1. Use Minimal Mode for Large Datasets (+3)
1. Use Minimal Mode for Large Datasets
# GOOD: Minimal mode for large data
profile = ProfileReport(large_df, minimal=True)
# AVOID: Full explorative on large data
# profile = ProfileReport(large_df, explorative=True) # Slow!
2. Sample for Initial Exploration
# GOOD: Sample first, then full profile
sample = df.sample(n=10000, random_state=42)
profile = ProfileReport(sample, title="Sample Profile")
# If interesting, profile full data
# profile_full = ProfileReport(df, minimal=True)
3. Customize for Your Needs
# GOOD: Disable unnecessary computations
profile = ProfileReport(
df,
correlations={"pearson": {"calculate": True}}, # Only Pearson
missing_diagrams={"bar": True, "matrix": False, "heatmap": False}
)
4. Use Lazy Evaluation
# GOOD: Lazy profile, compute when needed
profile = ProfileReport(df, lazy=True)
# ... do other work ...
profile.to_file("report.html") # Computes here