Description
The following documents are project description and dataset. There is one more dataset which is too big. I can uploade it on webstie.
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Introduction to Data Science – DS GA 1001
Capstone project
The purpose of this capstone project is to tie everything we learned in this class together. This might be
challenging in the short term, but is consistently rated by students as being extremely valuable and useful
in the long run. The cover story this time is that you are working as a Data Scientist for Spotify. You have
data on a set of 52,000 songs and you want to better understand what makes music popular as well as
the audio features that make up specific genres. Historically, this domain was dominated by musicians
and music theorists, but is increasingly the domain of the data scientist.
This is where you come in: Can you provide the value that justifies your rather high salary?
Mission command preamble: As usual, we won’t tell you *how* to do something. That is up
to you and allows you to showcase your creative problem-solving skills. However, we will pose the
questions that you should answer by interrogating the data.
Format: The project consist of your answers to 10 (equally-weighed, grade-wise) questions. Each answer
*must* include some text (describing both what you did and what you found, i.e. explicitly stating the
answer to the question), a figure that illustrates the findings and some numbers (e.g. test statistics,
confidence intervals, p-values or the like). Please save it as a pdf document. This document should be 5-7
pages long (arbitrary font size and margins). About ½ a page/question is reasonable. In addition, open
your document with a title page where you introduce your group (and group name), state author
contributions as well as statements as to how you handled preprocessing (e.g. dimension reduction, data
cleaning and data transformations), as this will apply to all answers.
Academic integrity: You are expected to do this project as a group. So make sure this works reflects your
intellectual contribution – not that of third parties. Feel free to use generative AI like chatGPT to aid you
in this task, but make sure to specify in the author contributions how you used if, if you did. There are
enough degrees of freedom (e.g. how to clean the data, what variables to compare, aesthetic choices in
the figures, etc.) that no two reports will be alike. We’ll be on the lookout for suspicious
similarities, so please refrain from collaborating.
To prevent cheating (please don’t do this – it is easily detected), it is very important that you –
at the beginning of the code file – seed the random number generator with the N-number of one of your
team members (specify which one). That way, the correct answers will be keyed to your own solution (as
this matters, e.g. for the specific train/test split or bootstrapping).
As N-numbers are unique, this will also protect your work from plagiarism.
Failure to seed the RNG in this way will also result in the loss of grade points.
Deliverables: Upload two files to the Brightspace portal by the due date in the sittyba:
*A pdf (the “project report”) that contains your answers to the questions, as well as
an introductory
paragraph about preprocessing, how you seeded the RNG, etc.
*A .py file with the code that performed the data analysis and created the figures. This will help us
understand what you were trying to attempt – in particular if you get the “wrong” answer.
We do wish you all the best in executing on these instructions. We aimed at an optimal balance between
specificity and implementation leeway, while still allowing us to grade the projects in a fast, fair and
faithful (=consistent and accurate) manner (FFF).
Everything we ask for should be doable from what was covered in this course.
Description of dataset: This dataset consists of data on 52,000 songs that were randomly picked from a
variety of genres sorted in alphabetic order (a as in “acoustic” to h as in “hiphop”). For
the purposes of this analysis, you can assume that the data for one song are independent for data
from other songs.
This data is stored in the file “spotify52kData.csv”, as follows:
Row 1: Column headers
Row 2-52001: Specific individual songs
Column 1: songNumber – the track ID of the song, from 0 to 51999.
Column 2: artist(s) – the artist(s) who are credited with creating the song.
Column 3: album_name – the name of the album
Column 4: track_name – the title of the specific track corresponding to the track ID
Column 5: popularity – this is an important metric provided by spotify, an integer from 0 to 100, where a
higher number corresponds to a higher number of plays on spotify.
Column 6: duration – this is the duration of the song in ms. A ms is a millisecond. There are a thousand
milliseconds in a second and 60 seconds in a minute.
Column 7: explicit – this is a binary (Boolean) categorical variable. If it is true, the lyrics of the track
contain explicit language, e.g. foul language, swear words or content that some consider indecent.
Column 8: danceability – this is an audio feature provided by the Spotify API. It tries to quantify how
easy it is to dance to the song (presumably capturing tempo and beat), and varies from 0 to 1.
Column 9: energy – this is an audio feature provided by the Spotify API. It tries to quantify how “hard” a
song goes. Intense songs have more energy, softer/melodic songs lower energy, it varies from 0 to 1.
Column 10: key – what is the key of the song, from A to G# (mapped to categories 0 to 11).
Column 11: loudness – average loudness of a track in dB (decibels)
Column 12: mode – this is a binary categorical variable. 1 = song is in major, 0 – song is in minor
Column 13: speechiness – quantifies how much of the song is spoken, varying from 0 (fully instrumental
songs) to 1 (songs that consist entirely of spoken words).
Column 14: acousticness – varies from 0 (song contains exclusively synthesized sounds) to 1 (song
features exclusively acoustic instruments like acoustic guitars, pianos or orchestral instruments).
