Data Visualizer
by daffy0208
Expert in creating charts, dashboards, and data visualizations using modern libraries
Skill Details
Repository Files
3 files in this skill directory
name: data-visualizer description: Expert in creating charts, dashboards, and data visualizations using modern libraries version: 1.0.0 tags: [data-viz, charts, dashboards, d3, recharts, analytics]
Data Visualizer Skill
I help you build beautiful, interactive data visualizations and dashboards.
What I Do
Chart Creation:
- Line charts, bar charts, pie charts
- Area charts, scatter plots, heatmaps
- Complex visualizations (Sankey, treemaps, network graphs)
Dashboard Building:
- KPI cards and metrics
- Real-time data dashboards
- Interactive filters and drill-downs
- Responsive layouts
Data Presentation:
- Data storytelling
- Color schemes and accessibility
- Animation and interactions
- Export capabilities
Library Selection Guide
Recharts (Recommended for React)
Best for:
- Quick, simple charts
- React/Next.js projects
- Standard chart types
- Responsive design
Example:
import { LineChart, Line, XAxis, YAxis, CartesianGrid, Tooltip, Legend } from 'recharts'
const data = [
{ month: 'Jan', revenue: 4000, expenses: 2400 },
{ month: 'Feb', revenue: 3000, expenses: 1398 },
{ month: 'Mar', revenue: 2000, expenses: 9800 },
]
function RevenueChart() {
return (
<LineChart width={600} height={300} data={data}>
<CartesianGrid strokeDasharray="3 3" />
<XAxis dataKey="month" />
<YAxis />
<Tooltip />
<Legend />
<Line type="monotone" dataKey="revenue" stroke="#8884d8" />
<Line type="monotone" dataKey="expenses" stroke="#82ca9d" />
</LineChart>
)
}
Chart.js (Recommended for Vue/Angular)
Best for:
- Framework-agnostic
- Simple API
- Good documentation
- Standard chart types
Example:
import { Chart } from 'chart.js/auto'
const ctx = document.getElementById('myChart')
const chart = new Chart(ctx, {
type: 'bar',
data: {
labels: ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun'],
datasets: [
{
label: 'Sales',
data: [12, 19, 3, 5, 2, 3],
backgroundColor: 'rgba(54, 162, 235, 0.5)'
}
]
},
options: {
responsive: true,
plugins: {
legend: { position: 'top' },
title: { display: true, text: 'Monthly Sales' }
}
}
})
D3.js (Advanced)
Best for:
- Custom visualizations
- Complex interactions
- Full control over rendering
- Data-driven documents
When to use:
- Need custom chart type
- Complex data transformations
- Advanced interactions
- Publication-quality graphics
Example:
import * as d3 from 'd3'
function createBarChart(data: Array<{ name: string; value: number }>) {
const width = 600
const height = 400
const margin = { top: 20, right: 20, bottom: 30, left: 40 }
const svg = d3.select('#chart').append('svg').attr('width', width).attr('height', height)
const x = d3
.scaleBand()
.domain(data.map(d => d.name))
.range([margin.left, width - margin.right])
.padding(0.1)
const y = d3
.scaleLinear()
.domain([0, d3.max(data, d => d.value)])
.range([height - margin.bottom, margin.top])
svg
.selectAll('rect')
.data(data)
.join('rect')
.attr('x', d => x(d.name))
.attr('y', d => y(d.value))
.attr('height', d => y(0) - y(d.value))
.attr('width', x.bandwidth())
.attr('fill', 'steelblue')
// Add axes
svg
.append('g')
.attr('transform', `translate(0,${height - margin.bottom})`)
.call(d3.axisBottom(x))
svg.append('g').attr('transform', `translate(${margin.left},0)`).call(d3.axisLeft(y))
}
Dashboard Patterns
Pattern 1: KPI Dashboard
Use case: Executive dashboard with key metrics
// components/KPIDashboard.tsx
import { Card } from '@/components/ui/card'
interface KPICardProps {
title: string
value: string | number
change: number
trend: 'up' | 'down'
}
function KPICard({ title, value, change, trend }: KPICardProps) {
const trendColor = trend === 'up' ? 'text-green-600' : 'text-red-600'
const trendIcon = trend === 'up' ? '↑' : '↓'
return (
<Card className="p-6">
<h3 className="text-sm font-medium text-gray-600">{title}</h3>
<div className="mt-2 flex items-baseline">
<p className="text-3xl font-semibold">{value}</p>
<span className={`ml-2 text-sm ${trendColor}`}>
{trendIcon} {Math.abs(change)}%
</span>
</div>
</Card>
)
}
export default function Dashboard() {
return (
<div className="grid grid-cols-1 md:grid-cols-2 lg:grid-cols-4 gap-6">
<KPICard title="Total Revenue" value="$45,231" change={12.5} trend="up" />
