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dayplot

dayplot logo

A simple-to-use Python library to build calendar heatmaps with ease. It's built on top of matplotlib and leverages it to access high customization possibilities. They can even be interactive!

Examples

import matplotlib.pyplot as plt
import dayplot as dp

df = dp.load_dataset("pandas") # can also be "polars", "pyarrow", etc

fig, ax = plt.subplots(figsize=(15, 6))
dp.calendar(
    dates=df["dates"],
    values=df["values"],
    start_date="2024-01-01",
    end_date="2024-12-31",
    ax=ax,
)


import matplotlib.pyplot as plt
import dayplot as dp

df = dp.load_dataset("pandas")

fig, ax = plt.subplots(figsize=(15, 6))
dp.calendar(
    dates=df["dates"],
    values=df["values"],
    cmap="Reds", # any matplotlib colormap
    start_date="2024-01-01",
    end_date="2024-12-31",
    ax=ax,
)


import matplotlib.pyplot as plt
import dayplot as dp

df = dp.load_dataset("pandas")

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=1.22,
    ax=ax,
)


import matplotlib.pyplot as plt
import dayplot as dp

df = dp.load_dataset("pandas")

fig, ax = plt.subplots(figsize=(15, 6))
dp.calendar(
    dates=df["dates"],
    values=df["values"],
    start_date="2024-01-01",
    end_date="2024-12-31",
    color_for_none="#bcbcbc",
    edgecolor="white",
    edgewidth=0.4,
    cmap="OrRd",
    day_kws={"color": "white"},
    month_kws={"color": "white"},
    ax=ax,
)
fig.set_facecolor("#2a2929")
ax.set_facecolor("#2a2929")


import matplotlib.pyplot as plt
import dayplot as dp

df = dp.load_dataset("pandas")

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,
)


import matplotlib.pyplot as plt
import dayplot as dp

df = dp.load_dataset("pandas")

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",
    ax=ax,
    **dp.styles["github"]
)
fig.set_facecolor("#0d1117")
ax.set_facecolor("#0d1117")


import matplotlib.pyplot as plt
import dayplot as dp

df = dp.load_dataset("pandas")

fig, ax = plt.subplots(figsize=(15, 6))
dp.calendar(
    dates=df["dates"],
    values=df["values"],
    start_date="2024-01-01",
    end_date="2024-12-31",
    month_grid=True,
    ax=ax,
)

You can also make dayplot interactive thanks to plotjs:

import matplotlib.pyplot as plt
import dayplot as dp
from plotjs import PlotJS

df = dp.load_dataset()

fig, ax = plt.subplots(figsize=(15, 6))
dp.calendar(
    dates=df["dates"],
    values=df["values"],
    start_date="2024-01-01",
    end_date="2024-12-31",
    ax=ax,
)
PlotJS(fig).add_tooltip(labels=df["values"]).save("docs/img/interactive.html")

See more examples

Installation

pip install dayplot

pip install git+https://github.com/y-sunflower/dayplot.git@main