Histogramas condicionales univariados con displot() —-#

0:00 min | Última modificación: Octubre 13, 2021 | [YouTube]

[1]:

import matplotlib.pyplot as plt
import seaborn as sns

[2]:

penguins = sns.load_dataset("penguins")

[3]:

#
# Visualización por defecto
#
sns.displot(
    penguins,
    x="flipper_length_mm",
    hue="species",
    kind="hist",
)
plt.show()

../../_images/02_seaborn_notebooks_3-31_distributions_displot_hist_condicionales_3_0.png

[4]:

#
# Cambio de la representación visual
#
sns.displot(
    penguins,
    x="flipper_length_mm",
    hue="species",
    element="step",
)
plt.show()

../../_images/02_seaborn_notebooks_3-31_distributions_displot_hist_condicionales_4_0.png

[5]:

#
# Histogramas apilados
#
sns.displot(
    penguins,
    x="flipper_length_mm",
    hue="species",
    multiple="stack",
)
plt.show()

../../_images/02_seaborn_notebooks_3-31_distributions_displot_hist_condicionales_5_0.png

[6]:

#
# Histograma con barras agrupadas
#
sns.displot(
    penguins,
    x="flipper_length_mm",
    hue="sex",
    multiple="dodge",
)
plt.show()

../../_images/02_seaborn_notebooks_3-31_distributions_displot_hist_condicionales_6_0.png

[7]:

#
# Separación por categoria
#
sns.displot(
    penguins,
    x="flipper_length_mm",
    col="sex",
)
plt.show()

../../_images/02_seaborn_notebooks_3-31_distributions_displot_hist_condicionales_7_0.png