ⴰⵙⴻⴽⵛⴻⵎ ⵏ ⵢⵉⵙⴻⴼⴽⴰ ⴷⴻⴳ Pitun ⵙ Seaborn

ⵉⵎⵉⵔⴰ, ⴰⵢⴻⵏ ⵢⴻⵙⵄⴰⵏ ⴰⵣⴰⵍ ⴰⴽⴽ ⴷⴻⴳ ⵓⵎⴰⴹⴰⵍ ⵓⵔ ⵢⴻⵍⵍⵉ ⴰⵔⴰ ⴷ lpitrul, ⵡⴰⵏⴰⴳ ⴷ ⵉⵙⴻⴼⴽⴰ. ⵜⴰⵎⵓⵖⵍⵉ ⵍⴰ ⵜⴻⵜⵜⵓⵖⴰⵍ ⴷ ⴰⵍⵍⴰⵍ ⵢⴻⵙⵄⴰⵏ ⴰⵣⴰⵍ ⵓⴳⴰⵔ ⵉ ⵓⵙⵏⴻⵔⵏⵉ ⵏ ⵍⵎⴻⵄⵏⴰ ⵏ ⵢⵉⵎⴻⵍⵢⴰⵔⴻⵏ ⵏ ⵢⵉⴹⵔⵉⵙⴻⵏ ⵏ ⵢⵉⵙⴻⴼⴽⴰ. ⵙ ⵓⵙⵓⵇⴻⵍ ⵏ ⵢⵉⵙⴻⴼⴽⴰ ⵙ ⵜⵎⵓⵖⵍⵉ ⵏ ⵜⴼⴻⵍⵡⵉⵜ ⵙ ⵜⵖⴰⵡⵍⴰ, ⴰⵙⴻⴽⵛⴻⵎ ⵏ ⵢⵉⵙⴻⴼⴽⴰ ⵢⴻⵜⵜⵄⴰⵡⴰⵏ ⴷⴻⴳ ⵓⵃⵔⵉⵛ ⵏ ⵜⵎⴰⵛⴰⵀⵓⵜ ⵏ ⵢⵉⵙⴻⴼⴽⴰ ⵙ ⵓⵙⵎⴻⴽⵜⵉ ⵏ ⵢⵉⵙⴰⵍⵍⴻⵏ, ⵏ ⵜⵎⵓⵖⵍⵉⵡⵉⵏ, ⴷ ⵢⵉⴼⴻⵔⴷⵉⵙⴻⵏ ⵏ ⵜⴼⴻⵍⵡⵉⵜ ⵉⵛⵓⴷⴷⴻⵏ ⵖⴻⵔ ⵡⴰⵢⴰ. ⵎⴰⵛⴰ, ⵉⵙⴻⴼⴽⴰ ⴷ ⵜⴼⴻⵍⵡⵉⵢⵉⵏ ⵢⴻⵙⵙⴻⴼⴽ ⴰⴷ ⵎⵙⴻⴼⵀⴰⵎⴻⵏ : D ⵜⴰⵥⵓⵔⵉ ⵏ ⵓⵙⴷⵓⴽⴽⴻⵍ ⵏ ⵓⵙⵏⴻⴼⵍⵉ ⴰⵎⴻⵇⵇⵔⴰⵏ ⴷ ⵜⵎⴰⵛⴰⵀⵓⵜ ⵜⴰⵎⴻⵇⵇⵔⴰⵏⵜ. ⴷⴻⴳ ⵓⴹⵔⵉⵙⴰⴳⵉ ⵏ ⵓⴱⵍⵓⴳ, ⴰⴷ ⴰⴽⴷ-ⵏⴻⵙⵙⴽⴻⵏ "Sea Born", ⵢⵉⵡⴻⵏ ⵙⴻⴳ ⵡⴰⵍⵍⴰⵍⴻⵏ ⵏ ⵜⵎⵓⵖⵍⵉ ⵢⴻⵜⵜⵡⴰⵙⵙⵏⴻⵏ ⴰⵟⴰⵙ ⵢⴻⵜⵜⵡⴰⵔⵓⵏ ⵙ Python.

ⴰⵍⵍⴰⵍⴻⵏ ⵏ ⵓⵙⴻⴽⵍⴻⵙ

ⵏⴻⵙⵙⴻⵇⴷⴰⵛ ⴰⵍⵍⴰⵍⴻⵏ ⵏ Visualization ⴰⴽⴽⴻⵏ ⴰⴷ ⵏⴻⵙⵙⴻⵎⵔⴻⵙ ⵜⵉⴳⵏⴰⵜⵉⵏ, ⵍⵎⵓⴷⴻⵍ, ⵉⴼⴻⵔⴷⵉⵙⴻⵏ ⵏ ⵜⴼⴻⵍⵡⵉⵜ ⴷ ⵡⴰⵙⵙⴰⵖ ⴳⴰⵔ ⵢⵉⵎⴻⴹⵇⴰⵏ. ⴷ ⵜⴰⵎⵓⵙⵏⵉ ⵢⴻⵜⵜⵡⴰⵙⵙⵓⵜⵓⵔⴻⵏ ⴰⵟⴰⵙ ⵍⴰⴷⵖⴰ ⵉ ⵜⵎⴻⴷⴷⵓⵔⵜ ⵏ ⵜⵓⵙⵙⵏⴰ ⵏ ⵢⵉⵙⴻⴼⴽⴰ.

