Seaborn - lmplot 차트/그래프 그리기 Cheet Sheet

Anscombe’s quartet

seaborn components used: set_theme(), load_dataset(), lmplot()

import seaborn as sns
sns.set_theme(style="ticks")

# Load the example dataset for Anscombe's quartet
df = sns.load_dataset("anscombe")

# Show the results of a linear regression within each dataset
sns.lmplot(x="x", y="y", col="dataset", hue="dataset", data=df,
           col_wrap=2, ci=None, palette="muted", height=4,
           scatter_kws={"s": 50, "alpha": 1})

---

Faceted logistic regression

seaborn components used: set_theme(), load_dataset(), lmplot()

import seaborn as sns
sns.set_theme(style="darkgrid")

# Load the example Titanic dataset
df = sns.load_dataset("titanic")

# Make a custom palette with gendered colors
pal = dict(male="#6495ED", female="#F08080")

# Show the survival probability as a function of age and sex
g = sns.lmplot(x="age", y="survived", col="sex", hue="sex", data=df,
               palette=pal, y_jitter=.02, logistic=True, truncate=False)
g.set(xlim=(0, 80), ylim=(-.05, 1.05))

---

Multiple linear regression

seaborn components used: set_theme(), load_dataset(), lmplot()

import seaborn as sns
sns.set_theme()

# Load the penguins dataset
penguins = sns.load_dataset("penguins")

# Plot sepal width as a function of sepal_length across days
g = sns.lmplot(
    data=penguins,
    x="bill_length_mm", y="bill_depth_mm", hue="species",
    height=5
)

# Use more informative axis labels than are provided by default
g.set_axis_labels("Snoot length (mm)", "Snoot depth (mm)")

 

출처 : https://seaborn.pydata.org/