从文本 jquery 中查找和挑选出模式

。 还不错。 这有点复杂，但是通过键解析数据可以通过javascript完成。 当然，从存储的任何数据库中获取数据服务器端后，格式化数据服务器端会更易于维护，但此解决方案可以工作。

var raw_data = { "data": [ { "Output in top 10 percentiles (%)": "CNRS", "Overall": "22,6", "1996": "18,4", "1997": "18,6", "1998": "18,5", "1999": "17,3", "2000": "17,6", "2001": "18,6", "2002": "18,3", "2003": "17,5", "2004": "18,9", "2005": "20,2", "2006": "21,1", "2007": "22,1", "2008": "21,3", "2009": "22,9", "2010": "23,4", "2011": "25,3", "2012": "24,5", "2013": "29,3", "2014": "31,7" }, { "Output in top 10 percentiles (%)": "DACH - Austria, Germany and Switzerland", "Overall": "16,9", "1996": "13,3", "1997": "13,4", "1998": "13,6", "1999": "14,1", "2000": 14, "2001": "14,8", "2002": "15,1", "2003": "14,9", "2004": "15,5", "2005": "15,5", "2006": "15,8", "2007": "16,2", "2008": "16,1", "2009": "16,4", "2010": "17,6", "2011": "18,6", "2012": "18,4", "2013": "21,7", "2014": "25,1" }, { "Output in top 10 percentiles (%)": "Europe", "Overall": "13,5", "1996": "11,2", "1997": "11,2", "1998": "11,3", "1999": "11,5", "2000": "11,5", "2001": "12,2", "2002": "12,3", "2003": "12,2", "2004": "12,5", "2005": "12,6", "2006": "12,8", "2007": 13, "2008": "12,6", "2009": "12,8", "2010": "13,4", "2011": "14,1", "2012": "13,7", "2013": "16,5", "2014": "21,4" }, { "Output in top 10 percentiles (%)": "J. Stefan Institute", "Overall": "13,3", "1996": "6,5", "1997": 8, "1998": "8,9", "1999": "9,7", "2000": 8, "2001": "10,6", "2002": 7, "2003": "8,2", "2004": 12, "2005": "9,5", "2006": "10,6", "2007": "13,4", "2008": "11,9", "2009": "12,8", "2010": "14,9", "2011": "15,5", "2012": "15,2", "2013": "19,7", "2014": "25,6" } ] };
// create the object to store the values.  If you know associative
// arrays, this is the same concept.  We're creating keys that store
// each of the values.  This way we can keep referencing the same 
// property (e.g. 1998) and append each value wherever it should go.
var formatted_data = {};
// loop over the raw data
for(var i in raw_data.data) {
  // here we are grabbing all the keys for this row. (e.g. 1996, 1997,
  // and even "Output in top 10 percentiles (%)")
  var keys = Object.keys(raw_data.data[i]);
  // loop over all the keys
  for(var k = 0, len = keys.length; k < len; k++) {
    // First check to see if our key (1996 or whatever) is already in
    // the formatted_data variable.  If it is, append to it.  If it
    // isn't, we need to create it.
    if(typeof formatted_data[keys[k]] !== "undefined") {
      // it exists!  Tack on the value now.
      formatted_data[keys[k]].push(raw_data.data[i][keys[k]]);
    } else {
      // it doesn't exist, create a new one and instantiate an array
      // with one entry: the value.
      formatted_data[keys[k]] = new Array(raw_data.data[i][keys[k]])
    }
  }
}
// output for debugging
console.log(formatted_data);

<strong>See javascript console for output</strong>

尝试

// return object of year values as property of year
var yearData = $.map(data,function(value) {
  return $.map(value, function(years) {
    return Object.keys(years).filter(Number)
    .map(function(data) {
      var year = {};
      year[data] = years[data];
      return year
    })
  })
});
$("#graphcontainer").text(JSON.stringify(yearData, null, 2));
// filter year data
var filtered = function(year) {
  return [].slice.call(yearData).filter(function(years) {
    return Number(Object.keys(years)[0]) === year
  })
};
var year = filtered(1996);

var data = data = { "data": [ { "Output in top 10 percentiles (%)": "CNRS", "Overall": "22,6", "1996": "18,4", "1997": "18,6", "1998": "18,5", "1999": "17,3", "2000": "17,6", "2001": "18,6", "2002": "18,3", "2003": "17,5", "2004": "18,9", "2005": "20,2", "2006": "21,1", "2007": "22,1", "2008": "21,3", "2009": "22,9", "2010": "23,4", "2011": "25,3", "2012": "24,5", "2013": "29,3", "2014": "31,7" }, { "Output in top 10 percentiles (%)": "DACH - Austria, Germany and Switzerland", "Overall": "16,9", "1996": "13,3", "1997": "13,4", "1998": "13,6", "1999": "14,1", "2000": 14, "2001": "14,8", "2002": "15,1", "2003": "14,9", "2004": "15,5", "2005": "15,5", "2006": "15,8", "2007": "16,2", "2008": "16,1", "2009": "16,4", "2010": "17,6", "2011": "18,6", "2012": "18,4", "2013": "21,7", "2014": "25,1" }, { "Output in top 10 percentiles (%)": "Europe", "Overall": "13,5", "1996": "11,2", "1997": "11,2", "1998": "11,3", "1999": "11,5", "2000": "11,5", "2001": "12,2", "2002": "12,3", "2003": "12,2", "2004": "12,5", "2005": "12,6", "2006": "12,8", "2007": 13, "2008": "12,6", "2009": "12,8", "2010": "13,4", "2011": "14,1", "2012": "13,7", "2013": "16,5", "2014": "21,4" }, { "Output in top 10 percentiles (%)": "J. Stefan Institute", "Overall": "13,3", "1996": "6,5", "1997": 8, "1998": "8,9", "1999": "9,7", "2000": 8, "2001": "10,6", "2002": 7, "2003": "8,2", "2004": 12, "2005": "9,5", "2006": "10,6", "2007": "13,4", "2008": "11,9", "2009": "12,8", "2010": "14,9", "2011": "15,5", "2012": "15,2", "2013": "19,7", "2014": "25,6" } ] };
var yearData = $.map(data,function(value) {
  return $.map(value, function(years) {
    return Object.keys(years).filter(Number)
    .map(function(data) {
      var year = {};
      year[data] = years[data];
      return year
    })
  })
});
$("#graphcontainer").text(JSON.stringify(yearData, null, 2));

<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.11.1/jquery.min.js"></script>
<pre id="graphcontainer"></pre>

您可以使用 JavaScript 的映射和过滤方法将数据列与解析的 JSON 结构隔离开来。

下面是获取二维数组第三列的 .map 示例：

// 2D array
var arr2d = [[1, 2, 3], [4, 5, 6],[7, 8, 9]];
// get the third column
var col3 = arr2d.map(
    function(value, index) {
        return value[2];  // 2 is index of third column
    }
);
// col3 is now [3, 6, 9]

在您的情况下，这应该是获取数组中返回的所有 1996 值的方法：

// provide your JSON in variable parserOutput
// get the column of year 1996
var col1996 = parserOutput.data.map(
    function(value, index) {
        return value["1996"];  // dot notation would be possible here, if key wasn't a number
    }
);
// col1996 is now ["18,4", "13,3", "11,2", "6,5"]

