Built with blockbuilder.org
Data is a subset of the gapminder data from here: https://bost.ocks.org/mike/nations/
license: mit |
Built with blockbuilder.org
Data is a subset of the gapminder data from here: https://bost.ocks.org/mike/nations/
country | year | population | gdp | lifeexp | |
---|---|---|---|---|---|
India | 1950 | 359000000 | 580 | 36.8 | |
India | 1951 | 365000000 | 583 | 37.08 | |
India | 1952 | 372000000 | 588 | 37.65 | |
India | 1953 | 379000000 | 613 | 38.22 | |
India | 1954 | 386000000 | 626 | 38.8 | |
India | 1955 | 393000000 | 629 | 39.39 | |
India | 1956 | 401000000 | 651 | 39.98 | |
India | 1957 | 409000000 | 631 | 40.59 | |
India | 1958 | 418000000 | 663 | 41.19 | |
India | 1959 | 426000000 | 664 | 41.81 | |
India | 1960 | 434000000 | 696 | 42.44 | |
India | 1961 | 444000000 | 700 | 43.07 | |
India | 1962 | 454000000 | 699 | 43.71 | |
India | 1963 | 464000000 | 717 | 44.35 | |
India | 1964 | 474000000 | 755 | 45 | |
India | 1965 | 485000000 | 707 | 45.65 | |
India | 1966 | 495000000 | 698 | 46.3 | |
India | 1967 | 506000000 | 739 | 46.94 | |
India | 1968 | 518000000 | 739 | 47.57 | |
India | 1969 | 529000000 | 771 | 48.19 | |
India | 1970 | 541000000 | 791 | 48.82 | |
India | 1971 | 554000000 | 779 | 49.47 | |
India | 1972 | 567000000 | 758 | 50.14 | |
India | 1973 | 580000000 | 774 | 50.83 | |
India | 1974 | 593000000 | 764 | 51.54 | |
India | 1975 | 607000000 | 812 | 52.24 | |
India | 1976 | 620000000 | 804 | 52.92 | |
India | 1977 | 634000000 | 845 | 53.55 | |
India | 1978 | 648000000 | 870 | 54.13 | |
India | 1979 | 664000000 | 806 | 54.65 | |
India | 1980 | 679000000 | 844 | 55.11 | |
India | 1981 | 692000000 | 877 | 55.51 | |
India | 1982 | 708000000 | 883 | 55.88 | |
India | 1983 | 723000000 | 933 | 56.22 | |
India | 1984 | 739000000 | 947 | 56.55 | |
India | 1985 | 755000000 | 963 | 56.86 | |
India | 1986 | 771000000 | 982 | 57.16 | |
India | 1987 | 788000000 | 1001 | 57.44 | |
India | 1988 | 805000000 | 1081 | 57.7 | |
India | 1989 | 822000000 | 1127 | 57.95 | |
India | 1990 | 839000000 | 1160 | 58.2 | |
India | 1991 | 856000000 | 1150 | 58.45 | |
India | 1992 | 872000000 | 1186 | 58.72 | |
India | 1993 | 891000000 | 1227 | 59 | |
India | 1994 | 908000000 | 1290 | 59.3 | |
India | 1995 | 927000000 | 1354 | 59.62 | |
India | 1996 | 943000000 | 1433 | 59.95 | |
India | 1997 | 959000000 | 1475 | 60.28 | |
India | 1998 | 975000000 | 1543 | 60.61 | |
India | 1999 | 991691000 | 1607 | 60.94 | |
India | 2000 | 1007702000 | 1648 | 61.26 | |
India | 2001 | 1023590000 | 1714 | 61.56 | |
India | 2002 | 1034172547 | 1754 | 61.86 | |
India | 2003 | 1049700118 | 1872 | 62.15 | |
India | 2004 | 1065070607 | 1981 | 62.45 | |
India | 2005 | 1080264388 | 2126 | 62.74 | |
India | 2006 | 1095351995 | 2300 | 63.04 | |
India | 2007 | 1110396331 | 2478 | 63.35 | |
India | 2008 | 1125368288 | 2622 | 63.68 | |
United States | 1950 | 152271000 | 15855.86 | 68.12 | |
United States | 1951 | 154878000 | 16750.74 | 68.22 | |