<KPICard title="Active Users" value="2,350" change={-5.2} trend="down" />
<KPICard title="Conversion Rate" value="3.24%" change={8.1} trend="up" />
<KPICard title="Avg Order Value" value="$158" change={2.3} trend="up" />
</div>
)
}
Pattern 2: Real-Time Dashboard
Use case: Live data monitoring
// components/RealtimeDashboard.tsx
'use client'
import { useEffect, useState } from 'react'
import { LineChart, Line, XAxis, YAxis, Tooltip, ResponsiveContainer } from 'recharts'
interface DataPoint {
time: string
value: number
}
export default function RealtimeDashboard() {
const [data, setData] = useState<DataPoint[]>([])
useEffect(() => {
// Fetch initial data
fetch('/api/metrics/realtime')
.then(res => res.json())
.then(setData)
// Subscribe to real-time updates
const eventSource = new EventSource('/api/metrics/stream')
eventSource.onmessage = (event) => {
const newDataPoint = JSON.parse(event.data)
setData(prev => {
const updated = [...prev, newDataPoint]
// Keep last 20 data points
return updated.slice(-20)
})
}
return () => eventSource.close()
}, [])
return (
<div className="p-6 bg-white rounded-lg shadow">
<h2 className="text-xl font-bold mb-4">Live Traffic</h2>
<ResponsiveContainer width="100%" height={300}>
<LineChart data={data}>
<XAxis dataKey="time" />
<YAxis />
<Tooltip />
<Line
type="monotone"
dataKey="value"
stroke="#8884d8"
strokeWidth={2}
dot={false}
isAnimationActive={false}
/>
</LineChart>
</ResponsiveContainer>
</div>
)
}
API Route for SSE:
// app/api/metrics/stream/route.ts
export async function GET(req: Request) {
const encoder = new TextEncoder()
const stream = new ReadableStream({
async start(controller) {
const interval = setInterval(async () => {
const value = Math.floor(Math.random() * 100)
const time = new Date().toLocaleTimeString()
const data = `data: ${JSON.stringify({ time, value })}\n\n`
controller.enqueue(encoder.encode(data))
}, 1000)
// Cleanup on close
req.signal.addEventListener('abort', () => {
clearInterval(interval)
controller.close()
})
}
})
return new Response(stream, {
headers: {
'Content-Type': 'text/event-stream',
'Cache-Control': 'no-cache',
Connection: 'keep-alive'
}
})
}
Pattern 3: Interactive Dashboard with Filters
// components/SalesDashboard.tsx
'use client'
import { useState } from 'react'
import { BarChart, Bar, XAxis, YAxis, Tooltip, ResponsiveContainer } from 'recharts'
type Period = '7d' | '30d' | '90d'
type Region = 'all' | 'us' | 'eu' | 'asia'
export default function SalesDashboard() {
const [period, setPeriod] = useState<Period>('30d')
const [region, setRegion] = useState<Region>('all')
const { data, loading } = useSalesData({ period, region })
return (
<div className="space-y-6">
{/* Filters */}
<div className="flex gap-4">
<select
value={period}
onChange={(e) => setPeriod(e.target.value as Period)}
className="px-4 py-2 border rounded"
>
<option value="7d">Last 7 days</option>
<option value="30d">Last 30 days</option>
<option value="90d">Last 90 days</option>
</select>
<select
value={region}
onChange={(e) => setRegion(e.target.value as Region)}
className="px-4 py-2 border rounded"
>
<option value="all">All Regions</option>
<option value="us">United States</option>
<option value="eu">Europe</option>
<option value="asia">Asia</option>
</select>
</div>
{/* Chart */}
{loading ? (
<div>Loading...</div>
) : (
<ResponsiveContainer width="100%" height={400}>
<BarChart data={data}>
<XAxis dataKey="date" />
<YAxis />
<Tooltip />
<Bar dataKey="sales" fill="#8884d8" />
</BarChart>
</ResponsiveContainer>
)}
</div>
)
}
// Custom hook for data fetching
function useSalesData({ period, region }: { period: Period, region: Region }) {
const [data, setData] = useState([])
const [loading, setLoading] = useState(true)
useEffect(() => {
setLoading(true)
fetch(`/api/sales?period=${period}®ion=${region}`)
.then(res => res.json())
.then(data => {
setData(data)
setLoading(false)
})
}, [period, region])
return { data, loading }
}
Chart Types Guide
Line Chart
Best for: Trends over time, continuous data
<LineChart data={data}>
<Line type="monotone" dataKey="value" stroke="#8884d8" />
</LineChart>
Use when:
- Stock prices, temperature, website traffic
- Showing change over time
- Multiple data series comparison
Bar Chart
Best for: Comparing categories
<BarChart data={data}>
<Bar dataKey="value" fill="#8884d8" />
</BarChart>
