Boxstyle

Make fancy cells

Under the hood, dayplot uses a niche matplotlib object called a FancyBboxPatch. It's pretty much a rectangle, but with much higher customization level.

boxstyle

By default, you'll get simple squares, but you can leverage the boxstyle argument to do much fancier things.

circleroundsawtoothroundtoothround4

# mkdocs: render
import matplotlib.pyplot as plt
import dayplot as dp
from dayplot.data import load_dataset

df = load_dataset()

fig, ax = plt.subplots(figsize=(16, 4))
dp.calendar(
    dates=df["dates"],
    values=df["values"],
    start_date="2024-01-01",
    end_date="2024-12-31",
    boxstyle="circle",
    ax=ax,
)

# mkdocs: render
import matplotlib.pyplot as plt
import dayplot as dp
from dayplot.data import load_dataset

df = load_dataset()

fig, ax = plt.subplots(figsize=(16, 4))
dp.calendar(
    dates=df["dates"],
    values=df["values"],
    start_date="2024-01-01",
    end_date="2024-12-31",
    boxstyle="round",
    ax=ax,
)

# mkdocs: render
import matplotlib.pyplot as plt
import dayplot as dp
from dayplot.data import load_dataset

df = load_dataset()

fig, ax = plt.subplots(figsize=(16, 4))
dp.calendar(
    dates=df["dates"],
    values=df["values"],
    start_date="2024-01-01",
    end_date="2024-12-31",
    boxstyle="sawtooth",
    ax=ax,
)

# mkdocs: render
import matplotlib.pyplot as plt
import dayplot as dp
from dayplot.data import load_dataset

df = load_dataset()

fig, ax = plt.subplots(figsize=(16, 4))
dp.calendar(
    dates=df["dates"],
    values=df["values"],
    start_date="2024-01-01",
    end_date="2024-12-31",
    boxstyle="roundtooth",
    ax=ax,
)

# mkdocs: render
import matplotlib.pyplot as plt
import dayplot as dp
from dayplot.data import load_dataset

df = load_dataset()

fig, ax = plt.subplots(figsize=(16, 4))
dp.calendar(
    dates=df["dates"],
    values=df["values"],
    start_date="2024-01-01",
    end_date="2024-12-31",
    boxstyle="round4",
    ax=ax,
)

Other arguments

The dp.calendar() function will take all additional arguments and pass them to each FancyBboxPatch.

This means that any argument that this class accepts will be accepted. Here is a non-exhaustive list.

mutation_scale (size scale)hatchalphalinestyle

# mkdocs: render
import matplotlib.pyplot as plt
import dayplot as dp
from dayplot.data import load_dataset

df = load_dataset()

fig, ax = plt.subplots(figsize=(16, 4))
dp.calendar(
    dates=df["dates"],
    values=df["values"],
    start_date="2024-01-01",
    end_date="2024-12-31",
    mutation_scale=0.8, # 80% of original size
    ax=ax,
)

# mkdocs: render
import matplotlib.pyplot as plt
import dayplot as dp
from dayplot.data import load_dataset

df = load_dataset()

fig, ax = plt.subplots(figsize=(16, 4))
dp.calendar(
    dates=df["dates"],
    values=df["values"],
    start_date="2024-01-01",
    end_date="2024-12-31",
    hatch="*",
    ax=ax,
)

# mkdocs: render
import matplotlib.pyplot as plt
import dayplot as dp
from dayplot.data import load_dataset

df = load_dataset()

fig, ax = plt.subplots(figsize=(16, 4))
dp.calendar(
    dates=df["dates"],
    values=df["values"],
    start_date="2024-01-01",
    end_date="2024-12-31",
    alpha=0.5,
    ax=ax,
)

# mkdocs: render
import matplotlib.pyplot as plt
import dayplot as dp
from dayplot.data import load_dataset

df = load_dataset()

fig, ax = plt.subplots(figsize=(16, 4))
dp.calendar(
    dates=df["dates"],
    values=df["values"],
    start_date="2024-01-01",
    end_date="2024-12-31",
    linestyle="--",
    edgewidth=1,
    ax=ax,
)