Profiling

Basic usage

import pandas as pd
import eazydatafix as edf

df = pd.read_csv("hospital.csv")
prof = edf.profile(df, sample=10_000)
prof.columns["age"]

>>> prof = edf.profile(df, sample=10_000)
>>> prof.columns["age"]
ColumnProfile(age)
  dtype       int64
  missing     0
  unique      87
  min         0
  max         104
  mean        42.3
  median      41

Correlations

By default, profile() computes Pearson correlations for numeric columns. Disable with correlations=False on very wide datasets.

Sampling

For datasets larger than ~5M rows, pass sample= to keep profiling under a second while retaining a representative distribution.

Exporting

prof.to_html("out.html") writes a shareable HTML profile. prof.to_dict() returns a JSON-friendly dict.

See also

Full options at edf.profile().