2c:null 2d:["$","title",null,{"children":"Israel Fatalities 2000-2023 | Evgeny Zislis | Observable"}] 32:T664,Dots represent deaths by day, solid line is the moving average and black text towards the end of each month is the aggregation of total deaths from the beginning of the year up to the end of that month. The light gray line starting the fifth year represents the five year average for the same period of last five years. This is an average of the moving average for the previous five years and not a week-by-week comparison. This can help with seeing if a certain period has "Excess Mortality" compared to the average of the last several years. This is further explained on the [OurWorldInData website](https://ourworldindata.org/excess-mortality-covid).

כל נקודה מסמנת את מספר המתים באותו יום, והקו הצבעוני זה ממוצע נע לפי כמות הימים שנבחרו. המספר השחור בסוף כל חודש זה כמות המתים סה"כ מתחילת השנה עד לסוף אותו חודש. המספר האפור מתחת זה כמות המתים שנוספו עד לסוף אותו חודש.

הקו האפור החל מהשנה החמישית מראה את הממוצע של אותו יום לפי החמש השנים שקדמו לאותה שנה. זה מעיד על "תמותה עודפת" ע"י השוואה של השנה הנוכחית למה שבד"כ קורה באותו זמן בשנים בעבר. בלי לקחת בחשבון גידול באוכלוסיה. מידע נוסף על הקו אפשר למצוא באתר [OurWorldInData](https://ourworldindata.org/excess-mortality-covid).

33:T4bb,viewof N = { const options = [ 'Total','Male','Female','Jews Total','Jews Male','Jews Female','Arabs Total','Arabs Male','Arabs Female','0-19','20-24','25-29','30-34','35-39','40-44','45-49','50-54','55-59','60-64','65-69','70-74','75-79','80-84','85-89','90+' ]; const form = html` `; const value = {} form.i.oninput = () => form.value = { ...form.value, i: form.i.valueAsNumber }; form.i.oninput(); form.segment.oninput = () => form.value = { ...form.value, segment: form.segment.value }; form.segment.oninput(); return form; }34:T91a,vegalite({ data: { values: data_DailyDeaths }, facet: { row: { field: "Year" } }, spec: { width: 860, height: 200, layer: [ /* prior five years average - gray line */ { mark: { type: "line", size: 1, color: "rgba(180,180,180,0.75)" }, encoding: { x: { field: "Date", timeUnit: "monthdate" }, y: { field: "FiveYearAverage", type: "quantitative" } } }, /* per-day circles representing the numbers that day */ { mark: { type: "circle", size: 10 }, encoding: { color: { field: "Year", type: "nominal", legend: false }, x: { field: "Date", timeUnit: "monthdate" }, y: { field: "segment_Total", title: "Deaths", type: "quantitative" } } }, /* weekly error bands */ { mark: { type: "errorband", extent: "iqr", interpolate: "basis-open" }, encoding: { y: { field: "segment_Total", type: "quantitative", title: "" }, x: { field: "Date", timeUnit: "week", title: "" }, color: { field: "Year", type: "nominal", legend: false } } }, /* moving average line */ { mark: { type: "line", size: 3 }, encoding: { color: { field: "Year", type: "nominal", legend: false }, x: { field: "Date", timeUnit: "monthdate" }, y: { field: "ma_Total", type: "quantitative" } } }, /* cumulative since year start */ { mark: { type: "text", fontSize: 15, font: "monospace", baseline: 'top', fontWeight: 'bold', dx: 70, align: 'right', }, encoding: { text: { field: "agg_Total", aggregate: "max" }, x: { field: "Date", timeUnit: "month" }, y: { value: 155 } } }, /* per-month addition for each month */ { mark: { type: "text", fontSize: 12, font: "monospace", fontStyle: "italic", baseline: 'top', dx: 70, align: 'right', color: "#666666" }, encoding: { text: { field: "agg_Month", aggregate: "max", format: "+" }, x: { field: "Date", timeUnit: "month" }, y: { value: 170 } } } ] } })35:T6b2,data_DailyDeaths = { let yearTotal = 0 let monthTotal = 0 let firstYear = 0 const segment = N['segment'] const duration = N['i'] // get data from attached CSV file const bySectorAndAge = d3.csvParse( await FileAttachment("p-1@15.csv").text() ) // parse Date and add Year field .map(d => { const eventDate = new Date(d3.timeFormat('%Y-%m-%d')(d3.timeParse('%m/%d/%Y')(d.Date))) return { ...d, Year: eventDate.getFullYear(), segment_Total: parseInt(d[segment]), Date: eventDate } }) // sort by Date (its already sorted, just make sure) .sort( (a,b) => a.Date - b.Date ) // generate an array of moving averages const ma_Total = movingWindowAvg(bySectorAndAge.map(d => d[segment]), duration) // enrich data with aggregate of Total and with the moving average for each day return bySectorAndAge.map((d,idx) => { if (idx > 1 && d.Year != bySectorAndAge[idx-1].Year) yearTotal = 0 if (idx > 1 && d.Date.getDate() == 1) monthTotal = 0 if (!firstYear) firstYear = d.Year if (d.Year >= firstYear + 5) { d.FiveYearAverage = 1.0 * [1,2,3,4,5].reduce( (acc,yearAgo) => { const previous = ma_Total[idx - (yearAgo * 365)] if (previous > 0) return acc + previous return 0 // return acc + ma_Total[idx - (yearAgo*365)] }, 0) / 5.0 /* fix fifth year going way off scale and messing all scales */ if (d.FiveYearAverage > 700) { d.FiveYearAverage = ma_Total[idx] } } monthTotal += d.segment_Total yearTotal += d.segment_Total const agg_Total = yearTotal const agg_Month = monthTotal return { agg_Total, ma_Total: ma_Total[idx], agg_Month, ...d } }) 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מבוסס על הנתונים של מוות ותוכלת חיים שפורסמו ע\" הלשכה המרכזית לסטטיסטיקה (למ\"ס).

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