Column 15: instrumentalness – basically the inverse of speechiness, varying from 1 (for songs without
any vocals) to 0.
Column 16: liveness – this is an audio feature provided by the Spotify API. It tries to quantify how likely
the recording was live in front of an audience (values close to 1) vs. how likely it was recorded in a studio
without a live audience (values close to 0).
Column 17: valence – this is an audio feature provided by the Spotify API. It tries to quantify how
uplifting a song is. Songs with a positive mood =close to 1 and songs with a negative mood =close to 0
Column 18: tempo – speed of the song in beats per minute (BPM)
Column 19: time_signature – how many beats there are in a measure (usually 4 or 3)
Column 20: track_genre – genre assigned by spotify, e.g. “blues” or “classical”. 1k songs per
genre.
In addition, there is a file (“starRatings.csv”) that contains explicit feedback, specifically star ratings
from 10k users on 5k songs they listened to, on a scale from 0 (lowest) to 4 (highest). In this file, there
are no headers. Each row corresponds to a user and each column to a song, specifically to the first 5k
rows (songs) in the spotify52kData.csv dataset, in the same order. Missing data is represented as nans.
Note that we did most of the data munging and coding for you already but you still need to handle
missing data in some way (e.g. by row-wise removal, element-wise removal, imputation, masking, etc.).
Also, if there are skewed distributions, extreme values might also have to be handled.
Corporate needs you to find the answers to these questions:
1) Is there a relationship between song length and popularity of a song? If so, is it positive or negative?
2) Are explicitly rated songs more popular than songs that are not explicit?
3) Are songs in major key more popular than songs in minor key?
4) Which of the following 10 song features: duration, danceability, energy, loudness, speechiness,
acousticness, instrumentalness, liveness, valence and tempo predicts popularity best?
How good is this model?
5) Building a model that uses *all* of the song features mentioned in question 1, how well can you
predict popularity? How much (if at all) is this model improved compared to the model in question
4). How do you account for this? What happens if you regularize your model?
6) When considering the 10 song features in the previous question, how many meaningful principal
components can you extract? What proportion of the variance do these principal components
account for? Using these principal components, how many clusters can you identify? Do these
clusters reasonably correspond to the genre labels in column 20 of the data?
7) Can you predict whether a song is in major or minor key from valence using logistic regression or a
support vector machine? If so, how good is this prediction? If not, is there a better one?
8) Can you predict genre by using the 10 song features from question 4 directly or the principal
components you extracted in question 6 with a neural network? How well does this work?
9) In recommender systems, the popularity based model is an important baseline. We have a two part
question in this regard: a) Is there a relationship between popularity and average star rating for the
5k songs we have explicit feedback for? b) Which 10 songs are in the “greatest
hits” (out of the 5k songs), on the basis of the popularity based model?
10) You want to create a “personal mixtape” for all 10k users we have explicit
feedback for. This mixtape contains individualized recommendations as to which 10 songs (out
of the 5k) a given user will enjoy most. How do these recommendations compare to
the “greatest hits” from the previous question and how good is your recommender system
in making recommendations?
Extra credit: Tell us something interesting about this dataset that is not trivial and not already part of an
answer (implied or explicitly) to these enumerated questions [Suggestion: Do something with the
number of beats per measure, something with the key, or something with the song or album titles]
Hints:
*Beware of off-by-one errors. This document and the csv data files index from 1, but Python indexes
from 0. Make sure to keep track of this.
*In order to answer some of these questions, you might have to apply a dimension reduction method
first. Similarly, you might have to reduce variables to their summary statistics.
*In order to do some analyses, you will have to clean the data first, either by removing or imputing
missing data or handling it in some other way (either is fine, but explain and justify what you did)
*If you encounter skewed data, you might want to transform the data first, e.g. by z-scoring
*To clarify: When talking about “principal components” above, we mean the
transformed data, rotated
into the new coordinate system by the PCA.
*Avoid overfitting with cross-validation methods when making predictions.
*How well your model predicts can be assessed with RMSE or R2 for regression models, and AUC for
classification models. Use a suitable metric such as average precision for recommender systems.
*You can use conventional choices of alpha (e.g. 0.05) or confidence intervals (e.g. 95%) throughout.
*Make sure to actually answer all questions (particularly for multi-part of questions) that were asked
explicitly, for full credit. Make sure to follow style and logistics instructions (e.g. no seeding of RNG with
N-number, no statement of author contributions, etc.) to avoid losing points.
songNumber
artists
0 Gen Hoshino
album_name
track_name
Comedy
Comedy
popularity
duration
explicit
73
230666
FALSE
1 Ben Woodward Ghost (Acoustic)Ghost – Acoustic
55
149610
FALSE
2 Ingrid Michaelson;ZAYN
To Begin Again To Begin Again
57
210826
FALSE
Crazy Rich Asians
Can’t
(Original
Help Falling
MotionInPicture
Love Soundtrack)
71
201933
FALSE
3 Kina Grannis
4 Chord Overstreet
Hold On
Hold On
82
198853
FALSE
Days I Will Remember
Days I Will Remember
58
214240
FALSE
6 A Great Big World;Christina
Is There Anybody
Aguilera
Say
Out
Something
There?
