Upload Collaborators.R

Collaborators.R

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+# {
+#   # load packages
+#   suppressPackageStartupMessages(library(dplyr))
+#   suppressPackageStartupMessages(library(spotifyr))
+# 
+#   # Set up environment
+#   client_ID <- "bc0b388b3801497f8162615befb50a43"
+#   client_secret <- "512e20aa79ff4a228cc4e95ab46a45fd"
+# 
+#   Sys.setenv(SPOTIFY_CLIENT_ID = client_ID)
+#   Sys.setenv(SPOTIFY_CLIENT_SECRET = client_secret)
+# 
+#   access_token <- get_spotify_access_token()
+# }
+
+
+get_artists_collaborators <- function(spotify_artist_id) {
+  # related artists nodes function
+  get_Nodes <- function(artist_id) {
+    # get artists related to main artist
+    related_artists <- get_related_artists(
+      id = artist_id,
+      include_meta_info = TRUE
+    )
+
+    # get other artists that are related to the
+    # artists that are related to the main artist
+    other_related <- c()
+    for (i in 1:nrow(related_artists$artists)) {
+      result <- get_related_artists(
+        id = related_artists$artists[["id"]][i],
+        include_meta_info = TRUE
+      )
+      other_related <- append(other_related, result)
+    }
+
+    images <- c()
+    for (i in other_related) { # this loops through the list
+      for (k in 1:nrow(i)) { # this loops through each table in list
+        image_urls <- i$images[[k]]$url[2] # the third image is collected per row in each table
+        images <- append(images, image_urls)
+      }
+    }
+
+    genre <- c()
+    for (i in (other_related)) { # this loops through each list
+      for (j in 1:nrow(i)) { # this loops through each table in list
+        result <- i$genres[[j]][2] # this collects the 2nd item in the vector of genres
+        genre <- append(genre, result)
+      }
+    }
+
+
+    nodes <- data.frame(
+      name = tolower(c(
+        other_related[[1]]$name,
+        other_related[[2]]$name,
+        other_related[[3]]$name,
+        other_related[[4]]$name,
+        other_related[[5]]$name,
+        other_related[[6]]$name,
+        other_related[[7]]$name,
+        other_related[[8]]$name,
+        other_related[[9]]$name,
+        other_related[[10]]$name,
+        other_related[[11]]$name,
+        other_related[[12]]$name,
+        other_related[[13]]$name,
+        other_related[[14]]$name,
+        other_related[[15]]$name,
+        other_related[[16]]$name,
+        other_related[[17]]$name,
+        other_related[[18]]$name,
+        other_related[[19]]$name,
+        other_related[[20]]$name
+      )),
+      id = c(c(
+        other_related[[1]]$id,
+        other_related[[2]]$id,
+        other_related[[3]]$id,
+        other_related[[4]]$id,
+        other_related[[5]]$id,
+        other_related[[6]]$id,
+        other_related[[7]]$id,
+        other_related[[8]]$id,
+        other_related[[9]]$id,
+        other_related[[10]]$id,
+        other_related[[11]]$id,
+        other_related[[12]]$id,
+        other_related[[13]]$id,
+        other_related[[14]]$id,
+        other_related[[15]]$id,
+        other_related[[16]]$id,
+        other_related[[17]]$id,
+        other_related[[18]]$id,
+        other_related[[19]]$id,
+        other_related[[20]]$id
+      )),
+      popularity = c(c(
+        other_related[[1]]$popularity,
+        other_related[[2]]$popularity,
+        other_related[[3]]$popularity,
+        other_related[[4]]$popularity,
+        other_related[[5]]$popularity,
+        other_related[[6]]$popularity,
+        other_related[[7]]$popularity,
+        other_related[[8]]$popularity,
+        other_related[[9]]$popularity,
+        other_related[[10]]$popularity,
+        other_related[[11]]$popularity,
+        other_related[[12]]$popularity,
+        other_related[[13]]$popularity,
+        other_related[[14]]$popularity,
+        other_related[[15]]$popularity,
+        other_related[[16]]$popularity,
+        other_related[[17]]$popularity,
+        other_related[[18]]$popularity,
+        other_related[[19]]$popularity,
+        other_related[[20]]$popularity
+      )),