ⵉⵍⵓⵍⴻⵏ ⴷⴻⴳ ⵢⵉⵍⴻⵍ

Seaborn ⴷ ⵜⴰⵎⴽⴻⵔⴹⵉⵜ ⵏ ⵓⵙⴻⴽⵍⴻⵙ ⵏ ⵢⵉⵙⴻⴼⴽⴰ ⵏ Pitun ⵢⴻⴱⵏⴰⵏ ⵖⴻⴼ matplotlib. ⵢⴻⴼⴽⴰⴷ ⵜⴰⵖⴻⵛⵜ ⵏ ⵓⵙⵡⵉⵔ ⵏ ⵜⵖⵓⵔⵉ ⵏ ⵜⴼⴻⵍⵡⵉⵢⵉⵏ ⵏ ⵜⴻⵙⵏⴰⵜⵡⵉⵍⵜ ⵉⵊⴻⴱⴷⴻⵏ ⵢⴻⵔⵏⴰ ⵜⵜⴰⴽⴻⵏⵜⴷ ⵉⵙⴰⵍⴰⵏ.

ⵜⵉⵖⴱⵓⵍⴰ ⵏ ⵓⵙⵏⵓⵍⴼⵓ ⵏ Seaborn:

ⴷⴻⴳ seaborn, ⵏⴻⵙⵄⴰ 3 ⵏ ⵜⴰⴳⴳⴰⵢⵉⵏ ⵏ ⵜⵃⵓⵏⴰ

ⵜⵉⴼⴻⵍⵡⵉⵢⵉⵏ ⵏ ⵓⵙⵡⵉⵔ.
ⵜⵉⴼⴻⵍⵡⵉⵢⵉⵏ ⵏ ⵓⵙⴼⴻⵔⵔⴻⵇ.
ⵜⵉⴼⴻⵍⵡⵉⵢⵉⵏ ⵏ ⵡⴰⵙⵙⴰⵖ.

ⵜⵉⴼⴻⵍⵡⵉⵢⵉⵏ ⵏ ⵜⴰⴳⴳⴰⵢⵜ

ⵏⴻⵙⵙⴻⵇⴷⴰⵛ ⵜⵉⵣⴻⵎⵎⴰⵔ ⵏ ⵜⴼⴻⵍⵡⵉⵜ ⵏ ⵜⴼⴻⵍⵡⵉⵜ ⵏ seaborn ⴰⴽⴽⴻⵏ ⴰⴷ ⵏⵡⴰⵍⵉ ⵜⵉⴳⵏⴰⵜⵉⵏ ⵏ ⵓⵎⴳⵉⵔⴻⴷ ⵏ ⵜⴼⴻⵍⵡⵉⵜ ⵏⴻⵖ ⴰⴽⴽⴻⵏ ⴰⴷ ⵏⵡⴰⵍⵉ ⴰⵙⵙⴰⵖ ⵢⴻⵍⵍⴰⵏ ⴳⴰⵔ ⵙⵉⵏ ⵏ ⵢⵉⵎⴻⴹⵇⴰⵏ ⵙ ⵢⵉⵡⴻⵏ ⵏ ⵓⵎⴳⵉⵔⴻⴷ ⵏ ⵜⴼⴻⵍⵡⵉⵜ ⵎⴰ ⵓⵍⴰⵛ.

ⴰⵃⴻⵙⵙ ⵏ ⵜⴼⴻⵍⵡⵉⵜ:

ⵢⴻⵜⵜⴱⴻⴳⴳⵉⵏⴷ ⵍⵃⵉⵙⴰⴱ ⵏ ⵜⵎⵓⵖⵍⵉⵡⵉⵏ ⵏ ⵢⴰⵍ ⵜⴰⴳⴳⴰⵢⵜ ⵙⴻⴳ ⵓⵎⴳⵉⵔⴻⴷ ⵏ ⵜⴰⴳⴳⴰⵢⵜ. ⵏⴻⵃⵙⴻⴱ ⴽⴰⵏ ⴰⵎⴹⴰⵏ ⵏ ⵉⵃⴻⵣⵣⵉⴱⴻⵏ ⵏ ⵢⴰⵍ ⵜⴰⴳⴳⴰⵢⵜ ⵏ ⵓⵎⴳⵉⵔⴻⴷ

seaborn.catplot(kind = 'count',
                data = dataset,
                x    = 'variable')

ⴰⵃⵔⵉⵛ ⵏ ⵍⴱⴰⵔ:

