album_colours

Color your favorite albums into seaborn or matplotlib.

These palettes are the result of employing KMeans clustering on the color data extracted from the album covers.

The album selection for each artist was influenced by the colors of their cover, instead of their quality or representativeness.

Other albums are free to join this package. Open a PR with the album cover and the name of the artist and album.

Inspiration:

https://github.com/karthik/wesanderson

https://github.com/jbgb13/peRReo

Installation

$ pip install album_colours

Usage

Use this way into your notebook or script:

from album_colours import palette_generator

palette = palette_generator.color_gradient_generator('<palette>', 2)

We currently support the following albums:

devendra Flying Wig - Devendra Banhart
alvaro_diaz Felicilandia - Álvaro Díaz
alvaro_diaz2 Single Llori Pari - Álvaro Díaz
aventura The Last - Aventura
bad_bunny Un verano sin ti - Bad Bunny
frank_ocean Blonde - Frank Ocean
kanye The life of pablo - Kanye West
kendrick DAMN - Kendrick Lamar
kendrick2 good kid, m.A.A.d city - Kendrick Lamar
kendrick3 Mr. Morale & the Big Steppers - Kendrick Lamar
radiohead Kid A - Radiohead
rosalia El Mal Querer - Rosalía
rosalia2 Motomami - Rosalía
sen_senra Sensaciones - Sen Senra
soda_stereo Nada Personal - Soda Stereo
tyler Flower Boy - Tyler, the Creator

Please see the example notebook.

Palettes

Some of the palettes look like this:

bad_bunny Un verano sin ti - Bad Bunny

rosalia2 Motomami - Rosalía

alvaro_diaz Felicilandia - Álvaro Díaz

kanye The life of pablo - Kanye West

kendrick3 Mr. Morale & the Big Steppers - Kendrick Lamar

radiohead Kid A - Radiohead

Palette creations

The library at its core has the principal colors as a list of hex values. Use the palette_generator.color_gradient_generator() function to build and view your palettes.

Parameters

palette - The name of the palette you want to generate. See the list of available above. If the palette is not found, it will return an empty list.
color_count - The number of colors you want to generate. Default is the length of elements in the list.
palette_type - The type of palette you want to generate. Options are discrete and continuous. Default is discrete.

Its also recommended if you want to have the colors but in different order to use sample() from random package. As it is shown in the examples_plots.ipynb notebook.

Discrete palettes

palette_generator.color_gradient_generator('bad_bunny')

palette_generator.color_gradient_generator('rosalia', 4)

Continuous palettes

palette_generator.color_gradient_generator('bad_bunny', 20)

palette_generator.color_gradient_generator('rosalia', 20)

Plot examples

The library returns a list of colors that can be used in seaborn or matplotlib plots. Read more about it here: https://seaborn.pydata.org/tutorial/color_palettes.html

All examples are in the example notebook.

# all imports ...
bad_bunny = palette_generator.color_gradient_generator('bad_bunny', 9)

sns.set_palette(bad_bunny)
sns.scatterplot(x="total_bill", y="tip", hue="sex", size="size", sizes=(50, 200), data=tips)

p = palette_generator.color_gradient_generator('aventura', 9)
p_random = random.sample(p, 2)

sns.set_palette(p_random)
sns.relplot(
    data=fmri, kind="line",
    x="timepoint", y="signal", col="region",
    palette=p_random,
    hue="event", style="event",
)

p = palette_generator.color_gradient_generator('tyler', 9)
p_random = random.sample(p, 2)

sns.set_palette(p_random)
sns.catplot(data=tips, kind="violin", x="day", y="total_bill", hue="smoker", split=True)

p = palette_generator.color_gradient_generator('alvaro_diaz', 9)
p_random = random.sample(p, 3)

penguins = sns.load_dataset("penguins")
sns.set_palette(p_random)
sns.jointplot(data=penguins, x="flipper_length_mm", y="bill_length_mm", hue="species")

License

album-colours was created by Majo Castañeda, Dante Bazaldua. It is licensed under the terms of the MIT license.

Contact

For any comments or suggestions, feel free to reach me at dalnte@me.com or @MajoSedCast

danteese/album-colours