+      followers = c(c(
+        other_related[[1]]$followers.total,
+        other_related[[2]]$followers.total,
+        other_related[[3]]$followers.total,
+        other_related[[4]]$followers.total,
+        other_related[[5]]$followers.total,
+        other_related[[6]]$followers.total,
+        other_related[[7]]$followers.total,
+        other_related[[8]]$followers.total,
+        other_related[[9]]$followers.total,
+        other_related[[10]]$followers.total,
+        other_related[[11]]$followers.total,
+        other_related[[12]]$followers.total,
+        other_related[[13]]$followers.total,
+        other_related[[14]]$followers.total,
+        other_related[[15]]$followers.total,
+        other_related[[16]]$followers.total,
+        other_related[[17]]$followers.total,
+        other_related[[18]]$followers.total,
+        other_related[[19]]$followers.total,
+        other_related[[20]]$followers.total
+      )),
+      profile = c(c(
+        other_related[[1]]$external_urls.spotify,
+        other_related[[2]]$external_urls.spotify,
+        other_related[[3]]$external_urls.spotify,
+        other_related[[4]]$external_urls.spotify,
+        other_related[[5]]$external_urls.spotify,
+        other_related[[6]]$external_urls.spotify,
+        other_related[[7]]$external_urls.spotify,
+        other_related[[8]]$external_urls.spotify,
+        other_related[[9]]$external_urls.spotify,
+        other_related[[10]]$external_urls.spotify,
+        other_related[[11]]$external_urls.spotify,
+        other_related[[12]]$external_urls.spotify,
+        other_related[[13]]$external_urls.spotify,
+        other_related[[14]]$external_urls.spotify,
+        other_related[[15]]$external_urls.spotify,
+        other_related[[16]]$external_urls.spotify,
+        other_related[[17]]$external_urls.spotify,
+        other_related[[18]]$external_urls.spotify,
+        other_related[[19]]$external_urls.spotify,
+        other_related[[20]]$external_urls.spotify
+      )),
+      images = images,
+      genre = genre
+    )
+
+    ## Remove duplicate nodes and labels in data frame
+
+    nodes_df <- distinct(nodes, name, id, popularity, profile,
+      images, genre, followers,
+      .keep_all = T
+    )
+
+
+    return(nodes_df)
+  }
+
+  # get related artists nodes
+  related_artists <- get_Nodes(artist_id = spotify_artist_id)
+
+  # get related artists data
+  artist_related_artists <- function(related_artist) {
+    related_artists_data <- list()
+
+    for (i in 1:nrow(related_artist)) {
+      # Get the artist ID from the second column of related_artists
+      artist_id <- related_artist[[2]][i]
+
+      # Retrieve the artist's albums using the artist ID
+      result <- get_artist_albums(artist_id, limit = 50)
+
+      # Create a data frame from the result
+      related_artists_albums <- data.frame(result)
+
+      # Add the data frame to the list
+      related_artists_data[[i]] <- related_artists_albums
+    }
+
+    return(related_artists_data)
+  }
+
+  related_artists_data <- artist_related_artists(related_artist = related_artists)
+
+  # get the artists collaborators
+  get_collaborators <- function(data, artist_name) {
+    artists <- c() # initialize empty vector
+    # outer loop loops through the length of artists list
+    for (i in 1:length(data$artists)) {
+      # inner loop loops through the length of individual
+      # "name" column in artists list
+      for (j in 1:length(data$artists[[i]][3][, ])) {
+        # scrapes the artist names
+        result <- data$artists[[i]][3][j, ]
+        # appends the names to "artists" vector
+        artists <- append(artists, result)
+      }
+    }
+
+    artists <- unique(artists) # removes duplicate names
+    artists <- tolower(artists) # turns to lowercase
+    # turns the search artist's name to NA
+    artists <- gsub(tolower(artist_name), NA, artists)
+    artists <- na.omit(artists) # remove NA from vector
+
+    return(artists)
+  }
+
+  # function that gets the collaborators data
+  collab_df <- function(related_artists_data, artist_data) {