ⵢⴻⵜⵜⴳⴻⵏⵙⵉⵙⴷ ⴰⵇⵉⴹⵓⵏ ⵏ ⵜⵎⵓⵖⵍⵉ ⵏ ⵓⵎⴳⵉⵔⴻⴷ ⵉⴽⴻⵎⵍⴻⵏ ⵙ ⵜⵖⴻⵔⵖⴻⵔⵜ ⵏ ⵜⵎⴻⵥⵥⵓⵖⵜ ⵉ ⵢⴰⵍ ⵜⴰⴳⴳⴰⵢⵜ ⵏ ⵓⵎⴳⵉⵔⴻⴷ ⵏ ⵜⵎⴻⵥⵥⵓⵖⵜ. ⵉⵀⵉ ⵜⴰⵖⵓⵍⵜ ⵏ ⵓⵙⵏⵓⵍⴼⵓ ⵜⴻⵟⵟⴻⴼ ⵙⵉⵏ ⵏ ⵢⵉⵎⴻⴹⵇⴰⵏ ⴷ ⴰⵙⴻⴽⵛⴻⵎ, ⵢⵉⵡⴻⵏ ⴷ ⴰⴽⴻⵎⵎⴻⵍ ⵡⴰⵢⴻⴹ ⴷ ⴰⴼⴻⵔⴷⵉⵙ. ⵉ ⵢⴰⵍ ⵜⴰⴳⴳⴰⵢⵜ ⵙⴻⴳ ⵓⵎⴳⵉⵔⴻⴷ_1, ⴰⴷ ⵏⴻⵃⵙⴻⴱ ⵜⴻⵏⴷⴻⵏⵛⴻ ⵏ ⵓⵎⴳⵉⵔⴻⴷ_2.
ⵜⴻⵏⴷⴻⵏⵛⵢ ⵢⴻⵣⵎⴻⵔ ⴰⴷ ⵢⵉⵍⵉ ⴷ ⵍⵎⵉⵣⴰⵏ, ⴷ ⴰⵎⴳⵉⵔⴻⴷ, ⵏⴻⵖ ⵜⵣⴻⵎⵔⴻⴹ ⴰⴷ ⵜⴻⵙⵄⴻⴷⴷⵉⴹ ⴽⵔⴰ ⵏ ⵜⵖⴰⵡⵙⴰ ⵏ ⵓⵙⵎⴻⵍ...

seaborn.catplot(kind = 'bar',**data = dataset,**
                x    = 'variable_1',**y    = 'variable_2',**
                estimator = np.mean)**

ⴰⵃⵔⵉⵛ ⵏ ⵓⵃⵔⵉⵛ:

Strip plot ⴷ ⵢⵉⵡⴻⵏ ⵙⴻⴳ ⵢⵉⴼⴻⵔⴷⵉⵙⴻⵏ ⵉⵙⴻⵀⵍⴻⵏ ⵓ ⵙⵔⵉⴷ ⴷⴻⴳ ⵓⵙⴽⴰⵙⵉ ⵏ ⵢⵉⵙⴻⴼⴽⴰ, ⴰⴷ ⴷⵏⴻⵙⵙⴻⴽⵍⴻⵙ ⴽⴰⵏ ⵜⵉⵏⴻⵇⵇⵉⴹⵉⵏ ⵉ ⴷⵢⴻⵎⵎⴰⵍⴻⵏ ⴰⵣⴰⵍ ⵏ ⵓⵎⴳⵉⵔⴻⴷ ⵢⴻⵜⵜⵡⴰⴽⴻⵎⵍⴻⵏ.I ⵢⴰⵍ ⵜⴰⴳⴳⴰⵢⵜ ⵏ ⵓⵎⴳⵉⵔⴻⴷ 1, ⴰⴷ ⴷⵏⴻⵙⵙⴻⴽⵍⴻⵙ ⴰⵣⴰⵍ ⵏ ⵓⵎⴳⵉⵔⴻⴷ 2.

seaborn.catplot(kind = 'strip',
                data = dataset,
                x    = 'variable_1',
                y    = 'variable_2',
                jitter = 0.15)

ⵜⴰⵃⴻⵎⵍⴰ ⵏ ⵙⵡⴰⵔⵎ:

ⵙⵡⴰⵔⵎ plot ⵢⴻⵜⵜⴻⵎⵛⴰⴱⵉ ⴰⵟⴰⵙ ⵖⴻⵔ strip plot, ⵉⵎⵉ ⵢⴻⵙⵄⴰ ⴰⴽⴽⴻⵏ ⵉⵍⴰⵇ ⵢⵉⵡⴻⵜ ⵏ ⵜⵖⴰⵡⵙⴰ. ⴰⵎⴳⴰⵔⴰⴷ ⴽⴰⵏ ⴷⴻⴳ ⵡⴰⵎⴻⴽ ⵉ ⴷⵢⴻⵙⵙⴽⴻⵏ ⵜⵉⵏⴻⵇⵇⵉⴹⵉⵏ. ⵎⴰ ⵢⴻⵍⵍⴰ ⴷⴻⴳ strip plot, ⵜⵉⵏⴻⵇⵇⵉⴹⵉⵏ ⵏ ⵢⵉⵙⴻⴼⴽⴰ ⵣⴻⵎⵔⴻⵏⵜ ⴰⴷ ⵎⵅⴰⵍⵍⴰⴼⴻⵏⵜ ⵉⵎⵉ ⵜⵜⵡⴰⵙⴻⵔⵙⴻⵏⵜ ⵙ ⵜⵖⴰⵡⵍⴰ ⵖⴻⴼ ⵜⵖⴻⵔⵖⴻⵔⵜ x, ⴷⴻⴳ ⵙⵡⴰⵔⵎ plot ⵏⴻⵜⵜⵃⴻⵇⵔⵉⵇ ⴱⴻⵍⵍⵉ ⵜⵉⵏⴻⵇⵇⵉⴹⵉⵏ ⵓⵔ ⵜⵜⵎⵛⴰⴱⵉⵏⵜ ⴰⵔⴰ ⵙ ⵓⵙⵙⴻⵎⵔⴻⵙⵏⵙⴻⵏⵜ ⵖⴻⴼ ⵡⴰⵢⴻⴹ.
ⴰⵢⴻⵏ ⵉⵅⵓⵙⵙⴻⵏ ⴷⴰⴳⵉ ⴷ ⴰⴽⴽⴻⵏ ⵎⴰ ⵢⴻⵍⵍⴰ ⵏⴻⵙⵄⴰ ⴰⵟⴰⵙ ⵏ ⵜⵏⴻⵇⴹⵉⵏ ⵏ ⵢⵉⵙⴻⴼⴽⴰ, ⴰⴷ ⵢⵉⵍⵉ ⴷ ⴰⵢⴻⵏ ⵓⵔ ⵏⴻⵣⵎⵉⵔ ⴰⵔⴰ ⴰⴷ ⵜⴻⵏⵜⵏⴻⵜⵜⵇⴰⴱⴰⵍ, ⵉⵀⵉ algorithme ⴰⴷ ⵢⴻⴽⴽⴻⵙ ⴽⵔⴰ ⵏ ⵜⵏⴻⵇⴹⵉⵏ ⵏ ⵢⵉⵙⴻⴼⴽⴰ ⴰⴽⴽⴻⵏ ⵓⵔ ⵜⵜⵏⴻⵜⵜⵇⴰⴱⴰⵍ ⴰⵔⴰ.

