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Package |
Documentation: https://dribia.github.io/driviz
Source Code: https://github.com/dribia/driviz
This project resides in the Python Package Index (PyPI), so it can easily be installed with pip:
pip install driviz
from driviz import theme
theme.enable()
import altair as alt
import numpy as np
import pandas as pd
import random
from driviz import theme
theme.enable()
variety = [f"V{i}" for i in range(10)]
site = [f"site{i:02d}" for i in range(14)]
k = 10000
df = pd.DataFrame(
data={
"yield": np.random.rand(k,),
"variety": random.choices(variety, k=k),
"site": random.choices(site, k=k),
}
)
selection = alt.selection_point(fields=["site"], bind="legend")
bars = (
alt.Chart(df)
.mark_bar()
.encode(
x=alt.X("sum(yield):Q", stack="zero"),
y=alt.Y("variety:N"),
color=alt.Color("site"),
opacity=alt.condition(
selection, alt.value(1), alt.value(0.2)
)
)
.properties(title="Example chart")
.add_params(selection)
)
text = (
alt.Chart(df)
.mark_text(dx=-15, dy=3, color="white")
.encode(
x=alt.X("sum(yield):Q", stack="zero"),
y=alt.Y("variety:N"),
detail="site:N",
text=alt.Text("sum(yield):Q", format=".1f")
)
)
chart = bars + text
chart.save(
"altair_example_barh.html"
)
Poetry is the best way to interact with this project, to install it, follow the official Poetry installation guide.
With poetry
installed, one can install the project dependencies with:
make setup
Then, to run the project unit tests:
make test-unit
To run the linters (ruff
and mypy
):
make lint
To apply all code formatting:
make format
driviz
is distributed under the terms of the
MIT license.
Check the LICENSE file for further details.
FAQs
Data Visualization Library containing the Dribia Theme.
We found that driviz demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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