Datasets:
| """ | |
| Plots a pie-chart showing an overview of the genre distribution in the dataset | |
| """ | |
| import csv | |
| import random | |
| import matplotlib.pyplot as plt | |
| import seaborn as sns | |
| # Go through metadata CSV and read genre attribute | |
| with open("../JamendoLyrics.csv", "r") as f: | |
| rows = csv.DictReader(f) | |
| genres = [row["Genre"] for row in rows] | |
| unique_genres = list(set(genres)) | |
| genre_freq = [len([g for g in genres if g == target]) for target in unique_genres] | |
| # define Seaborn color palette to use | |
| colors = sns.color_palette("Set3") | |
| random.shuffle(colors) | |
| plt.rcParams["font.family"] = "serif" | |
| plt.rcParams["font.serif"] = ["Times New Roman"] | |
| plt.rcParams["font.size"] = 14 | |
| # Create pie chart | |
| plt.pie( | |
| genre_freq, | |
| labels=unique_genres, | |
| radius=1, | |
| wedgeprops=dict(width=0.3, edgecolor="w"), | |
| colors=colors, | |
| ) | |
| plt.savefig("genre_distribution.pdf", bbox_inches="tight") | |