seaborn.catplot(kind = 'swarm',
                data = dataset,
                x    = 'variable_1',
                y    = 'variable_2')

ⴰⵃⵔⵉⵛ ⵏ ⵜⴼⴻⵍⵡⵉⵜ:

ⵜⴰⴼⴻⵍⵡⵉⵜ ⵏ ⵜⴼⴻⵍⵡⵉⵜ ⵜⴻⵜⵜⵡⴰⵙⴻⵇⴷⴻⵛ ⴰⴽⴽⴻⵏ ⴰⴷ ⴷⵜⴻⵙⵙⴽⴻⵏ ⵜⴰⴼⵔⴻⵇⵜ ⵏ ⵓⵎⴳⵉⵔⴻⴷ ⵢⴻⵜⵜⵡⴰⴽⴻⵎⵍⴻⵏ ⵉ ⵢⴰⵍ ⵜⴰⴳⴳⴰⵢⵜ ⵏ ⵓⵎⴳⵉⵔⴻⴷ ⵏ ⵜⴼⴻⵍⵡⵉⵜ. ⵓⵍⴰ ⵎⴰ ⴷ ⴰⵢⴻⵏ ⵉⵙⴻⵀⵍⴻⵏ ⴰⵟⴰⵙ, ⵢⴻⵜⵜⴰⴽⴷ ⴰⵟⴰⵙ ⵏ ⵢⵉⵙⴰⵍⵍⴻⵏ:
ⴰⵣⴰⵍ ⵏ ⵢⵉⵇⵓⴰⵔⵜⵉⵍⴻⵏ:

ⵜⴰⴼⴻⵍⵡⵉⵜ ⵜⴻⵙⵄⴰ ⵢⵉⵡⴻⵏ ⵏ ⵍⵃⵉⵔⴼⴰ ⵏ ⵜⵍⴻⵎⵎⴰⵙⵜ ⴷⴰⵅⴻⵍ, ⴷ ⵜⵉⵏ ⵉ ⴷⵢⴻⵎⵎⴰⵍⴻⵏ ⵜⴰⵍⴻⵎⵎⴰⵙⵜ. ⵜⴰⴳⵣⵉⵔⵜ ⵏ ⵜⴼⴻⵍⵡⵉⵜ ⵏⵏⵉⴳⵙ ⴷ ⵜⵇⵓⴰⵔⵜⵉⵍⵉⵏ ⵏ ⵓⴼⴻⵍⵍⴰ, ⵜⵉⵏ ⵢⴻⵍⵍⴰⵏ ⴷⴷⴰⵡⴰⵙ ⴷ ⵜⵇⵓⴰⵔⵜⵉⵍⵉⵏ ⵏ ⴷⴷⴰⵡ.

ⵉⴱⴻⵔⴷⴰⵏ:

ⴰⴽⴽⴻⵏ ⴰⴷ ⵜⵡⴰⵍⵉⴹ ⴱⴻⵍⵍⵉ ⵍⵍⴰⵏⵜ ⴽⵔⴰ ⵏ ⵜⵏⴻⵇⴹⵉⵏ ⴱⴻⵔⵔⴰ ⵏ ⵜⴻⵙⴼⵉⴼⵜ, ⵜⵉⵏⴻⵇⵇⵉⴹⵉⵏⴰ ⵜⵜⴳⴻⵏⵙⴻⵏⵜⴷ ⵉⴱⴻⵔⴷⴰⵏ ⵏ ⴱⴻⵔⵔⴰ

seaborn.catplot(kind = 'box',
                data = dataset,
                x    = 'variable_1',
                y    = 'variable_2')

ⴰⵃⵔⵉⵛ ⵏ ⵜⴽⴻⵕⵕⵓⵙⵜ:

ⴷⴻⴳ ⵓⵎⴽⴰⵏ ⵏ ⵓⵙⵏⵓⵍⴼⵓ ⵏ ⵜⴼⴻⵍⵡⵉⵜ ⵏ ⵓⵙⵏⴻⴼⵍⵉ, ⴰⵙⵏⵉⵍⴻⵙ ⵏ ⵜⵎⴻⵥⵥⵓⵖⵜ ⴰⴷ ⴷⵢⴻⵙⵏⵓⵍⴼⵓ ⵜⴰⴼⴻⵍⵡⵉⵜ ⵏ ⵜⵉⴷⴻⵜ ⵏ ⵓⵎⴳⵉⵔⴻⴷ ⵢⴻⵜⵜⵡⴰⴽⴻⵎⵍⴻⵏ ⵉ ⵢⴰⵍ ⵜⴰⴳⴳⴰⵢⵜ ⵏ ⵓⵎⴳⵉⵔⴻⴷ ⵏ ⵜⴼⴻⵔⴽⵉⵜ ⵙ ⵓⵙⴻⵇⴷⴻⵛ ⵏ KDE ( Kernel Density Estimation ).

seaborn.catplot(kind = 'violin',
                data = dataset,
                x    = 'variable_1',
                y    = 'variable_2')

ⵉⵃⵔⵉⵛⴻⵏ ⵏ ⵜⴼⴻⵔⵇⴻⵜ:

ⵏⴻⵙⵙⴻⵇⴷⴰⵛ ⵜⵉⵣⴻⵎⵎⴰⵔ ⵏ ⵓⵙⵏⴻⴼⵍⵉ ⵏ ⵜⴼⴻⵔⴽⵉⵜ ⵏ seaborn ⴰⴽⴽⴻⵏ ⴰⴷ ⵏⵡⴰⵍⵉ ⵜⴰⴼⵔⴻⵇⵜ ⵏ ⵢⵉⵎⴻⴹⵇⴰⵏ ⵉⴽⴻⵎⵍⴻⵏ.

ⴰⵃⵔⵉⵛ ⵏ ⵓⵎⴻⵣⵔⵓⵢ:

ⵜⴰⴼⴻⵍⵡⵉⵜ ⵏ ⵀⵉⵙⵜ ⵜⴻⵜⵜⴳⴻⵏⵙⵉⵙⴷ ⵜⴰⴼⵔⴻⵇⵜ ⵏ ⵢⵉⵎⴻⴹⵇⴰⵏ ⵉⴽⴻⵎⵍⴻⵏ ⵙ ⵓⵙⴻⵇⴷⴻⵛ ⵏ ⵢⵉⴱⵉⵏ.

seaborn.distplot(kind = 'hist',
                 data = dataset,
                 x    = 'variable',
                 bins = 20)

ⴰⴹⵔⵉⵙ ⵏ KDE:

ⴽⴷⴻ plot ⵢⴻⵜⵜⴳⴻⵏⵙⵉⵙⴷ ⵜⴰⴼⵔⴻⵇⵜ ⵏ ⵜⵉⴷⴻⵜ ⵏ ⵢⵉⵙⴻⴼⴽⴰ, ⵙ ⵓⵙⴻⵇⴷⴻⵛ ⵏ ⵓⵇⵉⴹⵓⵏ ⵏ ⵜⵖⴻⵔⵖⴻⵔⵜ ⵏ ⴽⴻⵔⵏⴻⵍ.

seaborn.distplot(kind = 'kde',
                 data = dataset,
                 x    = 'variable')

ⵢⴻⵣⵎⴻⵔ ⴷⴰⵖⴻⵏ ⴰⴷ ⵢⴻⵜⵜⵡⴰⵙⴻⵇⴷⴻⵛ ⵉ ⵓⵙⴻⵎⵔⴻⵙ ⵏ ⵜⴼⴻⵔⴽⵉⵜ ⵏ ⵙⵉⵏ ⵏ ⵢⵉⵎⵓⴹⴰⵏ ⵉⴽⴻⵎⵍⴻⵏ.

seaborn.distplot(kind = 'kde',
                 data = dataset,
                 x    = 'variable_1',
                 y    = 'variable_2')

ⴰⵃⵔⵉⵛ ⵏ ECDF:

ECDF plot ⵢⴻⵜⵜⴳⴻⵏⵙⵉⵙⴷ ⵜⴰⴼⵔⴻⵇⵜ ⵏ ⵜⵎⴻⵔⵏⴰ ⵏ ⵜⴳⴻⵔⵎⴰⵏⵜ ⵏ ⵢⵉⵡⴻⵏ ⵏ ⵓⵎⴳⵉⵔⴻⴷ ⵢⴻⵜⵜⵡⴰⴽⴻⵎⵍⴻⵏ.

seaborn.distplot(kind = 'ecdf',
                 data = dataset,
                 x    = 'variable')

ⵉⴹⵔⵉⵙⴻⵏ ⵏ ⵡⴰⵙⵙⴰⵖ:

ⵏⴻⵙⵙⴻⵇⴷⴰⵛ ⵜⵉⵣⴻⵎⵎⴰⵔ ⵏ ⵓⵙⵏⵓⵍⴼⵓ ⵏ ⵡⴰⵙⵙⴰⵖⴻⵏ ⵏ seaborn ⴰⴽⴽⴻⵏ ⴰⴷ ⵏⵡⴰⵍⵉ ⴰⵙⵙⴰⵖ ⴳⴰⵔ ⵢⵉⵎⴻⴹⵇⴰⵏ ⵉⴽⴻⵎⵍⴻⵏ.

