CMTracking/MonthlyReports.Rmd at master · lisasheridan/CMTracking · GitHub

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---
title: "Monthly Numbers"
date: "Last updated: 11/12/2020"
output:
  html_document:
    toc: true
    toc_float: true
    collapsed: false
    number_sections: false
    toc_depth: 1
---


```{css, echo=FALSE}
h1 {
  text-align: center;
}
```

```{r setup, echo = FALSE, warning=FALSE, message=FALSE}
source("monthlyreport_functions.R")
data <- read.csv('October2020trackingdata.csv')
tracking.data <-reformat_googlesheet(data)
tracking.data.October2020 <- tracking.data[which(tracking.data$month=="October" & tracking.data$year=="2020"),]
```

Repository for CM/N Programs Monthly Tracking reports.

***

# **October 2020**

### Enrollment
```{r, October Enrollment, echo = FALSE, warning=FALSE, message=FALSE}
rows <- c("Media Meteorologists","Market Penetration (%)", "Local Television Stations", "Spanish-language Meteorologists", "Journalists Receiving CMN")
values <- c(968, 92, 483, 55, 702)
enrollment <- as.data.frame(cbind(rows, values))
names(enrollment) <- c(" ", "Enrollment")
library("formattable")
formattable(enrollment)
```


### Hits by Program
```{r, October Hits by Type and Program, echo = FALSE, warning=FALSE, message=FALSE}
#expanded view
library("tidyr")
expanded.hits.draft.October2020 <- hitsbyprogram(tracking.data.October2020)
expanded.hits.October2020 <- expanded.hits.draft.October2020[,c("source", "Twitter", "fb", "other",
                                  "online.article", "radio", "tv")]
#restrict data to CC, CM, CMN sources
expanded.hits.CMprograms.October2020 <- subset(expanded.hits.October2020, source=="CC"|source=="CM"|source=="CMN"|source=="Total")
#aggregate hits according to nest program model
CMN.October2020 <- expanded.hits.CMprograms.October2020[3,2:7]
CM.October2020 <- CMN.October2020 + expanded.hits.CMprograms.October2020[2,2:7]
CC.October2020 <- CM.October2020 + expanded.hits.CMprograms.October2020[1,2:7]
aggregated.hits.CMprograms.October2020 <- rbind(CC.October2020, CM.October2020, CMN.October2020)
rownames(aggregated.hits.CMprograms.October2020) <- c("CC", "CM", "CMN")
#change column names
names(aggregated.hits.CMprograms.October2020) <- c("Twitter", "Facebook", "Other ",
                          "Online Articles", "Radio", "TV")
library("formattable")
aggregated.hits.formatted.October2020 <- formattable(aggregated.hits.CMprograms.October2020,
                                       align=c("l", "c", "c", "c", "c", "c", "c"),
                                       list(''))
aggregated.hits.formatted.October2020
```

### Top 10 Releases
```{r, October 2020 Top 10 Releases, echo = FALSE, warning=FALSE, message=FALSE}
rankedreleases.October2020 <- rankReleases(tracking.data.October2020)
top10releases.October2020 <-rankedreleases.October2020[c(1:10),]
library("formattable")
names(top10releases.October2020) <- c("Release", "Social", "Stories", "TV", "Total")
formattable(top10releases.October2020)
```

### Top 5 Releases
```{r, October 2020 Top 5 Releases, echo = FALSE, warning=FALSE, message=FALSE}
rankedreleases.October2020 <- rankReleases(tracking.data.October2020)
top10releases.October2020 <-rankedreleases.October2020[c(1:10),]
names(top10releases.October2020) <- c("Release", "Social", "Stories", "TV", "Total")
top5releases.October2020 <-rankedreleases.October2020[c(1:5),]
names(top5releases.October2020) <- c("Release", "Social", "Stories", "TV", "Total")
library(DT)
datatable(top10releases.October2020, fillContainer=FALSE, options = list(scrollX="70px", scrollY="200px", pageLength = 5, dom = 'ftp'), rownames=FALSE)
```

### Hits by Region
```{r October Hits by Region, echo = FALSE, warning=FALSE, message=FALSE}
#compute hits by regions
month.hitsbyregion.October2020 <- hitsbyregion(tracking.data.October2020)
month.hitsbyregion.October2020
```

***

# **September 2020**

```{r September setup, echo = FALSE, warning=FALSE, message=FALSE}
tracking.data.September2020 <- tracking.data[which(tracking.data$month=="September" & tracking.data$year=="2020"),]
```