74
229400
FALSE
7 Jason Mraz
We Sing. We Dance.
I’m Yours
We Steal Things.
80
242946
FALSE
8 Jason Mraz;Colbie
WeCaillat
Sing. We Dance.
Lucky We Steal Things.
74
189613
FALSE
9 Ross Copperman
Hunger
Hunger
56
205594
FALSE
10 Zack Tabudlo Episode
Give Me Your Forever
74
244800
FALSE
5 Tyrone Wells
11 Jason Mraz
Love Is a Four Letter
I Won’t
Word
Give Up
69
240165
FALSE
12 Dan Berk
Solo
Solo
52
198712
FALSE
Bad Liar
62
248448
FALSE
56
188133
FALSE
The Boy Who Never
Falling in Love at a Coffee Shop
58
244986
FALSE
13 Anna Hamilton Bad Liar
14 Chord Overstreet;Deepend
Hold On (Remix)Hold On – Remix
15 Landon Pigg
16 Andrew Foy;Renee
ily (i Foy
love you baby)
ily (i love you baby)
56
129750
FALSE
17 Andrew Foy;Renee
At My
Foy
Worst
54
169728
FALSE
18 Jason Mraz;Colbie
WeCaillat
Sing. We Dance.
Lucky We Steal Things.
68
189613
FALSE
19 Boyce Avenue;Bea
Cover
Miller
Sessions,Photograph
Vol. 4
67
260186
FALSE
20 Jason Mraz
75
242946
FALSE
63
174174
FALSE
22 A Great Big World;Christina
Is There Anybody
Aguilera
Say
Out
Something
There? – Track by Track
70 Commentary
229400
FALSE
23 Jason Mraz
Coffee Moment93 Million Miles
0
216386
FALSE
24 Jason Mraz
Human – Best Adult
Unlonely
Pop Tunes
0
231266
FALSE
25 Jason Mraz
Mellow Adult Pop
Bella Luna
1
302346
FALSE
26 Jason Mraz
Holly Jolly Christmas
Winter Wonderland
0
131760
FALSE
27 Jason Mraz
Feeling Good – Adult
If It Kills
PopMe
Favorites
0
273653
FALSE
28 Jason Mraz
Christmas TimeWinter Wonderland
0
131760
FALSE
29 Jason Mraz
Perfect Christmas
Winter
Hits Wonderland
0
131760
FALSE
30 Jason Mraz
Merry ChristmasWinter Wonderland
0
131760
FALSE
31 Jason Mraz
Christmas MusicWinter
– Holiday
Wonderland
Hits
0
131760
FALSE
32 Chord Overstreet
Christmas Country
All ISongs
Want For
2022
Christmas Is A 0Real Good
234186
Tan
FALSE
33 Brandi Carlile;Sam
Human
Smith
– Best Adult
PartyPop
of One
Tunes
0
259558
FALSE
34 Brandi Carlile;Sam
Feeling
Smith
Good – Adult
Party Pop
of One
Favorites
0
259558
FALSE
35 Brandi Carlile;Sam
Mellow
Smith
Bars R’n’B
Party of One
0
259558
FALSE
36 KT Tunstall
0
257493
FALSE
37 Brandi Carlile rainy day indie Throwing Good After Bad
0
247791
FALSE
38 Brandi Carlile Coffee MomentThis Time Tomorrow
0
206267
FALSE
39 KT Tunstall
At My Worst
We Sing. We Dance.
I’m Yours
We Steal Things.