ⴰⵃⵔⵉⵛ ⵏ ⵓⵙⴼⴻⵔⵔⴻⵇ:

ⵢⴻⵜⵜⴱⴻⴳⴳⵉⵏⴷ ⴰⵙⵙⴰⵖ ⴳⴰⵔ ⵙⵉⵏ ⵏ ⵢⵉⵎⴻⴹⵇⴰⵏ ⵉⴽⴻⵎⵍⴻⵏ, ⵙ ⵓⵙⵏⵓⵍⴼⵓ ⴽⴰⵏ ⵏ ⵡⴰⴽⴽ ⵜⵉⵏⴻⵇⵇⵉⴹⵉⵏ ⵏ ⵢⵉⵙⴻⴼⴽⴰ.

seaborn.relplot(kind = 'scatter',
                data = dataset,
                x    = 'variable_1',
                y    = 'variable_2')

ⴰⴹⵔⵉⵙ ⵏ ⵓⵣⴻⴳⵣⴰⵡ:

ⵢⴻⵜⵜⴳⴻⵏⵙⵉⵙⴷ ⴰⵙⵙⴰⵖ ⴳⴰⵔ ⵢⵉⵎⴻⴹⵇⴰⵏ ⴰⵎ ⵜⵎⴻⵥⵍⴰ ⵏ ⵜⴽⴻⵎⵎⴻⵍⵜ.

seaborn.relplot(kind = 'line',
                data = dataset,
                x    = 'variable_1',
                y    = 'variable_2')

ⵓⴳⴰⵔ ⵏ ⵜⴻⵖⴱⵓⵍⴰ:

ⴰⵀⴰⵜ ⵜⵡⴰⵍⴰⴹ ⴱⴻⵍⵍⵉ ⴷⴻⴳ ⵡⴰⴽⴽ ⵜⵉⵖⴱⵓⵍⴰ ⵏ ⵓⵙⵏⵓⵍⴼⵓ ⵏⴻⵙⵙⴻⵅⴷⴰⵎ ⴰⵣⴰⵍ ⵏ ⵙⵉⵏ ⵏ ⵢⵉⵎⵓⴹⴰⵏ ⴷⴻⴳ ⵢⴰⵍ ⴰⴹⵔⵉⵙ, ⵎⴰⵛⴰ ⴷ ⴰⵛⵓ ⴰⵔⴰ ⴷⵏⵉⵏⵉ ⵎⴰ ⵏⴻⴱⵖⴰ ⴰⴷ ⴷⵏⴻⵙⵙⴻⴽⵛⴻⵎ ⵓⴳⴰⵔ ⵏ ⵢⵉⵎⵓⴹⴰⵏ ⴷⴻⴳ ⵓⵙⵏⵓⵍⴼⵓⵏⵏⴻⵖ ? ⵙ ⵍⴼⴻⵔⵃ, Seaborn ⵢⴻⵟⵟⴻⴼ ⴷⴻⴳ ⵡⴰⵢⴰ:

ⵜⵉⵏⵉ:

ⵙ ⵓⵙⴻⵇⴷⴻⵛ ⵏ ⵀⵓⴻ ⵏⴻⵣⵎⴻⵔ ⴰⴷ ⴷⵏⴻⵙⵙⴻⴽⵛⴻⵎ ⴰⵎⴳⵉⵔⴻⴷ ⵡⵉⵙ 3 ⵢⴻⵍⵍⴰⵏ ⴷ ⴰⴼⴻⵔⴷⵉⵙ ⵏ ⵜⵎⵓⵖⵍⵉⵏⵏⴻⵖ ⵙ ⵓⵙⴻⵇⴷⴻⵛ ⵏ ⵓⵙⵏⵓⵍⴼⵓ ⵏ ⵢⵉⵏⵉ, ⴰⵏⴰⵎⴻⴽⵉⵙ ⴷ ⴰⴽⴽⴻⵏ ⵜⵉⵏⴻⵇⵇⵉⴹⵉⵏ ⵏ ⵢⵉⵙⴻⴼⴽⴰ ⵢⴻⵍⵍⴰⵏ ⴷⴻⴳ ⵢⵉⵡⴻⵜ ⵏ ⵜⴰⴳⴳⴰⵢⵜ ⵏ ⵓⵎⴳⵉⵔⴻⴷ ⵡⵉⵙ 3agi ⴰⴷ ⵙⵄⵓⵏⵜ ⵢⵉⵡⴻⵏ ⵏ ⵢⵉⵏⵉ.

seaborn.relplot(kind = 'scatter',
                data = dataset,
                x    = 'variable_1',
                y    = 'variable_2',
                hue  = 'variable_3')

ⴰⵛⵃⴰⵍ ⴰⵢ ⵜⴻⵜⵜⵍⵓⵙⵓⴹ:

