plotly-dashboard-with-plotly-dash

Sub-skill of plotly: Dashboard with Plotly Dash.

5 stars

Best use case

plotly-dashboard-with-plotly-dash is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Sub-skill of plotly: Dashboard with Plotly Dash.

Teams using plotly-dashboard-with-plotly-dash should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

You only need a quick one-off answer and do not need a reusable workflow.
You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/dashboard-with-plotly-dash/SKILL.md --create-dirs "https://raw.githubusercontent.com/vamseeachanta/workspace-hub/main/.agents/skills/_archive/data/visualization/plotly/dashboard-with-plotly-dash/SKILL.md"

Manual Installation

Download SKILL.md from GitHub
Place it in .claude/skills/dashboard-with-plotly-dash/SKILL.md inside your project
Restart your AI agent — it will auto-discover the skill

How plotly-dashboard-with-plotly-dash Compares

Feature / Agent	plotly-dashboard-with-plotly-dash	Standard Approach
Platform Support	Not specified	Limited / Varies
Context Awareness	High	Baseline
Installation Complexity	Unknown	N/A

Frequently Asked Questions

What does this skill do?

Sub-skill of plotly: Dashboard with Plotly Dash.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Dashboard with Plotly Dash

## Dashboard with Plotly Dash


```python
import dash
from dash import dcc, html, Input, Output
import plotly.express as px
import pandas as pd

# Load data
df = pd.read_csv('../data/processed/dashboard_data.csv')

# Initialize app
app = dash.Dash(__name__)

# Layout
app.layout = html.Div([
    html.H1('Interactive Dashboard'),

    html.Div([
        html.Label('Select Category:'),
        dcc.Dropdown(
            id='category-dropdown',
            options=[{'label': cat, 'value': cat} for cat in df['category'].unique()],
            value=df['category'].unique()[0]
        )
    ], style={'width': '50%'}),


*See sub-skills for full details.*

Related Skills

well-production-dashboard

from vamseeachanta/workspace-hub

Create interactive well production dashboards with real-time monitoring, verification integration, economic metrics, and multi-format exports. Use for well performance analysis, field aggregation, production forecasting, and API-driven dashboards.