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kris230980kris230980
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Generated by Spark: Fix all reported errors.
1 parent 8e71b4f commit d820199

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Lines changed: 95 additions & 95 deletions

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‎src/App.tsx‎

Lines changed: 95 additions & 95 deletions
Original file line numberDiff line numberDiff line change
@@ -535,6 +535,101 @@ function App() {
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}
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}, [safeFilterConfig, safeUploadedData, applyAdvancedFilters, calculateStats, setFilterConfig, setUploadedData, setInsights])
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// Generate time-series insights
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const generateTimeSeriesInsights = useCallback((dateColumns: DataColumn[], numericColumns: DataColumn[]): Insight[] => {
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const insights: Insight[] = []
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// Find time series pairs (date + numeric columns)
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dateColumns.forEach(dateCol => {
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if (!dateCol.dateValues || dateCol.dateValues.length === 0) return
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const dateRange = dateCol.stats?.dateRange
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const frequency = dateCol.stats?.frequency
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// Date range insight with format information
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insights.push({
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type: 'temporal',
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title: `${dateCol.name} Date Analysis`,
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description: `Data spans ${dateRange} with ${frequency} frequency. Detected formats: ${dateCol.stats?.formatSummary || 'Various'}`,
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value: dateRange,
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importance: 'high'
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})
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// Frequency pattern insight
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if (frequency !== 'irregular') {
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insights.push({
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type: 'temporal',
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title: 'Data Collection Pattern',
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description: `Regular ${frequency} data collection detected, ideal for trend analysis and forecasting`,
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importance: 'medium'
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})
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}
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// Seasonal analysis for monthly/yearly data
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if (dateCol.dateValues && dateCol.dateValues.filter(d => d !== null).length >= 12 && (frequency === 'monthly' || frequency === 'yearly')) {
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const monthCounts = new Array(12).fill(0)
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dateCol.dateValues.forEach(date => {
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if (date) {
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monthCounts[date.getMonth()]++
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}
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})
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const maxMonth = monthCounts.indexOf(Math.max(...monthCounts))
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const minMonth = monthCounts.indexOf(Math.min(...monthCounts))
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const monthNames = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']
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insights.push({
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type: 'seasonal',
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title: 'Seasonal Patterns',
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description: `Peak activity in ${monthNames[maxMonth]}, lowest in ${monthNames[minMonth]}`,
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importance: 'medium'
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})
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}
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// Combine with numeric data for trend analysis
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numericColumns.forEach(numCol => {
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if (dateCol.values.length === numCol.values.length) {
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// Create time series pairs
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const pairs: Array<{date: Date, value: number}> = []
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for (let i = 0; i < dateCol.dateValues!.length; i++) {
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const date = dateCol.dateValues![i]
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const value = Number(numCol.values[i])
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if (date && !isNaN(value)) {
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pairs.push({ date, value })
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}
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}
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if (pairs.length >= 3) {
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// Sort by date
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pairs.sort((a, b) => a.date.getTime() - b.date.getTime())
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// Calculate trend
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const firstHalf = pairs.slice(0, Math.floor(pairs.length / 2))
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const secondHalf = pairs.slice(Math.floor(pairs.length / 2))
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const firstAvg = firstHalf.reduce((sum, p) => sum + p.value, 0) / firstHalf.length
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const secondAvg = secondHalf.reduce((sum, p) => sum + p.value, 0) / secondHalf.length
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const trendDirection = secondAvg > firstAvg ? 'increasing' : 'decreasing'
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const trendMagnitude = Math.abs((secondAvg - firstAvg) / firstAvg * 100)
