Testing Rmarkdown with Spotify dataset example

This dataset was reply from the OpenScience Course of the university of Cádiz (Original: https://www.kaggle.com/datasets/leonardopena/top-spotify-songs-from-20102019-by-year/)
Dataset Overview:

The dataset contains 603 records and 15 columns, representing the most successful Spotify songs from 2010 to 2019. It includes song attributes such as tempo, energy, danceability, loudness, and popularity.

Metadata Description:
Column Name    Description
Unnamed: 0    An index column (can be ignored).
title    The title of the song.
artist    The name of the artist who performed the song.
top genre    The primary genre of the song.
year    The year the song was released.
bpm    The beats per minute (tempo) of the song.
nrgy    The energy level of the song (0-100), where higher values indicate more energetic songs.
dnce    The danceability of the song (0-100), where higher values indicate a more danceable track.
dB    The loudness of the song in decibels (dB).
live    The liveness score (0-100), indicating the presence of a live audience.
val    The valence score (0-100), representing the mood of the song (higher values mean happier and more positive songs).
dur    The duration of the song in seconds.
acous    The acousticness score (0-100), where higher values indicate a more acoustic sound.
spch    The speechiness score (0-100), measuring spoken words in the track.
pop    The popularity score (0-100), where higher values indicate a more popular song.

This dataset is useful for analyzing trends in song characteristics over time, such as the evolution of tempo, loudness, and energy levels in popular music.