United States | 1952 | 157553000 | 17039.38 | 68.44 | |
United States | 1953 | 160184000 | 17471.28 | 68.79 | |
United States | 1954 | 163026000 | 16979.26 | 69.58 | |
United States | 1955 | 165931000 | 17822.45 | 69.63 | |
United States | 1956 | 168903000 | 17783.27 | 69.71 | |
United States | 1957 | 171984000 | 17749.5 | 69.49 | |
United States | 1958 | 174882000 | 17217.39 | 69.76 | |
United States | 1959 | 177830000 | 18084.11 | 69.98 | |
United States | 1960 | 180671000 | 18175.43 | 69.91 | |
United States | 1961 | 183691000 | 18226.62 | 70.32 | |
United States | 1962 | 186538000 | 18978.45 | 70.21 | |
United States | 1963 | 189242000 | 19461.1 | 70.04 | |
United States | 1964 | 191889000 | 20243.98 | 70.33 | |
United States | 1965 | 194303000 | 21209.93 | 70.41 | |
United States | 1966 | 196560000 | 22263.22 | 70.43 | |
United States | 1967 | 198712000 | 22495.68 | 70.76 | |
United States | 1968 | 200706000 | 23268.21 | 70.42 | |
United States | 1969 | 202677000 | 23669.41 | 70.66 | |
United States | 1970 | 205052000 | 23345.77 | 70.92 | |
United States | 1971 | 207661000 | 23744.67 | 71.24 | |
United States | 1972 | 209896000 | 24654.04 | 71.34 | |
United States | 1973 | 211909000 | 25742 | 71.54 | |
United States | 1974 | 213854000 | 25281.7 | 72.08 | |
United States | 1975 | 215973000 | 24889.6 | 72.68 | |
United States | 1976 | 218035000 | 25881.72 | 72.99 | |
United States | 1977 | 220239000 | 26715.14 | 73.38 | |
United States | 1978 | 222585000 | 27814.18 | 73.58 | |
United States | 1979 | 225055000 | 28278.91 | 74.03 | |
United States | 1980 | 227726463 | 27838.11 | 73.93 | |
United States | 1981 | 229966237 | 28160.14 | 74.36 | |
United States | 1982 | 232187835 | 27243.47 | 74.65 | |
United States | 1983 | 234307207 | 28119.69 | 74.71 | |
United States | 1984 | 236348292 | 29785.25 | 74.82 | |
United States | 1985 | 238466283 | 30636.21 | 74.79 | |
United States | 1986 | 240650755 | 31297.31 | 74.87 | |
United States | 1987 | 242803533 | 31953.81 | 75.01 | |
United States | 1988 | 245021414 | 32860.52 | 75.03 | |
United States | 1989 | 247341697 | 33587.09 | 75.31 | |
United States | 1990 | 250131894 | 33710.39 | 75.6 | |
United States | 1991 | 253492503 | 33076.87 | 75.8 | |
United States | 1992 | 256894189 | 33589.59 | 76.08 | |
United States | 1993 | 260255352 | 33914.89 | 75.83 | |
United States | 1994 | 263435673 | 34730.56 | 76 | |
United States | 1995 | 266557091 | 35053.29 | 76.09 | |
United States | 1996 | 269667391 | 35807 | 76.44 | |
United States | 1997 | 272911760 | 36847.81 | 76.8 | |
United States | 1998 | 276115288 | 37811.68 | 76.97 | |
United States | 1999 | 279294713 | 38912.58 | 76.97 | |
United States | 2000 | 282338631 | 39758.5 | 77.13 | |
United States | 2001 | 285023886 | 39474.11 | 77.25 | |
United States | 2002 | 287675526 | 39535.84 | 77.31 | |
United States | 2003 | 290342554 | 40044.18 | 77.49 | |
United States | 2004 | 293027571 | 40956.4 | 77.92 | |
United States | 2005 | 295734134 | 41674 | 77.93 | |