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if (trendMagnitude > 5) {
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insights.push({
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type: 'trend',
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title: `${numCol.name} Time Trend`,
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description: `${numCol.name} shows ${trendDirection} trend over time with ${trendMagnitude.toFixed(1)}% change`,
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value: `${trendDirection === 'increasing' ? '+' : '-'}${trendMagnitude.toFixed(1)}%`,
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importance: trendMagnitude > 20 ? 'high' : 'medium'
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})
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}
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}
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}
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})
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})
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return insights
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}, [])
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const analyzeData = useCallback((columns: DataColumn[]): Insight[] => {
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const newInsights: Insight[] = []
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@@ -662,101 +757,6 @@ function App() {
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return newInsights.slice(0, 8) // Limit to 8 insights
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}, [generateTimeSeriesInsights])
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665-
// Generate time-series insights
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const generateTimeSeriesInsights = useCallback((dateColumns: DataColumn[], numericColumns: DataColumn[]): Insight[] => {
667-
const insights: Insight[] = []
668-
669-
// Find time series pairs (date + numeric columns)
670-
dateColumns.forEach(dateCol => {
671-
if (!dateCol.dateValues || dateCol.dateValues.length === 0) return
672-
673-
const dateRange = dateCol.stats?.dateRange
674-
const frequency = dateCol.stats?.frequency
675-
676-
// Date range insight with format information
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insights.push({
678-
type: 'temporal',
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title: `${dateCol.name} Date Analysis`,
680-
description: `Data spans ${dateRange} with ${frequency} frequency. Detected formats: ${dateCol.stats?.formatSummary || 'Various'}`,
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value: dateRange,
682-
importance: 'high'
683-
})
684-
685-
// Frequency pattern insight
686-
if (frequency !== 'irregular') {
687-
insights.push({
688-
type: 'temporal',
689-
title: 'Data Collection Pattern',
690-
description: `Regular ${frequency} data collection detected, ideal for trend analysis and forecasting`,
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importance: 'medium'
692-
})
693-
}
694-
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// Seasonal analysis for monthly/yearly data
696-
if (dateCol.dateValues && dateCol.dateValues.filter(d => d !== null).length >= 12 && (frequency === 'monthly' || frequency === 'yearly')) {
697-
const monthCounts = new Array(12).fill(0)
698-
dateCol.dateValues.forEach(date => {
699-
if (date) {
700-
monthCounts[date.getMonth()]++
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}
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})
703-
704-
const maxMonth = monthCounts.indexOf(Math.max(...monthCounts))
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const minMonth = monthCounts.indexOf(Math.min(...monthCounts))
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const monthNames = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']
707-
708-
insights.push({
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type: 'seasonal',
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title: 'Seasonal Patterns',
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description: `Peak activity in ${monthNames[maxMonth]}, lowest in ${monthNames[minMonth]}`,
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importance: 'medium'
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})
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}
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// Combine with numeric data for trend analysis
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numericColumns.forEach(numCol => {
718-
if (dateCol.values.length === numCol.values.length) {
719-
// Create time series pairs
720-
const pairs: Array<{date: Date, value: number}> = []
721-
for (let i = 0; i < dateCol.dateValues!.length; i++) {
722-
const date = dateCol.dateValues![i]
723-
const value = Number(numCol.values[i])
724-
if (date && !isNaN(value)) {
725-
pairs.push({ date, value })
726-
}
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}
728-
729-
if (pairs.length >= 3) {
730-
// Sort by date
731-
pairs.sort((a, b) => a.date.getTime() - b.date.getTime())
732-
733-
// Calculate trend
734-
const firstHalf = pairs.slice(0, Math.floor(pairs.length / 2))
735-
const secondHalf = pairs.slice(Math.floor(pairs.length / 2))
736-
737-
const firstAvg = firstHalf.reduce((sum, p) => sum + p.value, 0) / firstHalf.length
738-
const secondAvg = secondHalf.reduce((sum, p) => sum + p.value, 0) / secondHalf.length
739-
740-
const trendDirection = secondAvg > firstAvg ? 'increasing' : 'decreasing'
741-
const trendMagnitude = Math.abs((secondAvg - firstAvg) / firstAvg * 100)
742-
743-
if (trendMagnitude > 5) {
744-
insights.push({
745-
type: 'trend',
746-
title: `${numCol.name} Time Trend`,
747-
description: `${numCol.name} shows ${trendDirection} trend over time with ${trendMagnitude.toFixed(1)}% change`,
748-
value: `${trendDirection === 'increasing' ? '+' : '-'}${trendMagnitude.toFixed(1)}%`,
749-
importance: trendMagnitude > 20 ? 'high' : 'medium'
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})
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}
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}
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}
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})
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})
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757-
return insights
758-
}, [])
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// Clear all filters
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const clearAllFilters = useCallback(() => {
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setFilterConfig({})

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