ⵜⴰⴳⵎⵓⴹⵜ (ⵙⵉⵣⴻ) ⵜⵛⵓⴷⴷ ⵖⴻⵔ ⵀⵓⴻ, ⵎⴰⵛⴰ ⵜⴻⵙⵙⴻⵇⴷⴰⵛ ⴰⵙⴻⴽⵛⴻⵎ ⵏ ⵜⵖⴻⵔⵖⴻⵔⵜ ⴷⴻⴳ ⵓⵎⴹⵉⵇ ⵏ ⵓⵙⴻⴽⵛⴻⵎ ⵏ ⵛⵛⴱⴰⵃⴰ. ⴰⵏⴰⵎⴻⴽⵉⵙ ⴷ ⴰⴽⴽⴻⵏ ⵜⵉⵏⴻⵇⵇⵉⴹⵉⵏ ⵏ ⵢⵉⵙⴻⴼⴽⴰ ⵢⴻⵍⵍⴰⵏ ⴷⴻⴳ ⵢⵉⵡⴻⵜ ⵏ ⵜⵎⴻⵣⴳⵓⵏⵜ ⵏ ⵓⵎⴳⵉⵔⴻⴷ ⵡⵉⵙ 3 ⴰⴷ ⵙⵄⵓⵏⵜ ⵢⵉⵡⴻⵏ ⵏ ⵍⵇⵉⴷⴰⵔ ⵓⵏⵏⵉⴳ. ⵉⵎⴳⴰⵔⴰⴷⴻⵏ ⵉⵎⴻⵥⵍⴰ ⴰⵏⴰⵎⴻⴽⵏⵙⴻⵏ ⴷ ⵜⵉⴳⵏⴰⵜⵉⵏ ⵢⴻⵎⴳⴰⵔⴰⴷⴻⵏ.

seaborn.relplot(kind = 'scatter',
                data = dataset,
                x    = 'variable_1',
                y    = 'variable_2',
                size = 'variable_3',
                sizes = [50, 100])

ⴰⵖⴰⵏⵉⴱ:

ⵇⵔⵉⴱ ⴰⵎ ⵀⵓⴻ ⴷ ⵙⵉⵣⴻ, ⴰⵏⴰⵎⴻⴽⵉⵙ ⴷ ⴰⴽⴽⴻⵏ ⵜⵉⵏⴻⵇⵇⵉⴹⵉⵏ ⵏ ⵢⵉⵙⴻⴼⴽⴰ ⵢⴻⵍⵍⴰⵏ ⴷⴻⴳ ⵢⵉⵡⴻⵜ ⵏ ⵜⴰⴳⴳⴰⵢⵜ ⵏ ⵓⵎⴳⵉⵔⴻⴷ ⵡⵉⵙ 3 ⴰⴷ ⵙⵄⵓⵏⵜ ⵢⵉⵡⴻⵏ ⵏ ⵓⵙⵡⵉⵔ ⵓⵏⵏⵉⴳ. ⵜⴰⵙⵏⵉⵍⴻⵙⵜ ⵏ ⵜⵏⴻⵇⴹⵉⵏ ⵜⴻⵣⵎⴻⵔ ⴰⴷ ⵜⵉⵍⵉ ⴷ ⵜⵏⴻⵇⴹⴻⵜ, ⴷ ⵉⵜⵔⵉ, ⴷ ⴰⵄⴻⴽⴽⴰⵣ, ⴷ ⵜⵔⵉⴰⵏⴳⵍⴻ, ... ⵏⴻⵙⵙⴰⵡⴰⵍⴰⵙⴻⵏ ⴷ ⵉⵎⴻⵙⵍⴰⵢⴻⵏ.

seaborn.relplot(kind = 'scatter',
                data = dataset,
                x    = 'variable_1',
                y    = 'variable_2',
                style = 'variable_3',
                markers = ['X', '*'])

ⵏⴻⵣⵎⴻⵔ ⴷⴰⵖⴻⵏ ⴰⴷ ⴷⵏⴻⵙⵙⴻⴽⵛⴻⵎ ⴰⵎⴳⵉⵔⴻⴷ ⴰⵎⴰⵢⵏⵓⵜ ⵏ ⵜⵎⴻⵥⵔⵉ ⵙ ⵓⵙⴻⵇⴷⴻⵛ ⵏ ⵜⴼⴻⵍⵡⵉⵢⵉⵏ ⵏ ⵜⵎⴻⵥⵔⵉ, ⵢⴰⵍ ⵜⴰⴼⴻⵍⵡⵉⵜ ⵜⴻⵍⵍⴰ ⴷⴻⴳ ⵢⵉⵡⴻⵜ ⵏ ⵜⵎⴻⵥⵔⵉ ⵙⴻⴳ ⵓⵎⴳⵉⵔⴻⴷ ⵏ ⵜⵎⴻⵥⵔⵉ ⵏ ⵜⵎⴻⵥⵔⵉ :

ⴰⴽⵓⵍ:

ⴰⴷ ⴷⵢⴻⵙⵏⵓⵍⴼⵓ ⴰⵟⴰⵙ ⵏ ⵢⵉⴹⵔⵉⵙⴻⵏ ⵙ ⵜⵖⴰⵡⵍⴰ ⴷⴻⴳ ⵡⴰⵢⴻⵏ ⵢⴻⵔⵣⴰⵏ ⵜⵉⴳⵏⴰⵜⵉⵏ ⵏ ⵓⵎⴳⵉⵔⴻⴷ ⵡⵉⵙ 3.

seaborn.relplot(kind = 'scatter',
                data = dataset,
                x    = 'variable_1',
                y    = 'variable_2',
                col  = 'variable_3')

ⵡⴰ ⴷⴻⴼⴼⵉⵔ ⵏ ⵡⴰ:

seaborn.relplot(kind = 'scatter',
                data = dataset,
                x    = 'variable_1',
                y    = 'variable_2',
                row  = 'variable_3')

