Scatterplot

import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
sns.set_theme()

tips = sns.load_dataset("tips")
tips.head()

sns.scatterplot(data=tips, x="total_bill", y="tip")

sns.scatterplot(data=tips, x="total_bill", y="tip", hue="time")

sns.scatterplot(data=tips, x="total_bill", y="tip", hue="time", style="time")

sns.scatterplot(data=tips, x="total_bill", y="tip", hue="day", style="time")

sns.scatterplot(data=tips, x="total_bill", y="tip", hue="size")

sns.scatterplot(data=tips, x="total_bill", y="tip", hue="size", palette="deep")

tip_rate = tips.eval("tip / total_bill").rename("tip_rate")
sns.scatterplot(data=tips, x="total_bill", y="tip", hue=tip_rate)

sns.scatterplot(data=tips, x="total_bill", y="tip", hue="size", size="size")

sns.scatterplot(
    data=tips, x="total_bill", y="tip", hue="size", size="size",
    sizes=(20, 200), legend="full"
)

sns.scatterplot(
    data=tips, x="total_bill", y="tip", hue="size", size="size",
    sizes=(20, 200), hue_norm=(0, 7), legend="full"
)

markers = {"Lunch": "s", "Dinner": "X"}
sns.scatterplot(data=tips, x="total_bill", y="tip", style="time", markers=markers)

sns.scatterplot(data=tips, x="total_bill", y="tip", s=100, color=".2", marker="+")

index = pd.date_range("1 1 2000", periods=100, freq="ME", name="date")
data = np.random.randn(100, 4).cumsum(axis=0)
wide_df = pd.DataFrame(data, index, ["a", "b", "c", "d"])
sns.scatterplot(data=wide_df)

sns.relplot(
    data=tips, x="total_bill", y="tip",
    col="time", hue="day", style="day",
    kind="scatter"
)