Example of dynamic data visualization with Plotly where more data points are gradually added.

polotly-streaming-data.py

import plotly.graph_objects as go
from time import sleep
import numpy as np

fig = go.FigureWidget()
# Display in Jupyter:
display(fig)
sleep(.25)

fig.add_trace(go.Scatter(x=[0], y=[0]))

for x in range(200):
    fig.data[0].x = np.concatenate([fig.data[0].x, [x]])
    fig.data[0].y = np.concatenate([fig.data[0].y, [fig.data[0].y[-1] + np.random.uniform(-.1, +.1)]])
    
    sleep(.001)