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如何在用户窗口中更新分布图并探索异常值平台

各位，

 

我正在更新我前段时间写的脚本。 您可以找到原始脚本/想法这里。 原始脚本旨在当用户单击当前数据表的“选择列”面板框中列出的列时更新一些基本统计信息。

 

我现在想做的是添加一些面板框，当用户单击当前数据表中可用的不同列时，这些面板框也会更新。 我想更新一个显示列内数据分布的面板框 - 实际上显示分布平台的结果（如果可能），而不仅仅是生成图形生成器或图形框来执行此操作。 另一个是显示“探索离群值”平台结果的面板框。 我希望当用户选择要查看的新列时这两个面板框都会更新。

 

使用“Big Class.jmp”示例数据文件，我制作了一个我希望它显示的内容的小模型。 我在最后添加了 JSL。

 

这是用户界面的当前视图。

 

这就是当有人单击感兴趣的列（在本例中为：高度）时我希望它看起来如何的概念。

 

然后，当用户单击新列（例如：weight）时，显示会更新并显示以下内容：

 

我实际上不需要分布平台中的汇总统计数据，但我想要带有箱线图和在其上方绘制的数据点的分布，以及箱线图中的附加信息，例如均值、中值和最大 50%数据——例如，您无法在图形生成器中轻松添加这些数据。

 

 

您不必为我完全解决这个问题，但如果有人对如何开始有建议，我真的很感激，因为到目前为止我尝试过的想法不起作用。 我什至不知道这是否可能，但我希望如此。 我宁愿不必将其作为仪表板。

 

在此先感谢您的帮助！ 下面是JSL

 

谢谢！，

DS

//GUI for quickly reporting statistics written by D. Schmidt, ver2.0
//Thanks to JMP User community members: jthi, ian_jmp, and ErraticAttach for helpful suggested changes.
Names Default To Here( 1 );
Clear Symbols();
//the width of the column list box in pixels
lbWidth = 200;

dt = Current Data Table();
//dt = Open( "$SAMPLE_DATA/Big Class.jmp" );

//List of statistics to calculate
StatsList1 = {"µ", "σ", "Max", "Min", "Range(Δ)", "N"};
StatsList2 = {"µ", "Median", "Mode", "N"};
StatsList3 = {"Quantiles", "5%", "25%", "50%", "75%", "95%", "Int. Q. Range"};
StatsList4 = {"N", "N Missing", "N 0", "Prop 0", "Prop non-0"};
maxStatCount = Max( N Items( StatsList1 ), N Items( StatsList2 ), N Items( StatsList3 ), N Items( StatsList4 ) );

//RadioBox() arguments
rbArg = Eval List(
 {Concat Items( StatsList1, ", " ), Concat Items( StatsList2, ", " ), Concat Items( StatsList3, ", " ), Concat Items( StatsList4, ", " )}
);
rbcArg = {"Select for categorical columns"};

//Statistics to Calculate
statMean = Expr( Col Mean( tempCol ) );
statStd = Expr( Col Std Dev( tempCol ) );
statMax = Expr( Col Max( tempCol ) );
statMin = Expr( Col Min( tempCol ) );
statMed = Expr( Col Median( tempCol ) );
statMode = Expr(
 Mode( dt:tempcol << getvalues )
);

statRange = Expr(
 Col Max( tempCol ) - Col Min( tempCol )
);
statN = Expr( Col Number( tempCol ) );
statQ95 = Expr(
 Col Quantile( tempCol, 0.05 )
);
statQ75 = Expr(
 Col Quantile( tempCol, 0.25 )
);
statQ50 = Expr(
 Col Quantile( tempCol, 0.5 )
);
statQ25 = Expr(
 Col Quantile( tempCol, 0.75 )
);
statQ5 = Expr(
 Col Quantile( tempCol, 0.95 )
);
statIntQR = Expr( StatQ25 - StatQ75 );
statMiss = Expr(
 Col N Missing( tempCol )
);
statZero = Expr(
 N Items( Loc( tempCol << get as matrix, 0 ) )
);
statProp0 = Expr( statZero / statN );
statPropn0 = Expr( 1 - statProp0 );

OrdStats = Expr(
 colmodeltype = tempCol << Get Modeling type;
 If( colmodeltype == "Ordinal",
  orddist = dt << Distribution( Nominal Distribution( Column( tempCol ) ), Invisible );
  rpt_orddist = orddist << Report;

  ordlvl = rpt_orddist[String Col Box( 1 )] << Get;
  ordCount = rpt_orddist[Number Col Box( 1 )] << Get;
  ordProb = rpt_orddist[Number Col Box( 2 )] << Get;
  OrdSummNMiss = rpt_orddist[List Box( 7 )][2] << Get Text;
  OrdSummLvl = rpt_orddist[List Box( 8 )][1] << Get text;
  OrdnumNMiss = Num( OrdSummNMiss );
  OrdnumLvl = Num( OrdSummLvl );
  Orddist << Close Window;
 );
 Insert Into( Ordlvl, {"N Missing", "N Levels"} );
 Insert Into( OrdCount, OrdnumNMiss );
 Insert Into( OrdCount, OrdnumLvl );
);

CatStats = Expr(
 coltype = tempCol << Get Data type;
 If( coltype == "Character",
  catdist = dt << Distribution( Nominal Distribution( Column( tempCol ) ), Invisible );
  rpt_catdist = catdist << Report;

  lvl = rpt_catdist[String Col Box( 1 )] << Get;
  Count = rpt_catdist[Number Col Box( 1 )] << Get;
  Prob = rpt_catdist[Number Col Box( 2 )] << Get;
  SummNMiss = rpt_catdist[List Box( 7 )][2] << Get Text;
  SummLvl = rpt_catdist[List Box( 8 )][1] << Get text;
  numNMiss = Num( SummNMiss );
  numLvl = Num( SummLvl );
  catdist << Close Window;
 );
 Insert Into( lvl, {"N Missing", "N Levels"} );
 Insert Into( Count, numNMiss );
 Insert Into( Count, numLvl );
);

//List for results
StatList = Eval List( {StatsList1, StatsList2, StatsList3, StatsList4} );
StatListRes1 = Expr(
 Eval List( {statMean, statStd, statMax, statMin, statRange, statN} )
);
StatListRes2 = Expr(
 Eval List( {statMean, statMed, statMode, statN} )
);
StatListRes3 = Expr(
 Eval List( {., statQ95, statQ75, statQ50, statQ25, statQ5, StatIntQR} )
);
StatListRes4 = Expr(
 Eval List( {statN, statMiss, statZero, statProp0, statPropn0} )
);
StatListRes = Expr(
 Eval List( {StatListRes1, StatListRes2, StatListRes3, StatListRes4} )
);

//Expression to handle the distribution platform
DistExpr = Expr(
 Distribution(
  Continuous Distribution(
   Column( tempCol ),
   Quantiles( 0 ),
   Horizontal Layout( 1 ),
   Vertical( 0 ),
   Customize Summary Statistics( N Zero( 1 ) )
  ),
  SendToReport( Dispatch( tempCol, "Summary Statistics", OutlineBox, {Close( 1 )} ) )
 )
);

//Expression for Outliers
OutlierExpr = Expr(
 Explore Outliers( Y( tempCol ), Quantile Range Outliers)
);


//User window
ValueDlg = Expr(
 nwin = New Window( "GUI for quick stats",
  <<RETURN result=""></RETURN>

 

自动化和脚本编写基础数据分析和建模数据探索和可视化分享和交流结果回复：如何在用户窗口中更新分布图并探索异常值平台

我的脑海中浮现出几个想法：

• 使用带有尺寸的间隔框强制显示存储分布和探索异常值的框的特定尺寸。 当用户更改到感兴趣的列时 - >删除旧的分布并探索异常值并将它们重新制作到相同的位置（附加应该在这里工作）
• 使用隐藏的列切换器并在用户在列列表中进行更改时更新列选择

Names Default To Here(1);

dt = Open("$SAMPLE_DATA/Big Class.jmp");

eo = dt << Explore Outliers(
 Y(:weight),
 Quantile Range Outliers
);

cs_eo = eo << Column Switcher(
 :weight,
 {:weight, :height}
);
(Report(eo) << top parent)[Outline Box("Column Switcher")] << Visibility("Collapse");

wait(1);
cs_eo << Set Current("height");
wait(1);
cs_eo << Set Current("weight");

回复：如何在用户窗口中更新分布图并探索异常值平台

你好@jthi ,

 

我其实希望你能回复，因为我知道我会得到很好的建议，谢谢！

 

尽管您的建议并不完全是我想要的，但它们给了我一些关于如何进行我想要的改变的好主意。 我最终修改了代码中的 <

 

我在下面添加了我的代码，以防有人感兴趣。 我确信还有其他方法可以做到这一点，但这足够通用，适用于几种不同类型的数据文件，所以我现在对它很满意。

 

谢谢！，

DS

//GUI for quickly reporting statistics written by D. Schmidt, ver2.1<BR />//Thanks to JMP User community members: jthi, ian_jmp, and ErraticAttach for helpful suggested changes.
Names Default To Here( 1 );
Clear Symbols();
//the width of the column list box in pixels
lbWidth = 200;

dt = Current Data Table();
//dt = Open( "$SAMPLE_DATA/Big Class.jmp" );