21 Boyce Avenue;Jennel
Cover Garcia
Sessions,Demons
Vol. 3
Chill Christmas Lonely
Dinner This Christmas
0
257493
FALSE
40 Eddie Vedder Mega Hits Autumn/Fall
The Haves
2022
sadsadchristmas
Lonely This Christmas
0
306794
FALSE
41 Brandi Carlile Mellow Adult Pop
When You’re Wrong
0
266960
FALSE
42 Brandi Carlile;Lucius
Country Car HitsYou and Me on the Rock
0
230098
FALSE
43 Brandi Carlile;Lucius
Country Road Songs
You and Me on the Rock
0
230098
FALSE
44 Brandi Carlile Finest Country Speak Your Mind (From the Netflix
0
Series
193943
“We TheFALSE
People”)
45 Brandi Carlile;Lucius
Easy Country You and Me on the Rock
0
230098
FALSE
46 Brandi Carlile;Lucius
Cozy Country You and Me on the Rock
0
230098
FALSE
47 Brandi Carlile;Lucius
Good Times Country
You and Me on the Rock
0
230098
FALSE
48 Brandi Carlile;Lucius
Laidback Country
You and Me on the Rock
0
230098
FALSE
49 Brandi Carlile;Lucius
Chillin’ It – Mellow
You
Day
and
Country
Me on the Rock
0
230098
FALSE
50 Highland Peak Trampoline (Acoustic)
Trampoline – Acoustic
46
213098
FALSE
51 Motohiro Hata Documentary 透明だった世界
61
232360
FALSE
52 Andrew Belle
Black Bear
Pieces
60
241119
FALSE
53 Ron Pope
The Bedroom Demos
A Drop in the Ocean
68
220239
FALSE
54 Adam Christopher
So Far Away (Acoustic)
So Far Away – Acoustic
52
171543
FALSE
55 Andrew Belle
Black Bear
62
286865
FALSE
56 Aron Wright
Build It Better Build It Better
51
234473
FALSE
57 Chord Overstreet
Sleepwalking in Sleepwalking
the Rain
in the Rain
0
216000
FALSE
58 Sara Bareilles Little Voice
67
232760
FALSE
59 Chord Overstreet
What’s Left of You
What’s Left of You
57
178600
TRUE
60 Zack Tabudlo Pano
75
254400
FALSE
The Enemy
Gravity
Pano
61 Andrew Belle
The Daylight EPSky’s Still Blue
62
244320
FALSE
62 Kurt Cobain
Montage Of Heck:
AndThe
I Love
Home
HerRecordings
66
124933
FALSE
63 Boyce Avenue;Bea
Cover
Miller
Sessions,We
Vol.Can’t
3 Stop
64
222146
FALSE
64 Tim Halperin
Covers
62
181852
FALSE
65 Canyon City
Midnight WavesAlone with You
58
186584
FALSE
66 Aaron Espe
Making All Things
Making
New All Things New
65
159600
FALSE
67 Sara Bareilles What’s Inside: Songs
She Used
fromTo
Waitress
Be Mine
67
250266
FALSE
318908
FALSE
Always Be My Baby
68 Andrew Belle
In My Veins (Feat.
In My
ErinVeins
Mccarley)
– Feat. Erin Mccarley
65
69 Tyler Ward
Under Covers I Don’t Wanna Live Forever 44
(Fifty Shades
222351
Darker) FALSE
70 Ron Pope
Whatever It Takes
A Drop In the Ocean
55
219480
FALSE
71 Five For Fighting
America Town Superman (It’s Not Easy)
70
221693
FALSE
72 Andrew Belle
Dive Deep
57
354400
FALSE
73 Bailey Jehl
You’re Still The You’re
One Still The One
When the End Comes
56
177500
FALSE
74 Ingrid Michaelson
It Doesn’t Have Light
To Make
Me Up
Sense
56
247840
FALSE
75 Jason Mraz
67
216386
FALSE
76 A Great Big World
When the Morning
Kaleidoscope
Comes
62
229320
FALSE
77 Eddie Vedder;Nusrat
Eat, Pray,
FatehLove
Ali Khan
The Long Road
45
330933
FALSE
78 Drew Holcomb &
Good
The Light
NeighborsWhat Would I Do Without You
64
172213
FALSE
79 Jason Mraz
65
226106
FALSE
80 Gabrielle Aplin Mellow Adult Pop
Heavy Heart
0
235173
FALSE
81 Gabrielle Aplin Break Up SongsThe House We Never Built
0
195213
FALSE
82 Eddie Vedder Into The Wild (Music
Society
For The Motion Picture)
68
236306
FALSE
83 Gabrielle Aplin u don’t deserve Please
me
Don’t Say You Love Me
0
181400
FALSE
84 Gabrielle Aplin Coffee MomentPlease Don’t Say You Love Me
0
181400
FALSE
85 Eddie Vedder Into The Wild (Music
Guaranteed
For The Motion Picture)
61
164500
FALSE
86 Sara Bareilles The Blessed Unrest
Brave
220573
FALSE
Love Is a Four Letter
93 Million
WordMiles
Know.