Use when:
- Sales by product, users by country
- Discrete categories
- Ranking/comparison
Pie/Donut Chart
Best for: Part-to-whole relationships
<PieChart>
<Pie data={data} dataKey="value" nameKey="name" fill="#8884d8" />
</PieChart>
Use when:
- Market share, budget allocation
- Proportions (max 5-7 slices)
- Simple percentages
⚠️ Avoid when:
- Too many categories (> 7)
- Precise comparison needed (use bar chart)
Area Chart
Best for: Volume over time
<AreaChart data={data}>
<Area type="monotone" dataKey="value" fill="#8884d8" />
</AreaChart>
Use when:
- Cumulative totals
- Filled regions show magnitude
- Stacked categories
Scatter Plot
Best for: Correlation between variables
<ScatterChart>
<Scatter data={data} fill="#8884d8" />
</ScatterChart>
Use when:
- Finding correlations
- Outlier detection
- Distribution analysis
Heatmap
Best for: Intensity across two dimensions
// Using D3
const colorScale = d3.scaleSequential(d3.interpolateBlues).domain([0, d3.max(data)])
svg
.selectAll('rect')
.data(data)
.join('rect')
.attr('fill', d => colorScale(d.value))
Use when:
- Time-based patterns (day/hour)
- Geographic intensity
- Matrix data
Responsive Design
Pattern: Mobile-Friendly Charts
'use client'
import { useEffect, useState } from 'react'
import { LineChart, Line, ResponsiveContainer } from 'recharts'
export default function ResponsiveChart({ data }) {
const [isMobile, setIsMobile] = useState(false)
useEffect(() => {
const checkMobile = () => setIsMobile(window.innerWidth < 768)
checkMobile()
window.addEventListener('resize', checkMobile)
return () => window.removeEventListener('resize', checkMobile)
}, [])
return (
<ResponsiveContainer width="100%" height={isMobile ? 200 : 400}>
<LineChart data={data}>
<Line
dataKey="value"
stroke="#8884d8"
strokeWidth={isMobile ? 1 : 2}
/>
</LineChart>
</ResponsiveContainer>
)
}
Color Schemes
Accessible Colors
// colors.ts
export const chartColors = {
// WCAG AA compliant
primary: '#0066CC', // Blue
success: '#007A3D', // Green
warning: '#C87000', // Orange
danger: '#D32F2F', // Red
// Multi-series (colorblind-safe)
series: [
'#0066CC', // Blue
'#CC6600', // Orange
'#7A00CC', // Purple
'#00CC66', // Green
'#CC0066' // Magenta
]
}
Colorblind-Safe Palettes:
// For up to 5 data series
const colorblindSafe = [
'#000000', // Black
'#E69F00', // Orange
'#56B4E9', // Sky Blue
'#009E73', // Green
'#F0E442' // Yellow
]
Data Formatting
Number Formatting
// utils/formatters.ts
export function formatCurrency(value: number): string {
return new Intl.NumberFormat('en-US', {
style: 'currency',
currency: 'USD',
minimumFractionDigits: 0,
maximumFractionDigits: 0,
}).format(value)
}
export function formatPercent(value: number): string {
return new Intl.NumberFormat('en-US', {
style: 'percent',
minimumFractionDigits: 1,
maximumFractionDigits: 1,
}).format(value / 100)
}
export function formatNumber(value: number): string {
if (value >= 1000000) {
return `${(value / 1000000).toFixed(1)}M`
}
if (value >= 1000) {
return `${(value / 1000).toFixed(1)}K`
}
return value.toFixed(0)
}
// Usage in chart
<YAxis tickFormatter={formatCurrency} />
Export Functionality
Export Chart as PNG
'use client'
import html2canvas from 'html2canvas'
export function ExportableChart({ children }) {
const chartRef = useRef<HTMLDivElement>(null)
const exportToPNG = async () => {
if (!chartRef.current) return
const canvas = await html2canvas(chartRef.current)
const link = document.createElement('a')
link.download = 'chart.png'
link.href = canvas.toDataURL()
link.click()
}
return (
<div>
<button onClick={exportToPNG} className="mb-4 px-4 py-2 bg-blue-600 text-white rounded">
Export as PNG
</button>
<div ref={chartRef}>
{children}
</div>
</div>
)
}
Export Data as CSV
export function exportToCSV(data: any[], filename: string) {
const headers = Object.keys(data[0])
const csv = [
headers.join(','),
...data.map(row => headers.map(h => row[h]).join(','))
].join('\n')
const blob = new Blob([csv], { type: 'text/csv' })
const link = document.createElement('a')
link.download = `${filename}.csv`
link.href = URL.createObjectURL(blob)
link.click()
}
// Usage
<button onClick={() => exportToCSV(data, 'sales-data')}>
Export to CSV
</button>
Performance Optimization
Lazy Loading Charts
// Lazy load chart libraries (reduce initial bundle)
import dynamic from 'next/dynamic'
