{formatNumber(column.d3format, sparkData[index])}
{formatTime(
column.dateFormat,
moment.utc(entries[index].time).toDate(),
)}
)}
/>
);
}
renderValueCell(valueField, column, reversedEntries) {
const recent = reversedEntries[0][valueField];
let v;
let errorMsg;
if (column.colType === 'time') {
// Time lag ratio
const timeLag = column.timeLag || 0;
const totalLag = Object.keys(reversedEntries).length;
if (timeLag >= totalLag) {
errorMsg = `The time lag set at ${timeLag} is too large for the length of data at ${reversedEntries.length}. No data available.`;
} else {
v = reversedEntries[timeLag][valueField];
}
if (column.comparisonType === 'diff') {
v = recent - v;
} else if (column.comparisonType === 'perc') {
v = recent / v;
} else if (column.comparisonType === 'perc_change') {
v = recent / v - 1;
}
v = v || 0;
} else if (column.colType === 'contrib') {
// contribution to column total
v =
recent /
Object.keys(reversedEntries[0])
.map(k => (k !== 'time' ? reversedEntries[0][k] : null))
.reduce((a, b) => a + b);
} else if (column.colType === 'avg') {
// Average over the last {timeLag}
v =
reversedEntries
.map((k, i) => (i < column.timeLag ? k[valueField] : 0))
.reduce((a, b) => a + b) / column.timeLag;
}
const color = colorFromBounds(v, column.bounds);
return (