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dayplot

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.

Examples

import matplotlib.pyplot as plt
import dayplot as dp

df = dp.load_dataset()  # requires pandas to be installed

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()

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()

# add negative values at some random dates
df.loc[df.sample(n=40, replace=False).index, "values"] *= -1

fig, ax = plt.subplots(figsize=(16, 4))
dp.calendar(
    dates=df["dates"],
    values=df["values"],
    cmap="RdBu", # use a diverging colormap (red -> white -> blue)
    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()

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=1.15,
    ax=ax,
)


import matplotlib.pyplot as plt
import dayplot as dp

df = dp.load_dataset()

fig, ax = plt.subplots(figsize=(15, 6))
dp.calendar(
    df["dates"],
    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()

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,
)

You can find more examples in the Gallery.

Installation

pip install dayplot

Advanced usage

dayplot is designed to fit any matplotlib graph, allowing you to do things like: