Es interesante ver la distribución del conjunto de datos de las tres especies. 🤔
Ciertamente, parece bimodal, aunque posiblemente al normalizar la data, encontraremos algún factor influyente que cambie este panorama 📊
var_flipper_len = processed_penguins_df['flipper_length_mm']
g=sns.histplot(
data=processed_penguins_df,
x='flipper_length_mm',
binwidth=1,
hue='species',
alpha=.5
)
g.set_title('Penguins Flipper Length Distribution', y=1.03)
# Mean(Red)
plt.axvline(
x =var_flipper_len.mean(),
linestyle="dashed",
color="r",
linewidth=2
)
# Median(Green)
plt.axvline(
x=var_flipper_len.median(),
linestyle="dashed",
color="g",
linewidth=2
)
# Q_75(Black)
plt.axvline(
x=var_flipper_len.quantile(0.75),
linestyle="dashed",
color="k",
linewidth=2
)
# Q_25(Black)
plt.axvline(
x=var_flipper_len.quantile(0.25),
linestyle="dashed",
color="k",
linewidth=2
)
plt.text(184.7,17.5, 'Q(25%)', fontsize=12)
plt.text(192,17.5, 'median', fontsize=12, color='g')
plt.text(201.5,17.5, 'mean', fontsize=12, color='r')
plt.text(213.5,17.5, 'Q(75%)', fontsize=12)
plt.show()
