edfEazyDataFix

Profiling

edf.profile() gives you a fast structural inventory: shape, columns, data types and memory use.

Basic usage

profile.py
import eazydatafix as edf

profile = edf.profile("hospital.csv")

print(profile.rows, profile.columns)
print(profile.column_names)
print(profile.data_types)
print(profile.memory_usage_bytes)
Python 3.11
>>> profile.rows, profile.columns
(15, 8)
>>> profile.column_names[:3]
['patient_id', 'age', 'gender']

Available fields

  • file_name and file_type
  • rows and columns
  • column_names and data_types
  • memory_usage_bytes

Profile versus assess

A profile describes the dataset structure only. Use edf.assess() when you need missing-value counts, duplicates, quality dimensions, recommendations or an exportable report.

See also

Full details at edf.profile(), or continue to assessment.