United States | 2006 | 298444215 | 42385.18 | 78.21 | |
United States | 2007 | 301139947 | 42866.22 | 79.09 | |
United States | 2008 | 303824646 | 42656.49 | 79.27 | |
China | 1950 | 546815000 | 394.49 | 39.25 | |
China | 1951 | 557480000 | 432.35 | 39.64 | |
China | 1952 | 568910000 | 473.38 | 40.41 | |
China | 1953 | 581390000 | 486.2 | 44.56 | |
China | 1954 | 595310000 | 490.39 | 46.47 | |
China | 1955 | 608655000 | 507.64 | 48.02 | |
China | 1956 | 621465000 | 542.5 | 50.45 | |
China | 1957 | 637408000 | 560 | 50.55 | |
China | 1958 | 653235000 | 607.89 | 50.16 | |
China | 1959 | 666005000 | 604.38 | 38.4 | |
China | 1960 | 667070000 | 583.02 | 31.63 | |
China | 1961 | 660330000 | 486.83 | 34.1 | |
China | 1962 | 665770000 | 484.67 | 44.5 | |
China | 1963 | 682335000 | 519.76 | 51.9 | |
China | 1964 | 698355000 | 567.77 | 53.32 | |
China | 1965 | 715185000 | 617.76 | 55.65 | |
China | 1966 | 735400000 | 657.14 | 56.8 | |
China | 1967 | 754550000 | 622.45 | 58.38 | |
China | 1968 | 774510000 | 594.27 | 59.41 | |
China | 1969 | 796025000 | 627.78 | 60.97 | |
China | 1970 | 818315000 | 685.35 | 62.65 | |
China | 1971 | 841105000 | 699.98 | 63.74 | |
China | 1972 | 862030000 | 702.94 | 63.12 | |
China | 1973 | 881940000 | 738.22 | 62.78 | |
China | 1974 | 900350000 | 735.36 | 62.5 | |
China | 1975 | 916395000 | 767.09 | 62.7 | |
China | 1976 | 930685000 | 750.79 | 62.44 | |
China | 1977 | 943455000 | 786.85 | 63.97 | |
China | 1978 | 956165000 | 861.1 | 64.24 | |
China | 1979 | 969005000 | 915.22 | 65.09 | |
China | 1980 | 981235000 | 934.27 | 66.12 | |
China | 1981 | 993861000 | 977.54 | 66.45 | |
China | 1982 | 1000281000 | 1044.34 | 66.37 | |
China | 1983 | 1023288000 | 1107.46 | 66.54 | |
China | 1984 | 1036825000 | 1229.08 | 66.71 | |
China | 1985 | 1051040000 | 1337.64 | 66.89 | |
China | 1986 | 1066790000 | 1406.19 | 67.08 | |
China | 1987 | 1084035000 | 1529.5 | 67.29 | |
China | 1988 | 1101630000 | 1611.38 | 67.52 | |
China | 1989 | 1118650000 | 1615.03 | 67.77 | |
China | 1990 | 1135185000 | 1647.38 | 68.04 | |
China | 1991 | 1150780000 | 1732.13 | 68.33 | |
China | 1992 | 1164970000 | 1877.41 | 68.64 | |
China | 1993 | 1178440000 | 2035.59 | 68.95 | |
China | 1994 | 1191835000 | 2214.2 | 69.27 | |
China | 1995 | 1204855000 | 2521.34 | 69.6 | |
China | 1996 | 1217550000 | 2546.44 | 69.94 | |
China | 1997 | 1230075000 | 2653.3 | 70.28 | |
China | 1998 | 1241935000 | 2635.55 | 70.62 | |
China | 1999 | 1252735000 | 2784.39 | 70.96 | |
China | 2000 | 1262645000 | 3012.12 | 71.29 | |
China | 2001 | 1271850000 | 3309.8 | 71.59 | |
China | 2002 | 1280400000 | 3695.65 | 71.87 | |
China | 2003 | 1288400000 | 4228.98 | 72.13 | |
China | 2004 | 1295733978 | 4551.13 | 72.35 | |
China | 2005 | 1303182268 | 4909.2 | 72.56 | |
China | 2006 | 1310823807 | 5450.12 | 72.74 | |
China | 2007 | 1318683096 | 6127.78 | 72.92 | |
China | 2008 | 1326856173 | 6679.2 | 73.1 |
<!DOCTYPE html> | |
<head> | |
<meta charset="utf-8"> | |