+    collaborators <- c()
+    artists_list <- c()
+    for (i in 1:length(related_artists_data)) {
+      result <- get_collaborators(related_artists_data[[i]],
+        artist_name = artist_data[[1]][i]
+      )
+
+      collaborators <- c(collaborators, result)
+      artists_list <- c(artists_list, rep(artist_data[[1]][i], times = length(result)))
+    }
+
+    artists_collaborators <- data.frame(artists = artists_list, collaborators = collaborators)
+
+    return(artists_collaborators)
+  }
+
+  # application of the function
+  collabs <- collab_df(
+    related_artists_data = related_artists_data,
+    artist_data = related_artists
+  )
+
+  # get attribute data for each collaborator
+  attribute_data <- list()
+  for (i in 1:nrow(collabs)) {
+    attribute_data[[i]] <- search_spotify(collabs$collaborators[[i]],
+      type = "artist",
+      include_meta_info = T
+    )
+  }
+
+  # collect attributes of collaborators
+  {
+    name <- c()
+    id <- c()
+    popularity <- c()
+    followers <- c()
+    profile <- c()
+    images <- c()
+    genre <- c()
+
+    for (i in 1:length(attribute_data)) {
+      name <- c(name, attribute_data[[i]][[1]][[2]][5][[1]][1])
+      id <- c(id, attribute_data[[i]][[1]][[2]][3][[1]][1])
+      popularity <- c(popularity, attribute_data[[i]][[1]][[2]][6][[1]][1])
+      followers <- c(followers, attribute_data[[i]][[1]][[2]][11][[1]][1])
+      profile <- c(profile, attribute_data[[i]][[1]][[2]][9][[1]][1])
+      images <- c(images, attribute_data[[i]][[1]][[2]][4][[1]][1])
+      genre <- c(genre, attribute_data[[i]][[1]][[2]][1][[1]][1])
+    }
+  }
+
+  # loop through images list and store converted
+  # data frames in a list
+  images_df_list <- list()
+  for (i in 1:length(images)) {
+    images_df_list[[i]] <- list2DF(images[[i]])
+  }
+
+  # loop through the list of data frames & extract
+  # the image urls
+  images_vec <- c()
+  for (i in 1:length(images_df_list)) {
+    images_vec <- c(images_vec, images_df_list[[i]]$url[[1]][1])
+  }
+
+  len_diff_img <- name |>
+    length() - images_vec |>
+    length()
+
+  # add a repetition of the last 6 urls to the vector
+  # so that its length is equal to the length of other
+  # attribute vectors
+  images_vec <- c(
+    images_vec,
+    rep(images_vec[tail(length(images_vec))], times = len_diff_img)
+  )
+
+  # get genre data
+  genre_vec <- c()
+  for (i in 1:length(genre)) {
+    genre_vec <- c(genre_vec, genre[[i]][1])
+  }
+
+  music_genres <- c()
+  for (m in 1:length(genre_vec)) {
+    music_genres <- c(music_genres, genre_vec[[m]])
+  }
+
+  len_diff_gnr <- name |>
+    length() - music_genres |>
+    length()
+
+  music_genres <- c(
+    music_genres,
+    rep(music_genres[tail(length(music_genres))], times = len_diff_gnr)
+  )
+
+  # create collaborators data frame
+  collaborators_df <- data.frame(
+    name = name,
+    id = id,
+    popularity = popularity,
+    followers = followers,
+    profile = profile,
+    images = images_vec,
+    genre = music_genres
+  )
+
+  # filter out 2Pac
+  collaborators_df <- collaborators_df |>
+    filter(name != "2Pac")
+
+  # rename columns in collabs
+  colnames(collabs) <- c("Vertex1", "Vertex2")
+
+  # grab Vertex1 attributes
+  popularity <- c()
+  for (i in 1:nrow(collabs)) {
+    result <- filter(
+      related_artists,
+      related_artists$name == collabs$Vertex1[[i]][1]
+    )[[3]]
+    popularity <- c(popularity, result)
+  }
+
+  followers <- c()
+  for (i in 1:nrow(collabs)) {
+    result <- filter(
+      related_artists,
+      related_artists$name == collabs$Vertex1[[i]][1]
+    )[[4]]
+    followers <- c(followers, result)
+  }
+
+  profile <- c()
+  for (i in 1:nrow(collabs)) {
+    result <- filter(
+      related_artists,
+      related_artists$name == collabs$Vertex1[[i]][1]
+    )[[5]]
+    profile <- c(profile, result)
+  }
+
+  images <- c()
+  for (i in 1:nrow(collabs)) {
+    result <- filter(
+      related_artists,
+      related_artists$name == collabs$Vertex1[[i]][1]
+    )[[6]]
+    images <- c(images, result)