### Hits by Program
```{r, September Hits by Type and Program, echo = FALSE, warning=FALSE, message=FALSE}
#expanded view
library("tidyr")
expanded.hits.draft.September2020 <- hitsbyprogram(tracking.data.September2020)
expanded.hits.September2020 <- expanded.hits.draft.September2020[,c("source", "Twitter", "fb", "other",
                                  "online.article", "radio", "tv")]
#restrict data to CC, CM, CMN sources
expanded.hits.CMprograms.September2020 <- subset(expanded.hits.September2020, source=="CC"|source=="CM"|source=="CMN"|source=="Total")
#aggregate hits according to nest program model
CMN.September2020 <- expanded.hits.CMprograms.September2020[3,2:7]
CM.September2020 <- CMN.September2020 + expanded.hits.CMprograms.September2020[2,2:7]
CC.September2020 <- CM.September2020 + expanded.hits.CMprograms.September2020[1,2:7]
aggregated.hits.CMprograms.September2020 <- rbind(CC.September2020, CM.September2020, CMN.September2020)
rownames(aggregated.hits.CMprograms.September2020) <- c("CC", "CM", "CMN")
#change column names
names(aggregated.hits.CMprograms.September2020) <- c("Twitter", "Facebook", "Other ",
                          "Online Articles", "Radio", "TV")
library("formattable")
aggregated.hits.formatted.September2020 <- formattable(aggregated.hits.CMprograms.September2020,
                                       align=c("l", "c", "c", "c", "c", "c", "c"),
                                       list(''))
aggregated.hits.formatted.September2020
```

### Top 10 Releases
```{r, September Top 10 Releases, echo = FALSE, warning=FALSE, message=FALSE}
rankedreleases.September2020 <- rankReleases(tracking.data.September2020)
top10releases.September2020 <-rankedreleases.September2020[c(1:10),]
library("formattable")
names(top10releases.September2020) <- c("Release", "Social", "Stories", "TV", "Total")
formattable(top10releases.September2020)
```


### Hits by Region
```{r September Hits by Region, echo = FALSE, warning=FALSE, message=FALSE}
#compute hits by regions
month.hitsbyregion.September2020 <- hitsbyregion(tracking.data.September2020)
month.hitsbyregion.September2020
```

***

# **August 2020**

### Enrollment
```{r, August Enrollment, echo = FALSE, warning=FALSE, message=FALSE}
rows <- c("Media Meteorologists","Market Penetration (%)", "Local Television Stations", "Spanish-language Meteorologists", "Journalists Receiving CMN")
values <- c(945, 92, 473, 54, 696)
enrollment <- as.data.frame(cbind(rows, values))
names(enrollment) <- c(" ", "Enrollment")
library("formattable")
formattable(enrollment)
```

```{r August setup, echo = FALSE, warning=FALSE, message=FALSE}
tracking.data.August2020 <- tracking.data[which(tracking.data$month=="August" & tracking.data$year=="2020"),]
```

### Hits by Program
```{r, August Hits by Type and Program, echo = FALSE, warning=FALSE, message=FALSE}
#expanded view
library("tidyr")
expanded.hits.draft.August2020 <- hitsbyprogram(tracking.data.August2020)
expanded.hits.August2020 <- expanded.hits.draft.August2020[,c("source", "Twitter", "fb", "other",
                                  "online.article", "radio", "tv")]
#restrict data to CC, CM, CMN sources
expanded.hits.CMprograms.August2020 <- subset(expanded.hits.August2020, source=="CC"|source=="CM"|source=="CMN"|source=="Total")
#aggregate hits according to nest program model
CMN.August2020 <- expanded.hits.CMprograms.August2020[3,2:7]
CM.August2020 <- CMN.August2020 + expanded.hits.CMprograms.August2020[2,2:7]
CC.August2020 <- CM.August2020 + expanded.hits.CMprograms.August2020[1,2:7]
aggregated.hits.CMprograms.August2020 <- rbind(CC.August2020, CM.August2020, CMN.August2020)
rownames(aggregated.hits.CMprograms.August2020) <- c("CC", "CM", "CMN")
#change column names
names(aggregated.hits.CMprograms.August2020) <- c("Twitter", "Facebook", "Other ",
                          "Online Articles", "Radio", "TV")
library("formattable")
aggregated.hits.formatted.August2020 <- formattable(aggregated.hits.CMprograms.August2020,
                                       align=c("l", "c", "c", "c", "c", "c", "c"),
                                       list(''))
aggregated.hits.formatted.August2020
```

### Top 10 Releases
```{r August Top 10 Releases, echo = FALSE, warning=FALSE, message=FALSE}
rankedreleases.August2020 <- rankReleases(tracking.data.August2020)
top10releases.August2020 <-rankedreleases.August2020[c(1:10),]
library("formattable")
names(top10releases.August2020) <- c("Release", "Social", "Stories", "TV", "Total")
formattable(top10releases.August2020)
```

### Hits by Region
```{r, August Hits By Region, echo = FALSE, warning=FALSE, message=FALSE}
#compute hits by regions
month.hitsbyregion.August2020 <- hitsbyregion(tracking.data.August2020)
month.hitsbyregion.August2020
```

***