Scatter plots¶

In [1]:

import matplotlib.pyplot as plt
import plotly.express as px

import arcadia_pycolor as apc

apc.mpl.setup()
apc.plotly.setup()

df = px.data.iris()

import matplotlib.pyplot as plt import plotly.express as px import arcadia_pycolor as apc apc.mpl.setup() apc.plotly.setup() df = px.data.iris()

1. Scatter plot with Matplotlib¶

In [2]:

fig, ax = plt.subplots(figsize=apc.mpl.get_figure_dimensions("float_wide"), layout="constrained")
scatter = ax.scatter(
    x=df["sepal_width"],
    y=df["sepal_length"],
    c=df["petal_length"],
    cmap="apc:magma",
)
ax.set_xlabel("Sepal width")
ax.set_ylabel("Sepal length")

cb = fig.colorbar(scatter, ax=ax)
cb.set_label("Petal length")
cb.outline.set_visible(False)  # type: ignore

apc.mpl.style_plot(monospaced_axes="all", colorbar_exists=True)

plt.show()

fig, ax = plt.subplots(figsize=apc.mpl.get_figure_dimensions("float_wide"), layout="constrained") scatter = ax.scatter( x=df["sepal_width"], y=df["sepal_length"], c=df["petal_length"], cmap="apc:magma", ) ax.set_xlabel("Sepal width") ax.set_ylabel("Sepal length") cb = fig.colorbar(scatter, ax=ax) cb.set_label("Petal length") cb.outline.set_visible(False) # type: ignore apc.mpl.style_plot(monospaced_axes="all", colorbar_exists=True) plt.show()

2. Scatter plot with Plotly¶

In [3]:

fig = px.scatter(
    df,
    x="sepal_width",
    y="sepal_length",
    color="petal_length",
    color_continuous_scale=apc.gradients.magma.to_plotly_colorscale(),
)

apc.plotly.style_plot(fig, monospaced_axes="all")
apc.plotly.set_figure_dimensions(fig, "float_wide")

fig.show()

fig = px.scatter( df, x="sepal_width", y="sepal_length", color="petal_length", color_continuous_scale=apc.gradients.magma.to_plotly_colorscale(), ) apc.plotly.style_plot(fig, monospaced_axes="all") apc.plotly.set_figure_dimensions(fig, "float_wide") fig.show()