pandas-eda-check
pandas-eda-check is a lightweight utility for quickly summarizing data types,
unique values, completeness, and missingness in a pandas DataFrame.
Features
- One-row-per-column data quality report
- Dataset-level missing-data summary
- Optional filtering to columns with missing values
- Sorting by missing percentage, missing count, unique count, or data type
- Report metadata stored in
DataFrame.attrs - Safe handling of empty DataFrames and duplicate column names
Installation
pip install pandas-eda-check
Python 3.9 or newer is required.
Usage
import pandas as pd
from pandas_eda_check import check
df = pd.DataFrame(
{
"name": ["Ada", "Bob", "Bob"],
"age": [36, None, 29],
"city": ["London", "Paris", None],
}
)
report = check(df)
print(report)
Console summary:
Data Shape: (3, 3)
Total Missing Cells: 2
Rows With Missing Values: 2
Overall Missing Percentage: 22.22%
Report:
Data Type Unique Values Values Present Missing Count Missing %
name object 2 3 0 0.00
age float64 2 2 1 33.33
city object 2 2 1 33.33
The original DataFrame column names are used as the report index.
Parameters
check(
data,
include_dtypes=True,
include_complete=True,
sort_by=None,
ascending=False,
round_digits=2,
display=True,
)
| Parameter | Description |
|---|---|
data |
pandas DataFrame to inspect. |
include_dtypes |
Include the Data Type report column. |
include_complete |
Include columns that have no missing values. |
sort_by |
Sort by missing_pct, missing_count, unique, or dtype. |
ascending |
Use ascending order when sorting. |
round_digits |
Non-negative number of decimal places for percentages. |
display |
Print the dataset-level summary. |
Sorting
check(df, sort_by="missing_pct")
check(df, sort_by="missing_count")
check(df, sort_by="unique")
check(df, sort_by="dtype", ascending=True)
Columns with missing values only
missing_columns = check(df, include_complete=False)
Suppress console output
report = check(df, display=False)
Report metadata
report.attrs["shape"]
report.attrs["total_missing_cells"]
report.attrs["rows_with_missing"]
report.attrs["overall_missing_percent"]
Development
Install the package and development tools in editable mode:
python -m pip install -e ".[dev]"
Run the tests:
python -m pytest
Build and validate the distribution:
python -m build
python -m twine check dist/*
License
MIT License. See LICENSE.
1 maintainer
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