female_artists <-
c("by Taylor Swift", "by Lana Del Rey", "by Demi Lovato", "by Carly Rae Jepsen", "by Christina Aguilera")
female_filtered_reviews <- all_reviews %>%
filter(album_artist %in% female_artists)
female_filtered_reviews %>%
ggplot(aes(x= album_title, y=user_rating, fill = album_artist)) +
geom_col() +
geom_text(aes(label = user_rating), vjust = -0.5, color = "black") +
scale_y_continuous(limits = c(0, 10))+
labs(title = "Female Artist's Album Ratings",
x = "Album Title",
y = "User Rating",
fill = "Artist")+
theme(axis.text.x = element_text(angle = 45, hjust = 1))Metacritic Analysis
Metacritic
Growing up, I learned how important music is. It is a form of art that can emulate in a few words or notes how a person is feeling, whether it is sad, happy, heartbroken, or in love. I used Metacritic as a source to look at what albums and artists impact the most people and are rated the best by users.
Data
As stated before, I scrapped Metacritic on their Album Releases by User Score page. I collected data from 4 pages which include nearly the top 400 songs according to the user scores. I was able to collect Album Artist, Album Name, Album Rank, Album Summary, and Album User Score.
Link
Hypothesis Analysis
Female Artist Comparison
My question/hypothesis is that female artists are more popular than male artists. I first started by looking at specific female artists’ albums of Taylor Swift, Lana Del Rey, Demi Lovato, and Carly Rae Jepson and their specific user ratings. I created a separate function look for these specific artists due to the high volume of albums in this data frame as well as the popularity of their music. With this, I was able to create a filter for these specific artists.
Analysis:
Through this visualization, we are able to see that Lana Del Rey’s album “Do You Know That There’s a Tunnel Under Ocean Blvd.” is the highest rated female artist album at 9.4 The majority of her albums are 9 or above with the exception of her “Ultraviolence” album that is at 8.8. Additionally, we can see that Taylor Swift is probably her biggest competition with her ratings being consistently close to 9 ranging from 8.9-9.2.
Male Artist Comparison
I, then, looked at male artists’ albums of Kenrick Lamar, Eminem, The Weeknd, Frank Ocean, and Hozier and their specific user ratings. Using the same strategy as the female artist visualization, I was able to create a function that filtered out these specific male artists based on the volume of albums.
male_artists <-
c("by Kendrick Lamar", "by Eminem", "by The Weeknd", "by Frank Ocean", "by Hozier")
male_filtered_reviews <- all_reviews %>%
filter(album_artist %in% male_artists)
male_filtered_reviews %>%
ggplot(aes(x= album_title, y=user_rating, fill = album_artist)) +
geom_col() +
geom_text(aes(label = user_rating), vjust = -0.5, color = "black") +
scale_y_continuous(limits = c(0, 10))+
labs(title = "Male Artist's Album Ratings",
x = "Album Title",
y = "User Rating",
fill = "Artist")+
theme(axis.text.x = element_text(angle = 45, hjust = 1))Analysis:
Through this visualization, we are able to see that Eminem’s albums “The Eminem Show” and “The Marshall Mathers LP” are tied with Kendrick Lamar’s album “To Pimp A Butterfly” are the highest rated male artist album at 9. The remaining albums are standing around an 8.8 or 8.9, but nothing above a 9.
Band Comparison
Finally, I looked at bands’ albums of Radiohead, Foo Fighters, Red Hot Chili Peppers, Pearl Jam, and My Chemical Romance and their specific user ratings.
bands_artists <-
c("by Radiohead", "by Foo Fighters","by Red Hot Chili Peppers", "by Pearl Jam", "by My Chemical Romance")
bands_filtered_reviews <- all_reviews %>%
filter(album_artist %in% bands_artists)
bands_filtered_reviews %>%
ggplot(aes(x= album_title, y=user_rating, fill = album_artist)) +
geom_col() +
geom_text(aes(label = user_rating), vjust = -0.5, color = "black") +
scale_y_continuous(limits = c(0, 10))+
labs(title = "Bands Album Ratings",
x = "Album Title",
y = "User Rating",
fill = "Band")+
theme(axis.text.x = element_text(angle = 45, hjust = 1))Analysis:
Through this visualization, we are able to see that Radiohead’s albums “In Rainbows” is the highest rated band album at 9. The remaining albums are standing around an 8.8 or 8.9, but nothing above a 9. This is the same as the male artist’s comparison.
Top 10
To bring it all together, I looked at the average user rating grouped by artists in descending order to see what the top 10 musicians were.
avg_rating_artists <-
all_reviews %>%
group_by(album_artist) %>%
summarize(avg_user_rating = mean(user_rating))
avg_rating_artists <- all_reviews %>%
group_by(album_artist) %>%
summarize(avg_user_rating = mean(user_rating)) %>%
arrange(desc(avg_user_rating)) %>%
top_n(10)
print(avg_rating_artists)Analysis
Here we can see that average user rating for each artist. It is showing that 7 out of 10 artists are females. While this data is skewed due to the few pages I pulled at the beginning which eliminates a good majority of the albums, it is showing the top albums of the moment.