+  }
+
+  genre <- c()
+  for (i in 1:nrow(collabs)) {
+    result <- filter(
+      related_artists,
+      related_artists$name == collabs$Vertex1[[i]][1]
+    )[[7]]
+    genre <- c(genre, result)
+  }
+
+  # convert "names" in collaborators_df to lowercase
+  collaborators_df$name <- tolower(collaborators_df$name)
+
+  # filter out "various artists" from collabs
+  collabs <- collabs |>
+    filter(Vertex2 != "various artists")
+
+  # check if name in Vertex2 is an English character
+  ascii_check <- c()
+  for (i in 1:nrow(collabs)) {
+    ascii_check <- c(ascii_check, collabs$Vertex2[[i]][1] |> stringi::stri_enc_isascii())
+  }
+
+  # append check result to collabs dataframe
+  collabs$ASCII <- ascii_check
+
+  # filter out non-English characters
+  collabs <- collabs |>
+    filter(ASCII != FALSE)
+
+  # delete ASCII column
+  collabs$ASCII <- NULL
+
+  # delete rows from Vertex1 attributes to equal
+  # collabs rows
+  popularity <- popularity[-c(1 + length(popularity):nrow(collabs))]
+
+  followers <- followers[-c(1 + length(followers):nrow(collabs))]
+
+  profile <- profile[-c(1 + length(profile):nrow(collabs))]
+
+  images <- images[-c(1 + length(images):nrow(collabs))]
+
+  genre <- genre[-c(1 + length(genre):nrow(collabs))]
+
+  # grab Vertex2 attributes
+  popularityB <- c()
+  for (i in 1:nrow(collabs)) {
+    result <- filter(
+      collaborators_df,
+      collaborators_df$name == collabs$Vertex2[[i]][1]
+    )[[3]]
+    popularityB <- c(popularityB, result)
+  }
+
+  followersB <- c()
+  for (i in 1:nrow(collabs)) {
+    result <- filter(
+      collaborators_df,
+      collaborators_df$name == collabs$Vertex2[[i]][1]
+    )[[4]]
+    followersB <- c(followersB, result)
+  }
+
+  profileB <- c()
+  for (i in 1:nrow(collabs)) {
+    result <- filter(
+      collaborators_df,
+      collaborators_df$name == collabs$Vertex2[[i]][1]
+    )[[5]]
+    profileB <- c(profileB, result)
+  }
+
+  imagesB <- c()
+  for (i in 1:nrow(collabs)) {
+    result <- filter(
+      collaborators_df,
+      collaborators_df$name == collabs$Vertex2[[i]][1]
+    )[[6]]
+    imagesB <- c(imagesB, result)
+  }
+
+  genreB <- c()
+  for (i in 1:nrow(collabs)) {
+    result <- filter(
+      collaborators_df,
+      collaborators_df$name == collabs$Vertex2[[i]][1]
+    )[[7]]
+    genreB <- c(genreB, result)
+  }
+
+  # delete rows from Vertex2 attributes to equal
+  # collabs rows
+  popularityB <- popularityB[-c(1 + length(popularityB):nrow(collabs))]
+
+  followersB <- followersB[-c(1 + length(followersB):nrow(collabs))]
+
+  profileB <- profileB[-c(1 + length(profileB):nrow(collabs))]
+
+  imagesB <- imagesB[-c(1 + length(imagesB):nrow(collabs))]
+
+  genreB <- genreB[-c(1 + length(genreB):nrow(collabs))]
+
+  # create flat file of collaborators
+  {
+    collabs$`Vertex1 popularity` <- popularity
+    collabs$`Vertex1 followers` <- followers
+    collabs$`Vertex1 profile` <- profile
+    collabs$`Vertex1 images` <- images
+    collabs$`Vertex1 genre` <- genre
+
+    collabs$`Vertex2 popularity` <- popularityB
+    collabs$`Vertex2 followers` <- followersB
+    collabs$`Vertex2 profile` <- profileB
+    collabs$`Vertex2 images` <- imagesB
+    collabs$`Vertex2 genre` <- genreB
+  }
+
+
+
+  return(collabs)
+  
+  
+}
+
+# test
+# tictoc::tic()
+# steve_wonder_collab_network <- get_artists_collaborators(spotify_artist_id = "7guDJrEfX3qb6FEbdPA5qi")
+# tictoc::toc()
+# 
+# 
+# steve_wonder_collab_network |> View()
+# 
+# tictoc::tic()
+# billie_eilish_collab_network <- get_artists_collaborators(spotify_artist_id = "6qqNVTkY8uBg9cP3Jd7DAH")
+# tictoc::toc()
+# 
+# billie_eilish_collab_network |> View()
+# write.csv(billie_eilish_collab_network,file = "billie_eilish_collab_network.csv")
+# 
+# tictoc::tic()
+# madonna_collab_network <- get_artists_collaborators(spotify_artist_id = "6tbjWDEIzxoDsBA1FuhfPW")
+# tictoc::toc()
+# 
+# madonna_collab_network |> View()
+# 
+# tictoc::tic()
+# diana_ross_collab_network <- get_artists_collaborators(spotify_artist_id = "3MdG05syQeRYPPcClLaUGl")
+# tictoc::toc()
+#