edfEazyDataFix

CSV Cleaning

Load a messy CSV, assess quality and export a cleaned copy.

Overview

The canonical EazyDataFix workflow — read a CSV, understand what is wrong with it, then apply the automatic cleaning pipeline and export the result.

Dataset

employees.csv1,204 rows × 12 columns
idnameemaildepartmentsalaryhire_date...

Python code

csv-cleaning.py
import eazydatafix as edf

report = edf.assess("employees.csv")
report.summary()

result = edf.fix("employees.csv", strategy="safe")
result.applied_fixes
result.to_csv("employees.clean.csv")

Expected output

Python 3.11
>>> report = edf.assess("employees.csv")
>>> report.summary()
QualityReport(employees.csv) score=94.0
 
>>> result = edf.fix("employees.csv")
>>> result.applied_fixes
['strip_whitespace', 'coerce_numeric', 'drop_duplicates(6)']
Excel Cleaning
Handle merged cells, blank rows and inconsistent columns from .xlsx workbooks.
Hospital Dataset
Assess a hospital admissions dataset with mixed dtypes and PII.
HR Dataset
Detect duplicate employee records and normalise department names.