Mutate

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from setup import ___

from siuba import *
from plotnine import *

from music_top200 import music_top200, track_features

Exercise 0:

Delete the # symbol on the line # music_top200. This symbol is called a comment, and causes everything to the right of it to be ignored.

# I am a helpful note. I am not code!

# music_top200

Exercise 1:

Currently, the duration is calculated in seconds.

• Delete (uncomment) the # symbol in the code.
• Complete the code to convert duration to milliseconds.

hint

Delete the # symbol. This is called a comment. When it is the first non-blank on a line, it stops that line from being run.

1 second is 1000 milliseconds. So you would multiply the duration by 1000.

(music_top200
  # >> mutate(___ = ___)
)

	country	position	track_name	artist	streams	duration	continent
0	Argentina	1	Tusa	KAROL G	1858666	200.960	Americas
1	Argentina	2	Tattoo	Rauw Alejandro	1344382	202.887	Americas
2	Argentina	3	Hola - Remix	Dalex	1330011	249.520	Americas
...	...	...	...	...	...	...	...
12397	South Africa	198	Black And White	Niall Horan	11771	193.090	Africa
12398	South Africa	199	When I See U	Fantasia	11752	217.347	Africa
12399	South Africa	200	Psycho!	MASN	11743	197.217	Africa

12400 rows × 7 columns

(music_top200
  >> mutate(duration_ms = _.duration * 1000)
)

	country	position	track_name	artist	streams	duration	continent	duration_ms
0	Argentina	1	Tusa	KAROL G	1858666	200.960	Americas	200960.0
1	Argentina	2	Tattoo	Rauw Alejandro	1344382	202.887	Americas	202887.0
2	Argentina	3	Hola - Remix	Dalex	1330011	249.520	Americas	249520.0
...	...	...	...	...	...	...	...	...
12397	South Africa	198	Black And White	Niall Horan	11771	193.090	Africa	193090.0
12398	South Africa	199	When I See U	Fantasia	11752	217.347	Africa	217347.0
12399	South Africa	200	Psycho!	MASN	11743	197.217	Africa	197217.0

12400 rows × 8 columns

Exercise 2:

Uncomment the mutate in the pipe below. Can you fix the two errors in it?

It should return data with a new column on the right, that divides position by 200.

(music_top200
  # >> mutate(new position = position / 200)
)

	country	position	track_name	artist	streams	duration	continent
0	Argentina	1	Tusa	KAROL G	1858666	200.960	Americas
1	Argentina	2	Tattoo	Rauw Alejandro	1344382	202.887	Americas
2	Argentina	3	Hola - Remix	Dalex	1330011	249.520	Americas
...	...	...	...	...	...	...	...
12397	South Africa	198	Black And White	Niall Horan	11771	193.090	Africa
12398	South Africa	199	When I See U	Fantasia	11752	217.347	Africa
12399	South Africa	200	Psycho!	MASN	11743	197.217	Africa

12400 rows × 7 columns

Show solution

(music_top200
  >> mutate(new_position = _.position / 200)
)

	country	position	track_name	artist	streams	duration	continent	new_position
0	Argentina	1	Tusa	KAROL G	1858666	200.960	Americas	0.005
1	Argentina	2	Tattoo	Rauw Alejandro	1344382	202.887	Americas	0.010
2	Argentina	3	Hola - Remix	Dalex	1330011	249.520	Americas	0.015
...	...	...	...	...	...	...	...	...
12397	South Africa	198	Black And White	Niall Horan	11771	193.090	Africa	0.990
12398	South Africa	199	When I See U	Fantasia	11752	217.347	Africa	0.995
12399	South Africa	200	Psycho!	MASN	11743	197.217	Africa	1.000

12400 rows × 8 columns

Exercise 3:

The mutate below uses code from a future chapter to calculate how many letters are in each artist’s name.

Which artist with the shortest name has the most streams?

hint

You’ll need to use an arrange in the pipe with 2 arguments.

(music_top200
  >> mutate(artist_length = _.artist.str.len())
)

	country	position	track_name	artist	streams	duration	continent	artist_length
0	Argentina	1	Tusa	KAROL G	1858666	200.960	Americas	7
1	Argentina	2	Tattoo	Rauw Alejandro	1344382	202.887	Americas	14
2	Argentina	3	Hola - Remix	Dalex	1330011	249.520	Americas	5
...	...	...	...	...	...	...	...	...
12397	South Africa	198	Black And White	Niall Horan	11771	193.090	Africa	11
12398	South Africa	199	When I See U	Fantasia	11752	217.347	Africa	8
12399	South Africa	200	Psycho!	MASN	11743	197.217	Africa	4

12400 rows × 8 columns

Show solution

(music_top200
  >> mutate(artist_length = _.artist.str.len())
  >> arrange(_.artist_length, -_.streams)
)

	country	position	track_name	artist	streams	duration	continent	artist_length
5256	Indonesia	57	Sweet Night	V	529806	214.259	Asia	1
9666	Philippines	67	Sweet Night	V	313660	214.259	Asia	1
5880	India	81	Sweet Night	V	230745	214.259	Asia	1
...	...	...	...	...	...	...	...	...
8366	Mexico	167	Escondidos	La Adictiva Banda San José de Mesillas	635158	191.893	Americas	38
11193	El Salvador	194	En Peligro de Extinción	La Adictiva Banda San José de Mesillas	11447	234.198	Americas	38
180	Argentina	181	Un Poco de Amor Francés	Patricio Rey y sus Redonditos de Ricota	178678	206.200	Americas	39

12400 rows × 8 columns

V, for their track in Indonesia

That’s right!

V, for their track in Hong Kong

That’s the right artist, but did you sort by most streams first?

F, for their track in Finland

Incorrect. Did you sort by most streams first?

F, for their track in Hong Kong

Incorrect. Did you sort by most streams first?