<script src="https://d3js.org/d3.v4.min.js"></script> | |
<style> | |
body { margin:0;position:fixed;top:0;right:0;bottom:0;left:0; } | |
</style> | |
</head> | |
<body> | |
<script> | |
// Feel free to change or delete any of the code you see in this editor! | |
var svg = d3.select("body") | |
.append("svg") | |
.attr("width", 960) | |
.attr("height", 500); | |
d3.csv("gapminder_time_subset.csv",function(dataWeLoaded) { | |
var xScale = d3.scaleLinear() | |
.domain([0,40000]) | |
.range([100,800]); | |
var xScaleTime = d3.scaleLinear() | |
.domain([1950,2010]) | |
.range([100,800]); | |
var yScale = d3.scaleLinear() | |
.domain([30,80]) | |
.range([400,100]); | |
var rScale = d3.scaleSqrt() | |
.domain([0,d3.max(dataWeLoaded, function(d) { return +d.population;})]) | |
.range([0,100]); | |
var colorScale = d3.scaleOrdinal(d3.schemeCategory10); | |
var chinaData = dataWeLoaded.filter(function(d) { return d.country == 'China';}); | |
var indiaData = dataWeLoaded.filter(function(d) { return d.country == 'India';}); | |
var usData = dataWeLoaded.filter(function(d) { return d.country == 'United States';}); | |
var data = [{ | |
id: 'China', | |
values: chinaData | |
},{ | |
id: 'India', | |
values: indiaData | |
},{ | |
id: 'United States', | |
values: usData | |
}]; | |
// Create a line generator | |
var line = d3.line() | |
.x(function(d) { return xScaleTime(+d.year);}) | |
.y(function(d) { return yScale(+d.lifeexp);}) | |
svg.selectAll("path") | |
.data(data) | |
.enter() | |
.append("path") | |
.attr("fill", "none") | |
.attr("stroke", function(d) { return colorScale(d.id);}) | |
.attr("stroke-linejoin", "round") | |
.attr("stroke-linecap", "round") | |
.attr("stroke-width", 1.5) | |
.attr("d", function(d) { return line(d.values);}); | |
svg.selectAll("text") | |
.data(data) | |
.enter() | |
.append("text") | |
.text(function(d) { return d.id; }) | |
.attr("font-size",10) | |
.attr("font-family","sans-serif") | |
.attr("transform", function(d) { return "translate(780," + yScale(+d.values.slice(-1)[0].lifeexp) + ")";}) | |
/* | |
// Alternate method to add one path at a time: | |
svg.append("path") | |
.datum(chinaData) | |
.attr("fill", "none") | |
.attr("stroke", function(d) { return colorScale(d.country);}) | |
.attr("stroke-linejoin", "round") | |
.attr("stroke-linecap", "round") | |
.attr("stroke-width", 1.5) | |
.attr("d", line); | |
*/ | |
var leftAxis = d3.axisLeft(yScale); | |
var bottomAxis = d3.axisBottom(xScaleTime) | |
.tickFormat(d3.format("d")); | |
svg.append("g") | |
.attr("transform", "translate(100,0)") | |
.call(leftAxis); | |
svg.append("g") | |
.attr("transform", "translate(0,400)") | |
.call(bottomAxis); | |
svg.append("text") | |
.text("life expectancy") | |
.attr("transform", "translate(60,90)") | |
.attr("font-size",10) | |
.attr("font-family","sans-serif") | |
svg.append("text") | |
.text("year") | |
.attr("transform", "translate(770,430)") | |
.attr("font-size",10) | |
.attr("font-family","sans-serif") | |
}) | |
</script> | |
</body> |