("TV"))
k349pluss <-
mdn13test %>% filter(aldgrp == "49+") %>% group_by(
OLV = factor(OLVuke),
medium = factor(medium),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(OLV ==
"1" & medium=="OLV" & recall == "1") %>% mutate(navn = paste("OLV"))
k449pluss <-
mdn13test %>% filter(aldgrp == "49+") %>% group_by(
OOH = factor(OOHuke),
medium = factor(medium),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(OOH ==
"1" & medium=="OOH" & recall == "1") %>% mutate(navn = paste("OOH"))
k549pluss <-
mdn13test %>% filter(aldgrp == "49+") %>% group_by(
SoMe = factor(SoMeuke),
medium = factor(medium),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(SoMe ==
"1" & medium=="SoMe" & recall == "1") %>% mutate(navn = paste("SoMe"))
k649pluss <-
mdn13test %>% filter(aldgrp == "49+") %>% group_by(
Avis = factor(AVISuke),
medium = factor(medium),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(Avis ==
"1" & medium=="Avis" & recall == "1") %>% mutate(navn = paste("Avis"))
k749pluss <-
mdn13test %>% filter(aldgrp == "49+") %>% group_by(
Display = factor(DISPLAYuke),
medium = factor(medium),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(Display ==
"1" & medium=="Web" & recall == "1") %>% mutate(navn = paste("Display"))
k849pluss <-
mdn13test %>% filter(aldgrp == "49+") %>% group_by(
Magasin = factor(Magasinuke),
medium = factor(medium),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(Magasin ==
"1" & medium=="Magasin" & recall == "1") %>% mutate(navn = paste("Magasin"))
k949pluss <-
mdn13test %>% filter(aldgrp == "49+") %>% group_by(
Radio = factor(Radiouke),
audio = factor(audio),
recall = factor(recall)
) %>% tally %>% complete(recall) %>% mutate(pct = n / sum(n) * 100) %>% filter(Radio ==
"1" & audio=="1" & recall == "1") %>% mutate(navn = paste("Radio"))
kanaltab49pluss <-
rbind(
k149pluss,
k249pluss,
k349pluss,
k449pluss,
k549pluss,
k649pluss,
k749pluss,
k849pluss,
k949pluss
)
```
```{r echo=FALSE}
plotkanal49pluss <- ggplot(data = kanaltab49pluss, mapping = aes(x = navn, y = pct, fill = pct))
plotkanal49pluss <- plotkanal49pluss + geom_bar(stat = "identity", colour = "#FF6666", fill = "#FF6666" , position = "dodge") + theme_dark() + ggtitle("Recall 49+ kanaler brukt siste uke") + xlab("kampanjer") + ylab("Recall %") + geom_hline(yintercept=mean(kanaltab$pct), linetype="dotted", color = "yellow") + geom_text(aes(label = round(pct, 1)))+theme(axis.text.x=element_text(angle=45,hjust=1))+ coord_cartesian(
ylim = c(0, 70))
ggplotly(plotkanal49pluss)
```
```{r eval=FALSE, include=FALSE}
#allspdata <- mdn13test[c(1,19:29,122)]
#allspdata
#
#allspdata %>% mutate_each(funs(mean), -c("utvalg","AMIProRspId.1","aldgrp")) -> sptab
#
#mcdspdata <- allspdata[which(allspdata$utvalg=="MacDonalds"),]
#
#mcdspdata %>% mutate_each(funs(mean), -c("utvalg","AMIProRspId.1","aldgrp")) -> mcdsptab
#
#
#allout <- sptab[, names(sptab)!= c("utvalg","AMIProRspId.1","aldgrp")] %>% summarize_all(.,funs(mean))%>% mutate(navn = paste("Alle"))
#mcdout <- mcdsptab[, names(mcdsptab)!= c("utvalg","AMIProRspId.1","aldgrp")] %>% summarize_all(.,funs(mean))%>% mutate(navn = paste("McDonalds"))
#
#spidertab <- rbind(allout,mcdout)
#spidertab$utvalg <- spidertab$AMIProRspId.1 <- spidertab$aldgrp <- NULL
#spidertab <- as_tibble(spidertab)
#
#plotdata <- spidertab %>%
#
#plotdata
#
# generate radar chart
#ggradar(spidertab,
# grid.label.size = 4,
# axis.label.size = 4,
# group.point.size = 5,
# group.line.width = 1.5,
# legend.text.size= 10) +
# labs(title = "Mammals, size, and sleep")
```
```
Om rapporten
========================================
Laget av: Robert Ruud for PointOut AS
Oslo, desember 2019
Arbeidet er gjort i Rstudio og programmer benyttet er:
RStudio Team (2015). RStudio: Integrated Development for R. RStudio, Inc., Boston, MA URL http://www.rstudio.com/.
```{r echo=FALSE}
citation()
citation("dplyr")
citation("ggplot2")
citation("plotly")
```