//List of statistics to calculate
StatsList1 = {"µ", "σ", "Max", "Min", "Range(Δ)", "N"};
StatsList2 = {"µ", "Median", "Mode", "N"};
StatsList3 = {"Quantiles", "5%", "25%", "50%", "75%", "95%", "Int. Q. Range"};
StatsList4 = {"N", "N Missing", "N 0", "Prop 0", "Prop non-0"};
maxStatCount = Max( N Items( StatsList1 ), N Items( StatsList2 ), N Items( StatsList3 ), N Items( StatsList4 ) );

//RadioBox() arguments
rbArg = Eval List(
 {Concat Items( StatsList1, ", " ), Concat Items( StatsList2, ", " ), Concat Items( StatsList3, ", " ), Concat Items( StatsList4, ", " )}
);
rbcArg = {"Select for categorical columns"};

//Statistics to Calculate
statMean = Expr( Col Mean( tempCol ) );
statStd = Expr( Col Std Dev( tempCol ) );
statMax = Expr( Col Max( tempCol ) );
statMin = Expr( Col Min( tempCol ) );
statMed = Expr( Col Median( tempCol ) );
statMode = Expr(
 Mode( dt:tempcol << getvalues )
);

statRange = Expr(
 Col Max( tempCol ) - Col Min( tempCol )
);
statN = Expr( Col Number( tempCol ) );
statQ95 = Expr(
 Col Quantile( tempCol, 0.05 )
);
statQ75 = Expr(
 Col Quantile( tempCol, 0.25 )
);
statQ50 = Expr(
 Col Quantile( tempCol, 0.5 )
);
statQ25 = Expr(
 Col Quantile( tempCol, 0.75 )
);
statQ5 = Expr(
 Col Quantile( tempCol, 0.95 )
);
statIntQR = Expr( StatQ25 - StatQ75 );
statMiss = Expr(
 Col N Missing( tempCol )
);
statZero = Expr(
 N Items( Loc( tempCol << get as matrix, 0 ) )
);
statProp0 = Expr( statZero / statN );
statPropn0 = Expr( 1 - statProp0 );

OrdStats = Expr(
 colmodeltype = tempCol << Get Modeling type;
 If( colmodeltype == "Ordinal",
  orddist = dt << Distribution( Nominal Distribution( Column( tempCol ) ), Invisible );
  rpt_orddist = orddist << Report;

  ordlvl = rpt_orddist[String Col Box( 1 )] << Get;
  ordCount = rpt_orddist[Number Col Box( 1 )] << Get;
  ordProb = rpt_orddist[Number Col Box( 2 )] << Get;
  OrdSummNMiss = rpt_orddist[List Box( 7 )][2] << Get Text;
  OrdSummLvl = rpt_orddist[List Box( 8 )][1] << Get text;
  OrdnumNMiss = Num( OrdSummNMiss );
  OrdnumLvl = Num( OrdSummLvl );
  Orddist << Close Window;
 );
 Insert Into( Ordlvl, {"N Missing", "N Levels"} );
 Insert Into( OrdCount, OrdnumNMiss );
 Insert Into( OrdCount, OrdnumLvl );
);

CatStats = Expr(
 coltype = tempCol << Get Data type;
 If( coltype == "Character",
  catdist = dt << Distribution( Nominal Distribution( Column( tempCol ) ), Invisible );
  rpt_catdist = catdist << Report;

  lvl = rpt_catdist[String Col Box( 1 )] << Get;
  Count = rpt_catdist[Number Col Box( 1 )] << Get;
  Prob = rpt_catdist[Number Col Box( 2 )] << Get;
  SummNMiss = rpt_catdist[List Box( 7 )][2] << Get Text;
  SummLvl = rpt_catdist[List Box( 8 )][1] << Get text;
  numNMiss = Num( SummNMiss );
  numLvl = Num( SummLvl );
  catdist << Close Window;
 );
 Insert Into( lvl, {"N Missing", "N Levels"} );
 Insert Into( Count, numNMiss );
 Insert Into( Count, numLvl );
);

//List for results
StatList = Eval List( {StatsList1, StatsList2, StatsList3, StatsList4} );
StatListRes1 = Expr(
 Eval List( {statMean, statStd, statMax, statMin, statRange, statN} )
);
StatListRes2 = Expr(
 Eval List( {statMean, statMed, statMode, statN} )
);
StatListRes3 = Expr(
 Eval List( {., statQ95, statQ75, statQ50, statQ25, statQ5, StatIntQR} )
);
StatListRes4 = Expr(
 Eval List( {statN, statMiss, statZero, statProp0, statPropn0} )
);
StatListRes = Expr(
 Eval List( {StatListRes1, StatListRes2, StatListRes3, StatListRes4} )
);


//User window
ValueDlg = Expr(
 nwin = New Window( "GUI for quick stats",
  <<RETURN result=""></RETURN>