Have It All
70
87 KT Tunstall
Slow ChristmasLonely
Songs This
2022Christmas
0
257493
FALSE
88 KT Tunstall
Lonely Christmas
Lonely
2022This Christmas
0
257493
FALSE
62
210612
FALSE
90 The Civil Wars Slow ChristmasISongs
Heard 2022
The Bells On Christmas
0 Day 154440
FALSE
91 The Civil Wars Alternative Christmas
I Heard2022
The Bells On Christmas
0 Day 154440
FALSE
92 KT Tunstall
263866
FALSE
93 The Civil Wars Acoustic Christmas
I Heard
Campfire
The Bells On Christmas
0 Day 154440
FALSE
94 The Civil Wars Lonely Christmas
I Heard
2022 The Bells On Christmas
0 Day 154440
FALSE
95 The Civil Wars Chill Christmas IDinner
Heard The Bells On Christmas
0 Day 154440
FALSE
96 The Civil Wars sadsadchristmas
I Heard The Bells On Christmas
0 Day 154440
FALSE
97 The Civil Wars Christmas Country
I Heard
Songs
The
2022
Bells On Christmas
0 Day 154440
FALSE
98 KT Tunstall
Del gusto de mamá
Hold On
0
177613
FALSE
99 KT Tunstall
OO’s Music Grandi
Suddenly
Successi
I See
0
199040
FALSE
58
293040
FALSE
101 Callum J WrightSomebody ElseSomebody
(Acoustic) Else – Acoustic 50
138495
FALSE
102 Andrew Belle
59
198626
FALSE
103 Boyce Avenue;Fifth
Cover
Harmony
Sessions,Mirrors
Vol. 3
57
292566
FALSE
104 Boyce Avenue Stand by Me
Stand by Me
60
199019
FALSE
105 Gabrielle Aplin;JP
Dear
Cooper
Happy
Losing Me
61
181760
FALSE
106 Mone Kamishiraishi
chouchou
89 Five For Fighting
Bookmarks
Heaven Knows
Alternative Christmas
Fairytale
2022
Of New York
100 Motohiro Hata 言ノ葉
Rain
Black Bear (Hushed)
Pieces (Hushed)
0
なんでもないや – movie ver.49
349920
FALSE
107 John Adams
You’re BeautifulYou’re
(Acoustic)
Beautiful – Acoustic 55
204973
FALSE
108 Kitri
Hikare Inochi
51
322146
FALSE
109 Tyler Ward
Songs From Nashville
How To Lose a Girl
46
210375
FALSE
110 Boyce Avenue Cover Sessions,Can’t
Vol. 6
Help Falling in Love
57
131000
FALSE
111 Andrew Belle
58
Hikare Inochi
218531
FALSE
112 Ben Woodward When the Party’s
When
over the
(Acoustic
Party’sPiano)
over (Acoustic
51 Piano)195945
Dive Deep (Hushed)
Dive Deep (Hushed)
FALSE
113 Augustana
All The Stars and
Boston
Boulevards
63
245933
FALSE
114 Matthew Perryman
Living
Jones
in the Shadows
Living in the Shadows
53
212386
FALSE
115 Boyce Avenue Cover Sessions,InVol.
Case
4 You Didn’t Know
60
225165
FALSE
116 Andrew Foy;Renee
death
Foy
bed (coffee
death
for your
bed (coffee
head) for your head)
47
112008
FALSE
117 Kina Grannis
You Are My Sunshine
You Are My Sunshine
60
123609
FALSE
118 Jason Mraz
I Won’t Give UpI Won’t Give Up
66
240165
FALSE
67
265843
FALSE
Life Sucks Playlist
Only Love Can Hurt Like This
43
194194
FALSE
119 Ray LaMontagne;Sierra
I Was Born
Ferrell
To Love
I WasYou
Born To Love You
120 Meg Birch
121 Catherine FeenyHurricane GlassMr Blue
54
154600
FALSE
122 Joshua Hyslop Where The Mountain
Do NotMeets
Let Me
The
GoValley
60
158960
FALSE
123 Ross Copperman
Holding On AndHolding
Letting Go
On -And
Single
Letting Go 49
319000
FALSE
124 JJ Heller
57
214360
FALSE
125 Ben Woodward Believer (Remix)Believer (Remix)
42
204480
FALSE
126 Howie Day
Stop All the World
Collide
Now-(Special
AcousticEdition)
Version
67
277000
FALSE
127 Ben Rector
Magic
61
214240
FALSE
71
215173
FALSE
You Already Know
You Already Know
Love Like This
128 Matt NathansonSome Mad Hope
Come On Get Higher
129 Rachael Yamagata
Something In the
“Something
Rain (Music
In from
the Rain”
the Original
(Something
49 TV Series)
In 296862
the Rain, Pt.FALSE
1) [Music from the Original T
130 Parachute
The Way It WasKiss Me Slowly
61
235813
FALSE
131 Parachute
Wide Awake
132 Jason Mraz
Without You
61
228933
FALSE
Waiting for My Rocket
Absolutely
to Come
Zero (Expanded Edition)
20
339196
FALSE
133 Jason Mraz
Waiting for My Rocket
Sleep All
to Day
Come (Expanded Edition)
22
296843
FALSE
134 Jason Mraz
Waiting for My Rocket
You and
toICome
Both (Expanded Edition)
35
218240
FALSE
135 Eddie Vedder Into The Wild (Music
Long For
Nights
The Motion Picture)
60
151773
FALSE
136 Gabrielle Aplin English Rain
181400
FALSE
201706
FALSE
Please Don’t Say You Love Me
59
137 KT Tunstall
Eye To The Telescope
Suddenly I See
73
138 Jason Mraz
Waiting for My Rocket
Who Needs
to Come
Shelter
(Expanded Edition)
22
192260
FALSE
139 Jason Mraz
Waiting for My Rocket
No Stopping
to Come
Us (Expanded Edition)
19
198855
FALSE
140 Jason Mraz
Waiting for My Rocket
I’ll Do Anything
to Come (Expanded Edition)
24
191889
FALSE
141 JJ Heller
I Dream of You:Make
CALMYou Feel My Love
171293
FALSE
142 Jason Mraz
Waiting for My Rocket
The Remedy
to Come
(I Won’t
(Expanded
Worry)Edition)
35
256440
FALSE
143 Jason Mraz
Waiting for My Rocket
Too Much
to Come
Food (Expanded Edition)
20
221425
FALSE
144 Jason Mraz
Waiting for My Rocket
The Boy’s
to Come
Gone (Expanded Edition)
18
255047
FALSE
145 Jason Mraz
Waiting for My Rocket
On Love,
to Come
in Sadness
(Expanded Edition)
19
208793
FALSE
146 Jason Mraz
Waiting for My Rocket
Curbside
to Come
Prophet
(Expanded Edition)
23
214552
FALSE
147 Jason Mraz
Waiting for My Rocket
Tonight,toNot
Come
Again
(Expanded
– Live Edition)
19
264280
FALSE
148 Jason Mraz
Waiting for My Rocket
Tonight,toNot
Come
Again
(Expanded Edition)
18
289041
FALSE
149 Eddie Vedder Into The Wild (Music
Hard Sun
For The Motion Picture)
65
322080
FALSE
150 Susie Suh;Robot
Here
Koch
with Me
57
Here with Me
55
238971
FALSE
151 Tyler Ward;Lindsey
TylerStirling;Kina
Ward Covers,
The
Grannis
Vol.
