Test notebook Titanic¶

from pathlib import Path

import numpy as np
import pandas as pd
from IPython.utils.capture import capture_output
from ipywidgets import widgets

from ydata_profiling import ProfileReport
from ydata_profiling.utils.cache import cache_file

# Read the Titanic Dataset
file_name = cache_file(
    "titanic.csv",
    "https://raw.githubusercontent.com/datasciencedojo/datasets/master/titanic.csv",
)
df = pd.read_csv(file_name)

# Generate the Profiling Report (with progress bar)
with capture_output() as out:
    profile = ProfileReport(
        df,
        title="Titanic Dataset",
        html={"style": {"full_width": True}},
        progress_bar=True,
        lazy=False,
    )

assert all(
    any(v in s.data["text/plain"] for v in ["%|", "FloatProgress"]) for s in out.outputs
)
assert len(out.outputs) == 2

# Generate the Profiling Report (without progress bar)
with capture_output() as out:
    profile = ProfileReport(
        df,
        title="Titanic Dataset",
        html={"style": {"full_width": True}},
        progress_bar=False,
        lazy=False,
    )

assert len(out.outputs) == 0

# Waiting on issue: https://github.com/computationalmodelling/nbval/issues/136

# The Notebook Widgets Interface
# with capture_output() as out:
#     profile.to_widgets()

# assert len(out.outputs) == 2
# assert out.outputs[0].data['text/plain'].startswith('Tab(children=(HTML(value=')
# assert out.outputs[1].data['text/plain'] == '<IPython.core.display.HTML object>'
# assert 'ydata-profiling' in out.outputs[1].data['text/html']

# Or use the HTML report in an iframe
with capture_output() as out:
    profile.to_notebook_iframe()

assert len(out.outputs) == 1
assert out.outputs[0].data["text/plain"] == "<IPython.core.display.HTML object>"