02. dataprep

Out:

  0%|          | 0/799 [00:00<?, ?it/s]
Computing series-max-agg-01366a2de6ffbca6d1e9ef985b4cf59f:   0%|          | 0/799 [00:00<?, ?it/s]
Computing series-max-agg-01366a2de6ffbca6d1e9ef985b4cf59f:   0%|          | 0/799 [00:00<?, ?it/s]
Computing series-min-agg-b5e434e390e46a13d2dc9b111720eefc: 100%|##########| 799/799 [00:00<00:00, 4762.67it/s]

Report has been saved to outputs/profile02-report.html!

# Libraries
import pandas as pd

# Specific
from dataprep.eda import create_report
from sklearn.datasets import load_iris
from pathlib import Path

# Load data object
obj = load_iris(as_frame=True)

# Create report
profile = create_report(obj.data,
    title="Pandas Profiling Report")

# Save to file
Path('./outputs').mkdir(parents=True, exist_ok=True)
profile.save("./outputs/profile02-report.html")

# Show report in the browser
#profile.show_browser()