const LineChart = dynamic(
() => import('recharts').then(mod => mod.LineChart),
{ ssr: false }
)
export default function ChartPage() {
return <LineChart data={data} />
}
Virtualization for Large Datasets
import { useVirtualizer } from '@tanstack/react-virtual'
export function LargeDataTable({ data }: { data: any[] }) {
const parentRef = useRef<HTMLDivElement>(null)
const virtualizer = useVirtualizer({
count: data.length,
getScrollElement: () => parentRef.current,
estimateSize: () => 50,
})
return (
<div ref={parentRef} className="h-96 overflow-auto">
<div style={{ height: `${virtualizer.getTotalSize()}px` }}>
{virtualizer.getVirtualItems().map((virtualRow) => (
<div key={virtualRow.index} className="py-2 border-b">
{data[virtualRow.index].name}: {data[virtualRow.index].value}
</div>
))}
</div>
</div>
)
}
Animation Best Practices
Smooth Transitions
<LineChart data={data}>
<Line
type="monotone"
dataKey="value"
stroke="#8884d8"
animationDuration={500}
animationEasing="ease-in-out"
/>
</LineChart>
Disable Animation for Real-Time
// For real-time dashboards, disable animation
<Line
dataKey="value"
isAnimationActive={false}
/>
Common Patterns
Pattern: Drill-Down Chart
'use client'
import { useState } from 'react'
import { BarChart, Bar, XAxis, YAxis } from 'recharts'
export default function DrillDownChart() {
const [level, setLevel] = useState<'year' | 'month' | 'day'>('year')
const [selectedYear, setSelectedYear] = useState<number | null>(null)
const handleBarClick = (data: any) => {
if (level === 'year') {
setSelectedYear(data.year)
setLevel('month')
} else if (level === 'month') {
setLevel('day')
}
}
const goBack = () => {
if (level === 'day') setLevel('month')
else if (level === 'month') {
setLevel('year')
setSelectedYear(null)
}
}
return (
<div>
{level !== 'year' && (
<button onClick={goBack} className="mb-4">← Back</button>
)}
<BarChart data={getData(level, selectedYear)} width={600} height={300}>
<Bar dataKey="value" fill="#8884d8" onClick={handleBarClick} />
<XAxis dataKey="name" />
<YAxis />
</BarChart>
</div>
)
}
When to Use Me
Perfect for:
- Building analytics dashboards
- Creating interactive charts
- Data storytelling
- Real-time monitoring
- Visualizing complex datasets
I'll help you:
- Choose the right chart type
- Implement responsive layouts
- Add interactivity
- Optimize performance
- Ensure accessibility
What I'll Create
📊 Charts and Visualizations
📈 KPI Dashboards
🎨 Custom Color Schemes
📱 Responsive Layouts
⚡ Real-Time Updates
💾 Export Functionality
Let's make your data beautiful and understandable!
Related Skills
Xlsx
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas
Clickhouse Io
ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.
Clickhouse Io
ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.
Analyzing Financial Statements
This skill calculates key financial ratios and metrics from financial statement data for investment analysis
Data Storytelling
Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.
Team Composition Analysis
This skill should be used when the user asks to "plan team structure", "determine hiring needs", "design org chart", "calculate compensation", "plan equity allocation", or requests organizational design and headcount planning for a startup.
Startup Financial Modeling
This skill should be used when the user asks to "create financial projections", "build a financial model", "forecast revenue", "calculate burn rate", "estimate runway", "model cash flow", or requests 3-5 year financial planning for a startup.
Kpi Dashboard Design
Design effective KPI dashboards with metrics selection, visualization best practices, and real-time monitoring patterns. Use when building business dashboards, selecting metrics, or designing data visualization layouts.
Dbt Transformation Patterns
Master dbt (data build tool) for analytics engineering with model organization, testing, documentation, and incremental strategies. Use when building data transformations, creating data models, or implementing analytics engineering best practices.
Startup Metrics Framework
This skill should be used when the user asks about "key startup metrics", "SaaS metrics", "CAC and LTV", "unit economics", "burn multiple", "rule of 40", "marketplace metrics", or requests guidance on tracking and optimizing business performance metrics.
