性能

Question

我需要根据规则创建一个新列，其中包含字母{a，b，c，d}：

{'a' if (df['q1']==0 & df['q2']==0), 
 'b' if (df['q1']==0 & df['q2']==1),
 'c' if (df['q1']==1 & df['q2']==0),
 'd' if (df['q1']==1 & df['q2']==1)}

所以，新的第三列应该包含一个字母，该字母对应于两列中{0,1}的特定组合。

         q1      q2
0         0       1
1         0       1
2         0       1
3         0       1
4         0       1
5         0       1
6         0       1
7         0       1
8         0       1
9         0       1
10        1       1
11        1       1
12        0       1
13        0       1
14        1       0
15        0       0
16        0       0
17        0       0
18        0       0
19        0       0
20        0       0
21        0       0

我考虑过将每行中的数字从二进制格式转换为十进制格式，然后应用字典规则。

Answer 1

您可以Series使用MultiIndex idx = pd.MultiIndex.from_product([[0,1],[0,1]], names=('q1','q2')) s = pd.Series(['a','b','c','d'], index=idx, name='val') print (s) q1 q2 0 0 a 1 b 1 0 c 1 d Name: val, dtype: object df = df.join(s, on=['q1','q2']) print (df) q1 q2 val 0 0 1 b 1 0 1 b 2 0 1 b 3 0 1 b 4 0 1 b 5 0 1 b 6 0 1 b 7 0 1 b 8 0 1 b 9 0 1 b 10 1 1 d 11 1 1 d 12 0 1 b 13 0 1 b 14 1 0 c 15 0 0 a 16 0 0 a 17 0 0 a 18 0 0 a 19 0 0 a 20 0 0 a 21 0 0 a：

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Answer 2

使用df.transform和In [90]: mapping = {(0, 0) :'a', (0, 1) : 'b', (1, 0): 'c', (1, 1): 'd'} In [91]: df['val'] = df.transform(lambda x: (x['q1'], x['q2']), axis=1).map(mapping); df Out[91]: q1 q2 val 0 0 1 b 1 0 1 b 2 0 1 b 3 0 1 b 4 0 1 b 5 0 1 b 6 0 1 b 7 0 1 b 8 0 1 b 9 0 1 b 10 1 1 d 11 1 1 d 12 0 1 b 13 0 1 b 14 1 0 c 15 0 0 a 16 0 0 a 17 0 0 a 18 0 0 a 19 0 0 a 20 0 0 a 21 0 0 a的另一种方法：

zip

您还可以使用pd.Series生成列，应用In [119]: df['val'] = pd.Series(list(zip(df.q1, df.q2))).map(mapping); df Out[119]: q1 q2 val 0 0 1 b 1 0 1 b 2 0 1 b 3 0 1 b 4 0 1 b 5 0 1 b 6 0 1 b 7 0 1 b 8 0 1 b 9 0 1 b 10 1 1 d 11 1 1 d 12 0 1 b 13 0 1 b 14 1 0 c 15 0 0 a 16 0 0 a 17 0 0 a 18 0 0 a 19 0 0 a 20 0 0 a 21 0 0 a然后执行映射：

In [552]: %%timeit
     ...: idx = pd.MultiIndex.from_product([[0,1],[0,1]], names=('q1','q2'))
     ...: s = pd.Series(['a','b','c','d'], index=idx, name='val')
     ...: df.join(s, on=['q1','q2'])
     ...: 
100 loops, best of 3: 2.84 ms per loop

性能

jezrael的解决方案：

In [553]: %%timeit
     ...: mapping = {(0, 0) :'a', (0, 1) : 'b', (1, 0): 'c', (1, 1): 'd'}
     ...: df.transform(lambda x: (x['q1'], x['q2']), axis=1).map(mapping)
     ...:  
1000 loops, best of 3: 1.7 ms per loop

在这篇文章中提出：

var data_table, row_num = 1,
  col_num = 11,
  row_cell = 1,
  col_cell = 0,
  iter = 0;
var cols = [];

var data = [{
  "StopName": "Udhna Darwaza",
  "1": "07:01:00",
  "2": "07:16:00",
  "3": "07:31:00",
  "4": "07:46:00",
  "5": "08:01:00",
  "6": "08:16:00",
  "7": "08:31:00",
  "8": "08:46:00",
  "9": "09:01:00",
  "10": "09:16:00"
}, {
  "StopName": "Kharwar Nagar",
  "1": "07:02:00",
  "2": "07:17:00",
  "3": "07:32:00",
  "4": "07:47:00",
  "5": "08:02:00",
  "6": "08:17:00",
  "7": "08:32:00",
  "8": "08:47:00",
  "9": "09:02:00",
  "10": "09:17:00"
}, {
  "StopName": "Satya Nagar",
  "1": "07:03:00",
  "2": "07:18:00",
  "3": "07:33:00",
  "4": "07:48:00",
  "5": "08:03:00",
  "6": "08:18:00",
  "7": "08:33:00",
  "8": "08:48:00",
  "9": "09:03:00",
  "10": "09:18:00"
}, {
  "StopName": "Udhna Tran Rasta",
  "1": "07:04:00",
  "2": "07:19:00",
  "3": "07:34:00",
  "4": "07:49:00",
  "5": "08:04:00",
  "6": "08:19:00",
  "7": "08:34:00",
  "8": "08:49:00",
  "9": "09:04:00",
  "10": "09:19:00"
}, {
  "StopName": "Udhna Bus Stand",
  "1": "07:05:00",
  "2": "07:20:00",
  "3": "07:35:00",
  "4": "07:50:00",
  "5": "08:05:00",
  "6": "08:20:00",
  "7": "08:35:00",
  "8": "08:50:00",
  "9": "09:05:00",
  "10": "09:20:00"
}, {
  "StopName": "Udhna Academy",
  "1": "07:06:00",
  "2": "07:21:00",
  "3": "07:36:00",
  "4": "07:51:00",
  "5": "08:06:00",
  "6": "08:21:00",
  "7": "08:36:00",
  "8": "08:51:00",
  "9": "09:06:00",
  "10": "09:21:00"
}, {
  "StopName": "Laxmi Narayan Temple",
  "1": "07:07:00",
  "2": "07:22:00",
  "3": "07:37:00",
  "4": "07:52:00",
  "5": "08:07:00",
  "6": "08:22:00",
  "7": "08:37:00",
  "8": "08:52:00",
  "9": "09:07:00",
  "10": "09:22:00"
}, {
  "StopName": "Daksheswar Mahadev",
  "1": "07:08:00",
  "2": "07:23:00",
  "3": "07:38:00",
  "4": "07:53:00",
  "5": "08:08:00",
  "6": "08:23:00",
  "7": "08:38:00",
  "8": "08:53:00",
  "9": "09:08:00",
  "10": "09:23:00"
}, {
  "StopName": "Pandesara G.I.D.C.",
  "1": "07:09:00",
  "2": "07:24:00",
  "3": "07:39:00",
  "4": "07:54:00",
  "5": "08:09:00",
  "6": "08:24:00",
  "7": "08:39:00",
  "8": "08:54:00",
  "9": "09:09:00",
  "10": "09:24:00"
}, {
  "StopName": "Kamnath Mahadev",
  "1": "07:10:00",
  "2": "07:25:00",
  "3": "07:40:00",
  "4": "07:55:00",
  "5": "08:10:00",
  "6": "08:25:00",
  "7": "08:40:00",
  "8": "08:55:00",
  "9": "09:10:00",
  "10": "09:25:00"
}, {
  "StopName": "Navin Flourine",
  "1": "07:11:00",
  "2": "07:26:00",
  "3": "07:41:00",
  "4": "07:56:00",
  "5": "08:11:00",
  "6": "08:26:00",
  "7": "08:41:00",
  "8": "08:56:00",
  "9": "09:11:00",
  "10": "09:26:00"
}, {
  "StopName": "Bhestan Naher",
  "1": "07:12:00",
  "2": "07:27:00",
  "3": "07:42:00",
  "4": "07:57:00",
  "5": "08:12:00",
  "6": "08:27:00",
  "7": "08:42:00",
  "8": "08:57:00",
  "9": "09:12:00",
  "10": "09:27:00"
}, {
  "StopName": "Bhagwati Industrial Estate",
  "1": "07:13:00",
  "2": "07:28:00",
  "3": "07:43:00",
  "4": "07:58:00",
  "5": "08:13:00",
  "6": "08:28:00",
  "7": "08:43:00",
  "8": "08:58:00",
  "9": "09:13:00",
  "10": "09:28:00"
}, {
  "StopName": "Unn Naka",
  "1": "07:14:00",
  "2": "07:29:00",
  "3": "07:44:00",
  "4": "07:59:00",
  "5": "08:14:00",
  "6": "08:29:00",
  "7": "08:44:00",
  "8": "08:59:00",
  "9": "09:14:00",
  "10": "09:29:00"
}, {
  "StopName": "Unn Industrial Estate",
  "1": "07:15:00",
  "2": "07:30:00",
  "3": "07:45:00",
  "4": "08:00:00",
  "5": "08:15:00",
  "6": "08:30:00",
  "7": "08:45:00",
  "8": "09:00:00",
  "9": "09:15:00",
  "10": "09:30:00"
}, {
  "StopName": "Unn Char Rasta",
  "1": "07:16:00",
  "2": "07:31:00",
  "3": "07:46:00",
  "4": "08:01:00",
  "5": "08:16:00",
  "6": "08:31:00",
  "7": "08:46:00",
  "8": "09:01:00",
  "9": "09:16:00",
  "10": "09:31:00"
}, {
  "StopName": "Green Park",
  "1": "07:17:00",
  "2": "07:32:00",
  "3": "07:47:00",
  "4": "08:02:00",
  "5": "08:17:00",
  "6": "08:32:00",
  "7": "08:47:00",
  "8": "09:02:00",
  "9": "09:17:00",
  "10": "09:32:00"
}, {
  "StopName": "Sachin G.I.D.C.",
  "1": "07:18:00",
  "2": "07:33:00",
  "3": "07:48:00",
  "4": "08:03:00",
  "5": "08:18:00",
  "6": "08:33:00",
  "7": "08:48:00",
  "8": "09:03:00",
  "9": "09:18:00",
  "10": "09:33:00"
}, {
  "StopName": "Sachin GIDC Naka",
  "1": "07:30:00",
  "2": "07:45:00",
  "3": "08:00:00",
  "4": "08:15:00",
  "5": "08:30:00",
  "6": "08:45:00",
  "7": "09:00:00",
  "8": "09:15:00",
  "9": "09:30:00",
  "10": "09:45:00"
}];

//Get stored data from HTML table element
var results = [];

function initDT() {
  debugger;
  //Construct the measurement table
  data_table = $('#example').dataTable({
    "bJQueryUI": true,
    "bDeferRender": true,
    "bInfo": false,
    "bSort": false,
    "bDestroy": true,
    "bFilter": false,
    "bPagination": false,
    "aaData": results,
    "aoColumns": cols,
  });
  attachTableClickEventHandlers();
}

function fnCreatedRow(nRow, aData, iDataIndex) {
  var sURL = aData[6];
  var t = "<img src='" + sURL + "' width='90' height='126'>";
  $(nRow).attr('tooltip-title', t);
}

function fnDrawCallback(settings) {
  $(".tooltip-card-name").each(function(i, td) {
    var title = $(td).parent().attr('tooltip-title');
    $(td).tooltip({
      "delay": 0,
      "track": true,
      "fade": 250,
      content: title
    })
  });
}

function GetSchedules() {
  cols = [];
  var returnedData = data;
  if (returnedData.length > 0) {
    var obj = returnedData[0];
    for (var key in obj) {
      var attrName = key;
      var attrValue = obj[key];
      var column = {
        "mData": key,
        "mDataProp": key,
        "sTitle": key,
        "sType": "string",
        "fnCreatedCell": function(nTd, sData, oData, iRow, iCol) {
          if (iCol == 0) {
            nTd.title = $(nTd).text();
            if ($(nTd).text().length > 3) {
              $(nTd).text($(nTd).text().substring(0, 3).concat("..."));
            }
          }
        }
      };
      cols.push(column);
    }
  }
  debugger;
  results = returnedData;
  //$('#example').dataTable().fnClearTable();
  initDT();
  addDBClikHandler();
}

function attachTableClickEventHandlers() {
  //row/column indexing is zero based
  $("#example thead tr th").click(function() {    
    col_num = parseInt($(this).index());
    console.log("column_num =" + col_num);  
  });
  $("#example tbody tr td").click(function() {    
    col_cell = parseInt($(this).index());
    row_cell = parseInt($(this).parent().index());   
    console.log("Row_num =" + row_cell + "  ,  column_num =" + col_cell);
  });
};