Scientist
5
47
276575
FALSE
152 Howie Day
56
249120
FALSE
Stop All The World
Collide
Now
153 Eden Elf;Ren Avel
get better
get better
53
111734
FALSE
154 Kitri
Hikare Inochi
Sympathy
49
210760
FALSE
155 Boyce Avenue;Rachel
Let It Go
Grae
Let It Go
51
255688
FALSE
156 Chord Overstreet
What You NeedWhat You Need
53
181786
FALSE
157 Five For Fighting
The Battle for Everything
100 Years
66
244600
FALSE
158 Andrew Belle
56
174546
FALSE
159 Rachael Yamagata
One Spring Night
No(Original
DirectionTelevision Soundtrack),
47
Pt. 234330
1
FALSE
160 Cary Brothers Under Control Belong
51
255600
FALSE
161 The Mayries
As It Was
As It Was
55
176542
FALSE
162 Jason Mraz
I’m Yours
I’m Yours
60
243494
FALSE
Chi Mai
40
188695
FALSE
164 A Great Big World;Christina
Say Something
Aguilera
Say Something
58
229400
FALSE
165 Parachute
55
216853
FALSE
166 Zack Tabudlo;Yonnyboii
Take Me Back Take Me Back ft. Yonnyboii 50
149000
FALSE
167 Tobey Rosen
Whole Again (Acoustic
Whole Again
Version)
– Acoustic Version
52
157231
FALSE
168 The Mayries
Overpass Graffiti
Overpass Graffiti
54
226603
FALSE
Nightshade
163 Joseph SullingerChi Mai
Parachute
You’re the Sea
Had It All
169 Sara Bareilles Little Voice
Love Song
73
258826
FALSE
170 Andrew Foy;Renee
Let Her
Foy Go
Let Her Go
38
194013
FALSE
171 Aqualung
Brighter Than Sunshine
53
242439
FALSE
172 Tyler Ward;Karis;Ray
Love Story
Lorraine Love Story
Still Life
55
232500
FALSE
173 Agustín Amigó;Nylonwings
Mujer con Abanico
Mujer con Abanico
41
156787
FALSE
174 Amy Stroup
46
263823
FALSE
In the Shadows In the Shadows
175 Boyce Avenue;Connie
Can You
Talbot
Feel the
Can
Love
YouTonight
Feel the Love Tonight
63
250916
FALSE
176 Brandi Carlile The Story
The Story
66
238493
FALSE
177 JJ Heller
Better
Better
54
215906
FALSE
178 Kina Grannis
Iris
Iris
62
181136
FALSE
179 The Mayries
#Acoustic
Rockabye – Acoustic Version57
157466
FALSE
180 Caleb Santos;Viva
I Need
Music
You
Publishing
More
I Need
Today
Inc.
You More Today
68
233728
FALSE
181 Boyce Avenue Cover Sessions,Beautiful
Vol. 4 Soul
62
216612
FALSE
245186
FALSE
182 Jason Mraz
Know.
