EDA VizKit
Reusable visualizations for inspecting and exploring data.
EDA VizKit provides high-level Python functions for common
exploratory data analysis visualizations.
The package works with ordinary pandas DataFrames and
returns Matplotlib Axes objects.
EDA VizKit does not clean data, classify variables, select relationships, make analytical decisions, or interpret results.
Design
- Accept ordinary pandas DataFrames and explicit column names.
- Provide reusable visualizations for common EDA tasks.
- Return Matplotlib
Axesobjects. - Never call
plt.show(). - Keep analytical choices visible to the caller.
- Avoid dependencies on analytical workflow frameworks.
- Keep the implementation readable and replaceable.
Install
uv add eda-vizkit
Example
from eda_vizkit import show_numeric_distribution
ax = show_numeric_distribution(
df,
column="body_mass_g",
)
ax.set_title("Penguin Body Mass")
The caller controls display and composition. In a script, for example:
import matplotlib.pyplot as plt
from eda_vizkit import show_numeric_distribution
ax = show_numeric_distribution(
df,
column="body_mass_g",
)
plt.show()
Initial API
Distributions:
show_numeric_distribution()show_categorical_distribution()
Relationships:
show_numeric_relationship()show_numeric_by_category()
Data quality:
show_missing_values()
Public Contract
Every public visualization helper:
- accepts already-available data,
- keeps the analytical choice explicit,
- returns a Matplotlib
Axesobject, - never calls
plt.show().
This allows the visualization helpers to work in scripts, applications, notebooks, documentation, and other presentation environments.
Example: Numeric Distribution
from eda_vizkit import show_numeric_distribution
ax = show_numeric_distribution(
df,
column="flipper_length_mm",
)
Example: Categorical Distribution
from eda_vizkit import show_categorical_distribution
ax = show_categorical_distribution(
df,
column="species",
)
Example: Numeric Relationship
from eda_vizkit import show_numeric_relationship
ax = show_numeric_relationship(
df,
x="flipper_length_mm",
y="body_mass_g",
)
Example: Numeric Variable by Category
from eda_vizkit import show_numeric_by_category
ax = show_numeric_by_category(
df,
numeric="body_mass_g",
category="species",
)
Example: Missing Values
from eda_vizkit import show_missing_values
ax = show_missing_values(df)
Developer Command Reference
Show command reference
In a machine terminal
Open a machine terminal where you want the project:
git clone https://github.com/analytics-toolworks/eda-vizkit
cd eda-vizkit
code .
In a VS Code terminal
uv self update
uv python pin 3.14
uv python install
uv lock --upgrade
uv sync
uv run pre-commit install
uv run pre-commit autoupdate
git add -A
uv run pre-commit run --all-files
# repeat if changes were made
uv run pre-commit run --all-files
# types, tests, docs
uv run ty check
uv run python -m pytest
uv run python -m zensical build
# save progress
git add -A
git commit -m "update"
git push -u origin main
Documentation
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1 maintainer
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