$("#btnAddRow").click(function() {
  //adding/removing row from datatable datasource
  //create test new record
  var aoCols = data_table.fnSettings().aoColumns;
  var newRow = new Object();
  for (var iRec = 0; iRec < aoCols.length; iRec++) {

    if (aoCols[iRec]._sManualType === "date") {
      newRow[aoCols[iRec].mDataProp] = "2011/03/25";
    } else if (aoCols[iRec]._sManualType === "numeric") {
      newRow[aoCols[iRec].mDataProp] = 10;
    } else if (aoCols[iRec]._sManualType === "string") {
      newRow[aoCols[iRec].mDataProp] = 'testStr';
    }
  }
  results.splice(row_cell + 1, 0, newRow);
  data_table.fnDestroy();
  initDT();
  addDBClikHandler();
});

$('#btnAddCol').click(function() {

  //new column information
  //row's new field(for new column)
  //cols must be updated
  cols.splice(col_num + 1, 0, {
    "mDataProp": "newField" + iter,
    sTitle: "Col-" + iter,
    sType: "string"
  });
  //update the result, actual data to be displayed
  for (var iRes = 0; iRes < results.length; iRes++) {
    results[iRes]["newField" + iter] = "data-" + iter;
  }
  //destroy the table
  data_table.fnDestroy();
  $("#example thead tr th").eq(col_num).after('<th>Col-' + iter + '</th>');
  //init again
  initDT();
  iter++;
  addDBClikHandler();
});

function restoreRow(oTable, nRow) {
  var aData = oTable.fnGetData(nRow);
  var jqTds = $('>td', nRow);

  for (var i = 0, iLen = jqTds.length; i < iLen; i++) {
    oTable.fnUpdate(aData[i], nRow, i, false);
  }
};

function editRow(oTable, nRow) {
  var aData = oTable.fnGetData(nRow);
  var jqTds = $('>td', nRow);
  jqTds[col_cell].innerHTML = '<input type="text" id ="typ" value="' + aData[cols[col_cell].mData] + '"/>';
  $("#typ").autocomplete({
    source: type1
  });
};

function saveRow(oTable, nRow) {
  var jqInputs = $('input', nRow);
  oTable.fnUpdate(jqInputs[0].value, row_cell, col_cell, false);
};

jQuery.extend(jQuery.fn.dataTableExt.oSort, {
  "date-uk-pre": function(a) {
    var ukDatea = a.split('/');
    return (ukDatea[2] + ukDatea[1] + ukDatea[0]) * 1
  },

  "date-uk-asc": function(a, b) {
    return ((a < b) ? -1 : ((a > b) ? 1 : 0));
  },

  "date-uk-desc": function(a, b) {
    return ((a < b) ? 1 : ((a > b) ? -1 : 0));
  }
});

/* Get the rows which are currently selected */
function fnGetSelected(oTableLocal) {
  var aReturn = new Array();
  var aTrs = oTableLocal.fnGetNodes();

  for (var i = 0; i < aTrs.length; i++) {
    if ($(aTrs[i]).hasClass('row_selected')) {
      aReturn.push(aTrs[i]);
    }
  }
  return aReturn;
};

function addDBClikHandler() {
  $('#example tbody tr').on('dblclick', function(e) {
    e.preventDefault();

    var nRow = $(this)[0];

    var jqTds = $('>td', nRow);
    if ($.trim(jqTds[0].innerHTML.substr(0, 6)) != '<input') {
      if (nEditing !== null && nEditing != nRow) {
        /* Currently editing - but not this row - restore the old before continuing to edit mode */
        restoreRow(oTable, nEditing);
        nEditing = nRow;
        editRow(oTable, nRow);

      } else {
        /* No edit in progress - let's start one */
        nEditing = nRow;
        editRow(oTable, nRow);

      }

    }


  });

  $('#example tbody tr').keydown(function(event) {

    if (event.keyCode == 13) {
      event.preventDefault();

      if (nEditing == null)
        alert("Select Row");
      else
        saveRow(oTable, nEditing);
      nEditing = null;
    }
    /* Editing this row and want to save it */

  });


};

var nEditing = null;

var oTable = null;

$(document).ready(function() {
  GetSchedules();
  initDT();
  oTable = data_table;
  addDBClikHandler();
});

使用字典映射熊猫中的列

2 个答案:

性能