Let’s See What The Night Can
53 Do
183 Rachael Yamagata
Something In the
LaRain
La La
(Music
(Something
from the
InOriginal
the Rain,
44 TVPt.Series)
2)219613
[Music fromFALSE
the Original TV Series]
184 Parachute
The Way It WasForever And Always
185 Priscilla Ahn
When Marnie Was
FineThere
On The
Song
Outside
Album – Just52
Know That
252466
I Love You.FALSE
57
248960
FALSE
186 Chord Overstreet
Tree House Tapes
Tortured Soul
53
246613
FALSE
187 JJ Heller
I Believe in YouI Believe in You
53
198786
FALSE
188 Jon Bryant
Cult Classic
55
226640
FALSE
At Home
189 Donovan WoodsHard Settle, Ain’tPortland,
TroubledMaine
66
203869
FALSE
190 Ross Copperman
Holding On and Holding
Letting Go
On LP
and Letting Go 49
317441
FALSE
191 Joshua Hyslop In Deepest BlueThe
(Bonus
Flood
Track Version)
261640
FALSE
192 Angelina Cruz Hanggang Kailan
Hanggang
(Umuwi Ka
Kailan
Na Baby)
(Umuwi Ka38Na Baby)211933
FALSE
193 Stephen SpeaksNo More Doubt Out of My League
218800
FALSE
194 A Great Big World
Is There Anybody
Say
Out
Something
There? – Track by Track
57 Commentary
233266
FALSE
195 Eddie Vedder Into The Wild (Music
Rise For The Motion Picture)
60
156453
FALSE
196 The Weepies;Deb
SayTalan;Steve
I Am You World
TannenSpins Madly On
64
165133
FALSE
197 Freddie King
Thanksgiving Party
Stumble
0
216626
FALSE
198 Taj Mahal
Supa Chill
0
251426
FALSE
199 Keb’ Mo’;GeraldUn
Albright
tecito y a mimir
Moonlight, Mistletoe & You
0
209293
FALSE
200 Motohiro Hata 青の光景
61
308146
FALSE
201 Thomas Daniel Since U Been Gone
Since U Been Gone – Acoustic
50 Version221170
FALSE
202 Masayoshi Yamazaki
One more time,One
One more chance
time,One more chance
47
330786
FALSE
203 Kina Grannis
58
234135
FALSE
204 Todd Carey;Ariza;Chuck
Higher Love
LeavellHigher Love
30
173250
FALSE
205 YUZU
Shinsekai
52
336619
FALSE
206 Canyon City
How Long Will IHow
LoveLong
You Will I Love You 55
144830
FALSE
221538
FALSE
192972
FALSE
Creep
207 Zack Tabudlo Binibini
208 Aron Wright
Paradise
ひまわりの約束
Creep
Hyouriittai
Binibini
60
67
67
You Were Supposed
You Were
to BeSupposed
Different to Be Different
45
209 Boyce Avenue Cover Sessions,Thinking
Vol. 3 out Loud
56
278640
FALSE
210 Jonah Baker
Perfect / Style
37
212864
FALSE
211 The Civil Wars Barton Hollow Poison & Wine
Covers
54
219466
FALSE
212 Howie Day
66
249120
FALSE
63
148400
FALSE
214 Zack Tabudlo;Billkin
Give Me Your Forever
Give Me Your Forever (ft. Billkin)
58
244800
FALSE
215 Landon Pigg
Coffee Shop
216 Anna Nalick
Wreck of the Day
Breathe (2 AM)
Stop All The World
Collide
Now
213 Ingrid Michaelson
Be OK
270840
FALSE
65
279826
FALSE
Habang Buhay
69
244067
FALSE
Beautiful Soul Beautiful Soul
44
214738
FALSE
217 Zack Tabudlo Episode
218 Jonah Baker
You And I
Falling in Love at a Coffee Shop
55
219 Ben Woodward Bulletproof
Bulletproof
39
207677
FALSE
220 Andrew Belle
Nightshade
Spectrum
54
265506
FALSE
221 Jonah Baker
Girls Like You (Acoustic
Girls LikeVersion)
You – Acoustic Version
44
188494
FALSE
222 Zack Tabudlo Nangangamba Nangangamba
70
210354
FALSE
223 Us The Duo
64
200706
FALSE
224 Andrew Foy;Renee
Heartbreak
Foy
Anniversary
Heartbreak Anniversary
40
199256
FALSE
225 Tyler Ward;Karis;Ray
One More
Lorraine
TimeOne
Around
More Time Around
47
205666
FALSE
226 A Great Big World
流星花園音樂專輯
Say Something
40
229573
FALSE
55
240952
FALSE
228 Donovan Woods;Tenille
The Other
Townes
Way I Ain’t Ever Loved No One – Acoustic
57
199594
FALSE
229 Ray LaMontagne
Till The Sun Turns
Empty
Black
317280
FALSE
Better TogetherBetter Together
227 Zack Tabudlo Episode
Heart Can’t Lose
48
230 Megan Davies See You Again, See
LoveYou
Me Again,
Like You
Love
Do,Me
Sugar
Like
54(Acoustic
You Do, 231965
Sugar
Mashup)
– Acoustic
FALSE
Mashup
231 Tim Halperin
Covers
The Reason
53
200800
FALSE
232 Canyon City
Refuge
Fix You
60
261665
FALSE
233 JJ Heller
Hand to Hold
Hand to Hold
54
231605
FALSE
Hold You in My Arms
62
306200
FALSE
51
224847
FALSE
236 Boyce Avenue;Megan
Cover Sessions,
Nicole Heaven
Vol. 2
61
250063
FALSE
237 Joshua Hyslop In Deepest BlueThe
(Bonus
Spark
Track
– Bonus
Version)
Track
51
201933
FALSE
238 Drew Holcomb &
Medicine
The NeighborsAmerican Beauty
63
158013
FALSE
239 Ray LaMontagne
Part Of The Light
Such A Simple Thing
65
296386
FALSE
240 Amos Lee
64
160453
FALSE
57
182442
FALSE
More Than Friends (feat. Meghan
54
Trainor)
181360
FALSE
234 Ray LaMontagne
Trouble
235 Us The Duo
Public Record One Last Dance
Amos Lee
Colors
241 Boyce Avenue Cover Sessions,Someone
Vol. 6 You Loved
242 Jason Mraz;Meghan
Know.Trainor
243 Days N Daze
37
169318
TRUE
244 Sara Bareilles The Blessed Unrest
I Choose You
Show Me the Blueprints.
