데이터 스토리텔링 포맷의 미래: 대시보드를 넘어선 새로운 경험

import plotly.graph_objects as go

fig = go.Figure()
fig.add_trace(go.Scatter(x=df["week"], y=df["signups"], mode="lines+markers", name="Signups"))

fig.update_layout(
    updatemenus=[dict(
        type="buttons",
        buttons=[
            dict(label="1) Overview", method="update", args=[{"visible": [True, False]}]),
            dict(label="2) Highlight", method="update", args=[{"visible": [True, False], "annotations": [dict(x=7, y=210, text="Launch")]}]),
            dict(label="3) Compare", method="update", args=[{"visible": [True, True]}])
        ]
    )]
)

import numpy as np
from IPython.display import Audio, display

def scale_to_freq(v):
    return min_f + (v - v_min) * (max_f - min_f) / (v_max - v_min)

audio_all = []
for v in visits:
    freq = scale_to_freq(v)
    t = np.linspace(0, note_dur, int(sample_rate * note_dur), endpoint=False)
    tone = 0.3 * np.sin(2 * np.pi * freq * t) * np.linspace(1, 0, len(t))
    audio_all.append(tone)

audio = np.concatenate(audio_all)
display(Audio(audio, rate=sample_rate))

import plotly.express as px
import ipywidgets as widgets

def render(threshold):
    filtered = df[df["score"] <= threshold]
    fig = px.scatter_3d(filtered, x="x", y="y", z="z", color="score")
    fig.show()

widgets.interact(render, threshold=(df["score"].min(), df["score"].max(), 0.05))