JupyDash
Drag a Jupyter notebook in. Get a live, modular dashboard of its outputs.
In [1]freq = 1.0
amp = 1.0
threshold = 0.60✨
In [2]y = amp*sin(freq*x) + noise
ax.plot(x, y)
In [3]ax.hist(y, bins=14)
In [4](y > threshold).sum()
In [5]pd.Series(y).describe()
JupyDash
✓ 11 ms
Signal⠿
Above threshold⠿
0of 120 samples
Distribution⠿
Stats⠿
| mean | 0.00 |
| std | 0.00 |
| max | 0.00 |
Universal (Apple Silicon + Intel) · macOS 11+ · runs notebooks in your own Jupyter kernel (ipykernel)