Flurry Rush
63
218573
FALSE
245 Mindy Gledhill Anchor
I Do Adore
53
149160
FALSE
246 Dave Barnes
Christmas Faves
I’ll2022
Be Home For Christmas
0
183293
FALSE
247 Get Dead
Tall Cans & Loose
Fuck
Ends
You
36
169266
TRUE
248 Albert King
pov: you have aChristmas
holly jolly christmas
Comes But Once A0 Year
272640
FALSE
249 Albert King
pov: you rock around
Christmas
the christmas
Comes But
tree
Once A0 Year
272640
FALSE
250 John Adams
If I Ain’t Got YouIf(Acoustic)
I Ain’t Got You – Acoustic 55
176509
FALSE
251 John Adams
Believe (Acoustic)
Believe – Acoustic
57
179886
FALSE
252 Adam Christopher
Iris (Acoustic) Iris – Acoustic
54
184200
FALSE
253 Motohiro Hata 言ノ葉
44
447306
FALSE
Rain – Long Ver.
254 Aoi Teshima
Cheek to Cheek~I
C’est
Love
si bon
Cinemas~
51
108346
FALSE
255 Jonah Baker
Baby (Acoustic Version)
Baby (Acoustic Version)
42
160768
FALSE
256 YUZU
Land
47
304320
FALSE
257 Boyce Avenue;Emma
I Like Me
Heesters
BetterI Like Me Better
54
201508
FALSE
258 Zack Tabudlo Asan Ka Na Ba Asan Ka Na Ba
73
241132
FALSE
259 Boyce Avenue Cover Sessions,AVol.
Thousand
3
Years
56
263710
FALSE
260 Thomas Daniel drivers license drivers license
56
246345
FALSE
261 Jason Mraz
YES!
59
257173
FALSE
262 Jae Hall
The Winner Takes
TheItWinner
All (Acoustic)
Takes It All – Acoustic
57
159012
FALSE
Reason
Love Someone
263 Aaron Espe
Only Time
56
178546
FALSE
264 A Fine Frenzy One Cell In TheAlmost
Sea Lover
57
268800
FALSE
265 Roses & Frey Dance Monkey Dance Monkey
51
197850
FALSE
266 Parachute
Parachute
48
222400
FALSE
267 Kina Grannis
Dream a Little Dream
Dreamofa Me
Little Dream of Me 52
142379
FALSE
268 The Mayries
Back For Good Back For Good
54
194667
FALSE
269 Canyon City
OK
55
212400
FALSE
270 Andrew Foy;Renee
JustFoy
The Two OfJust
Us The Two Of Us
41
196304
FALSE
271 Boyce Avenue Cover Sessions,Hey
Vol.There
6
Delilah
49
230868
FALSE
272 Andrew Foy;Renee
Arcade
Foy
Arcade
37
186738
FALSE
273 Kina Grannis
Yellow
52
193536
FALSE
Wake Me Up
58
196819
FALSE
275 Aidan Hawken Walking Blind (feat.
Walking
Carina
Blind
Round)
48
201440
FALSE
276 Jon Bryant
Headphones
56
204998
FALSE
277 The Rescues
Teenage DreamTeenage Dream
46
219093
FALSE
55
171800
FALSE
279 Kina Grannis
Can’t Help Falling
Can’t
In Love
Help (Piano
FallingVersion)
In Love – Piano
54
Version
211624
FALSE
280 Austin Plaine
Austin Plaine
Yellow
274 Roses & Frey Wake Me Up
Only Time
Ocean
OK
Headphones
278 Ivan & Alyosha The Worth Of The
TheWait
Worth Of The Wait
Never Come Back Again
57
196240
FALSE
49
199459
FALSE
Someone You Loved
Someone
(Acoustic)
You Loved – Acoustic
55
281 Chord Overstreet
Love You To Death
Love You To Death
282 Plamina
169253
FALSE
283 Kina Grannis;Imaginary
What a Wonderful
Future What
World
a Wonderful World
51
137066
FALSE
284 Andrew Foy;Renee
You Foy
Broke Me First
You Broke Me First
39
128798
TRUE
285 Joshua Hyslop Echos
Long Way Down