更新：

包含示例数据的代码片段：

// provide your JSON in variable parserOutput
var parserOutput = { 
  "data": [ 
    { "Output in top 10 percentiles (%)": "CNRS", "Overall": "22,6", "1996": "18,4", "1997": "18,6", "1998": "18,5", "1999": "17,3", "2000": "17,6", "2001": "18,6", "2002": "18,3", "2003": "17,5", "2004": "18,9", "2005": "20,2", "2006": "21,1", "2007": "22,1", "2008": "21,3", "2009": "22,9", "2010": "23,4", "2011": "25,3", "2012": "24,5", "2013": "29,3", "2014": "31,7" }, 
    { "Output in top 10 percentiles (%)": "DACH - Austria, Germany and Switzerland", "Overall": "16,9", "1996": "13,3", "1997": "13,4", "1998": "13,6", "1999": "14,1", "2000": 14, "2001": "14,8", "2002": "15,1", "2003": "14,9", "2004": "15,5", "2005": "15,5", "2006": "15,8", "2007": "16,2", "2008": "16,1", "2009": "16,4", "2010": "17,6", "2011": "18,6", "2012": "18,4", "2013": "21,7", "2014": "25,1" }, 
    { "Output in top 10 percentiles (%)": "Europe", "Overall": "13,5", "1996": "11,2", "1997": "11,2", "1998": "11,3", "1999": "11,5", "2000": "11,5", "2001": "12,2", "2002": "12,3", "2003": "12,2", "2004": "12,5", "2005": "12,6", "2006": "12,8", "2007": 13, "2008": "12,6", "2009": "12,8", "2010": "13,4", "2011": "14,1", "2012": "13,7", "2013": "16,5", "2014": "21,4" }, 
    { "Output in top 10 percentiles (%)": "J. Stefan Institute", "Overall": "13,3", "1996": "6,5", "1997": 8, "1998": "8,9", "1999": "9,7", "2000": 8, "2001": "10,6", "2002": 7, "2003": "8,2", "2004": 12, "2005": "9,5", "2006": "10,6", "2007": "13,4", "2008": "11,9", "2009": "12,8", "2010": "14,9", "2011": "15,5", "2012": "15,2", "2013": "19,7", "2014": "25,6" }, 
    { "Output in top 10 percentiles (%)": "Max Planck Society", "Overall": "30,3", "1996": "25,9", "1997": 24, "1998": "24,3", "1999": 25, "2000": "25,6", "2001": 27, "2002": "26,2", "2003": "27,6", "2004": "27,8", "2005": "27,8", "2006": "28,1", "2007": "29,4", "2008": "29,2", "2009": "30,9", "2010": "32,4", "2011": "33,2", "2012": "34,8", "2013": "39,8", "2014": "38,9" }, 
    { "Output in top 10 percentiles (%)": "National Institute of Biology Ljubljana", "Overall": "17,7", "1996": 4, "1997": "13,3", "1998": 20, "1999": "13,3", "2000": "9,1", "2001": 15, "2002": "15,6", "2003": "20,8", "2004": "18,2", "2005": "14,7", "2006": "14,3", "2007": 18, "2008": "19,7", "2009": 20, "2010": "21,1", "2011": "16,7", "2012": "18,2", "2013": 19, "2014": "24,1" }, 
    { "Output in top 10 percentiles (%)": "National Institute of Chemistry Ljubljana", "Overall": "21,5", "1996": "8,8", "1997": "4,1", "1998": "9,9", "1999": 15, "2000": "15,7", "2001": "21,4", "2002": "15,3", "2003": "18,4", "2004": "16,2", "2005": "20,4", "2006": "19,4", "2007": "30,8", "2008": "18,1", "2009": "19,4", "2010": "31,8", "2011": "23,1", "2012": "24,9", "2013": "29,3", "2014": 36 }, 
    { "Output in top 10 percentiles (%)": "Scientific Research Centre of the Slovenian Academy of Sciences and Arts", "Overall": "5,9", "1996": 0, "1997": 0, "1998": 0, "1999": 0, "2000": 0, "2001": "NA", "2002": 0, "2003": 0, "2004": "14,3", "2005": "4,5", "2006": 0, "2007": 0, "2008": 0, "2009": "7,8", "2010": "2,4", "2011": "6,8", "2012": "4,8", "2013": 0, "2014": 30 }, 
