stats220/dynamic_report.Rmd at main · pxstachio/stats220 · GitHub

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---
title: My dynamic report
output: html_fragment
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo=FALSE, message=FALSE, warning=FALSE, error=FALSE)

```

```{css}
h2 {
  border-bottom: 2px solid #BBBBBB;
  padding-bottom: 5px;
}
```

```{r}
library(tidyverse)

#Reading csv into dataframe
logged_data <- read_csv("https://docs.google.com/spreadsheets/d/e/2PACX-1vSPQSVUAFlAdH0FuJqS2GsZmhN36-r1GF4KKoqBAYhdTs2to39bqD4KLfVUPHvdEIbu_Q9dUtQza4xX/pub?gid=2014668508&single=true&output=csv")

#Renaming into new dataframe
latest_data <- logged_data %>%
  rename(timestamp = 1,
         show_name = 2,
         ep_name = 3,
         season = 4,
         ep_length = 5,
         rating = 6)
```

## Impact of Episode Length on Individual Episode Ratings

```{r}
#Summary Values

#Number of rows (number of responses)
num_responses <- nrow(latest_data)

#min, max and average length of an episode
ep_min <- min(latest_data$ep_length)
ep_max <- max(latest_data$ep_length)
ep_avg <- (sum(latest_data$ep_length) / num_responses) %>% round(0)

#min, max and average rating
rating_min <- min(latest_data$rating)
rating_max <- max(latest_data$rating)
rating_avg <- (sum(latest_data$rating) / num_responses) %>% round(0)
```

```{r}
#Number of Episodes by Episode Length
ggplot(data = latest_data) +
  geom_bar(aes(x = ep_length), fill = "#58D358") +
  labs(title = "Number of Episodes by Episode Length",
       x = "Length of episode (mins)",
       y = "Number of episodes")
```

There are `r num_responses` episodes (responses) in this data.

The minimum and maximum episode lengths are `r ep_min` minutes and `r ep_max` minutes, respectively.

The average episode length is around `r ep_avg` minutes.

```{r}
#Number of Episodes by Episode Rating
ggplot(data = latest_data) +
  geom_bar(aes(x = rating), fill = "#4C90D7") +
  labs(title = "Number of Episodes by Episode Rating",
       x = "Episode rating (%)",
       y = "Number of episodes")
```

The minimum and maximum episode ratings are `r rating_min`% and `r rating_max`%, respectively.

The average episode rating is around `r rating_avg`%.

```{r}
#Comparing Episode Length and Episode Rating
ggplot(data = latest_data) +
  geom_bar(aes(x = ep_length, fill = factor(rating))) +
  labs(title = "Comparing Episode Length and Episode Rating",
       x = "Episode length (mins)",
       y = "Number of episodes")
```

The highest rated episode with a rating of `r rating_max`%, and other high rated episodes seem to cluster just above the average episode length of `r ep_avg` minutes.

This suggests that higher rated episodes are often slightly longer, although this does not directly imply that longer episodes receive higher ratings.