ⵏⴻⵣⵎⴻⵔ ⴷⴰⵖⴻⵏ ⴰⴷ ⵏⴻⵙⵙⴻⵅⴷⴻⵎ Hue ⴷ Size ⴷⴻⴳ ⵢⵉⵡⴻⵏ ⵏ ⵓⵙⵎⴻⵍ, ⴰⴽⴽⴻⵏ ⴰⴷ ⴷⵏⴻⵙⵙⴻⵎⵔⴻⵙ 4 ⵏ ⵢⵉⵎⴻⴹⵇⴰⵏ, ⵏⴻⵖ ⵓⵍⴰ ⴷ Hue ⴷ Style ⴷ Col, ⴰⴽⴽⴻⵏ ⴰⴷ ⵏⴻⵙⵙⴻⵅⴷⴻⵎ 5 ⵏ ⵢⵉⵎⴻⴹⵇⴰⵏ ⴷⴻⴳ ⵢⵉⵡⴻⵏ ⵏ ⵓⵙⵎⴻⵍ ! ⵏⴻⵣⵎⴻⵔ ⴰⴷ ⵏⴻⵙⵙⴻⵅⴷⴻⵎ ⴰⵍⴰⵎⵎⴰ ⴷ 7 ⵏ ⵢⵉⵎⴻⴹⵇⴰⵏ ( ⴰⵎⴳⵉⵔⴻⴷ 1, ⴰⵎⴳⵉⵔⴻⴷ 2, Hue, Size, Style, Col, Row ) ⴷⴻⴳ ⵢⵉⵡⴻⵏ ⵏ ⵓⴹⵔⵉⵙ, ⵎⴰⵛⴰ ⴰⴷ ⴰⵖⴷ-ⵢⴻⴼⴽ ⵢⵉⵡⴻⵏ ⵏ ⵓⴹⵔⵉⵙ ⵢⴻⵜⵜⵡⴰⵞⵞⴰⵔⴻⵏ ⴰⵟⴰⵙ ⴷ ⵡⵉⵏ ⵉⵅⵓⵚⵚⴻⵏ ⴰⵟⴰⵙ ⵢⴻⵔⵏⴰ ⴷ ⴰⵢⴻⵏ ⵉⵅⵓⵚⵚⴻⵏ ⴰⵟⴰⵙ ⴷⴻⴳ ⵓⵙⴼⴻⵀⴻⵎ, ⵜⵉⴽⵡⴰⵍ ⵓⵍⴰⵛ . ⵏ ⵜⵎⵓⵙⵏⵉ ⴷⴻⴳ ⵡⴰⴽⴽ.

seaborn.relplot(kind = 'scatter',
                data = dataset,
                x    = 'variable_1',
                y    = 'variable_2',
                hue  = 'variable_3',
                size = 'variable_4')

ⵜⴰⴳⴳⴰⵔⴰ:

ⴷⴻⴳ ⵓⴹⵔⵉⵙⴰ, ⵏⴻⵍⵎⴻⴷ ⵖⴻⴼ seaborn, 3 ⵏ ⵜⵖⴰⵡⵙⵉⵡⵉⵏⵉⵙ ⵏ ⵜⵖⴰⵡⵙⵉⵡⵉⵏ ⵏ ⵓⵙⵏⵓⵍⴼⵓ : Tifelwiyin ⵏ ⵜⵖⴰⵡⵙⵉⵡⵉⵏ, ⵏ ⵜⴼⴻⵔⴽⵉⵜ ⴷ ⵜⵖⴰⵡⵙⵉⵡⵉⵏ ⵏ ⵡⴰⵙⵙⴰⵖ, ⵢⴻⵔⵏⴰ ⵏⴻⵙⴼⴻⵀⵎⴷ ⵢⴰⵍ ⵜⴰⵖⴰⵡⵙⴰ ⵏ ⵓⵙⵏⵓⵍⴼⵓ ⵉ ⵢⴰⵍ ⵜⴰⵖⴰⵡⵙⴰ, ⴰⴽⴽ ⴰⴽⴽ ⴷ ⵍⵇⴰⵏⵓⵏ ⵏ python.

ⵥⴻⵔ Bootcamp ⵏ ⵜⵓⵙⵙⵏⴰ ⵏ ⵢⵉⵙⴻⴼⴽⴰⵏⵏⴻⵖ ⴰⴽⴽⴻⵏ ⴰⴷ ⵜⵍⴻⵎⴷⴻⴹ ⵓⴳⴰⵔ ⵖⴻⴼ ⵓⵙⴻⵏⵜⴻⵍⴰ!

ⴰⵙⴻⴽⵛⴻⵎ ⵏ ⵢⵉⵙⴻⴼⴽⴰ ⴷⴻⴳ Pitun ⵙ Seaborn

ⴰⵍⵍⴰⵍⴻⵏ ⵏ ⵓⵙⴻⴽⵍⴻⵙ

ⵉⵍⵓⵍⴻⵏ ⴷⴻⴳ ⵢⵉⵍⴻⵍ

ⵜⵉⴼⴻⵍⵡⵉⵢⵉⵏ ⵏ ⵜⴰⴳⴳⴰⵢⵜ

ⵉⵎⴻⵥⵍⴰ ⵏ ⵜⵎⵓⵙⵏⵉ

ⴰⴷ ⵏⴻⵇⵇⵉⵎ ⴷⴻⴳ ⵓⵙⵉⵡⴰⴹ