    { "Output in top 10 percentiles (%)": "Slovenia", "Overall": "10,7", "1996": "5,8", "1997": "5,7", "1998": "5,7", "1999": "6,8", "2000": "5,5", "2001": "6,5", "2002": "6,8", "2003": "7,6", "2004": "7,8", "2005": "8,5", "2006": "9,3", "2007": "10,7", "2008": "9,6", "2009": "9,7", "2010": "10,8", "2011": "11,8", "2012": "12,3", "2013": "15,4", "2014": "20,4" }, 
    { "Output in top 10 percentiles (%)": "United States", "Overall": "18,3", "1996": "17,3", "1997": "17,5", "1998": "17,7", "1999": "17,7", "2000": "17,8", "2001": "18,9", "2002": "18,5", "2003": "17,7", "2004": "17,7", "2005": "17,3", "2006": "17,3", "2007": "17,6", "2008": "17,3", "2009": "17,4", "2010": "17,7", "2011": "18,4", "2012": "17,8", "2013": "20,2", "2014": 24 }, 
    { "Output in top 10 percentiles (%)": "Universitat Stuttgart", "Overall": "12,9", "1996": "12,7", "1997": "10,5", "1998": "14,2", "1999": "13,8", "2000": "10,6", "2001": "11,5", "2002": "12,6", "2003": "10,3", "2004": "11,8", "2005": "9,7", "2006": "11,9", "2007": "11,2", "2008": "11,8", "2009": "11,9", "2010": "11,4", "2011": "13,7", "2012": "11,8", "2013": "16,4", "2014": "23,6" }, 
    { "Output in top 10 percentiles (%)": "University of Ljubljana", "Overall": "10,9", "1996": "6,2", "1997": "6,1", "1998": "6,1", "1999": "7,1", "2000": 5, "2001": 6, "2002": "6,8", "2003": "8,9", "2004": "7,8", "2005": "8,8", "2006": "10,1", "2007": "11,3", "2008": "10,6", "2009": "10,2", "2010": "10,9", "2011": "12,1", "2012": "13,2", "2013": "14,6", "2014": "20,2" }, 
    { "Output in top 10 percentiles (%)": "University of Maribor", "Overall": "9,5", "1996": "4,8", "1997": "3,6", "1998": "3,9", "1999": "1,9", "2000": "2,4", "2001": "2,4", "2002": "6,5", "2003": "4,5", "2004": "6,4", "2005": "8,8", "2006": "8,1", "2007": "9,4", "2008": 10, "2009": "8,5", "2010": "7,7", "2011": "9,9", "2012": 13, "2013": "15,9", "2014": "19,6" }, 
    { "Output in top 10 percentiles (%)": "University of Nova Gorica", "Overall": "18,2", "1996": "NA", "1997": "NA", "1998": "NA", "1999": "8,3", "2000": 0, "2001": "4,2", "2002": 4, "2003": 10, "2004": "9,3", "2005": "12,3", "2006": 22, "2007": "25,2", "2008": "17,5", "2009": "12,2", "2010": "15,3", "2011": "15,9", "2012": "18,3", "2013": "25,6", "2014": "27,5" } 
  ], 
  "errors": [], "meta": { "delimiter": ";", "linebreak": "'r'n", "aborted": false, "truncated": false, "fields": [ "Output in top 10 percentiles (%)", "Overall", "1996", "1997", "1998", "1999", "2000", "2001", "2002", "2003", "2004", "2005", "2006", "2007", "2008", "2009", "2010", "2011", "2012", "2013", "2014" ] }
};
// get the column of year 1996
var col1996 = parserOutput.data.map(
    function(value, index) {
        return value["1996"];  // dot notation would be possible here, if key wasn't a number
    }
);
// col1996 is now ["18,4", "13,3", "11,2", "6,5", ...]
// Some methods to output the result:
//alert(col1996);
//console.log(col1996);
document.getElementById("result").innerHTML = col1996.join('<br>');

<p>Result in var col1996:</p>
<div id="result"></div>