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如何在用戶窗口中更新分佈圖並探索異常值平台

各位，

 

我正在更新我前段時間寫的腳本。 您可以找到原始腳本/想法這裡。 原始腳本旨在當用戶單擊當前數據表的“選擇列”面板框中列出的列時更新一些基本統計信息。

 

我現在想做的是添加一些面板框，當用戶單擊當前數據表中可用的不同列時，這些面板框也會更新。 我想更新一個顯示列內數據分佈的面板框 - 實際上顯示分佈平台的結果（如果可能），而不僅僅是生成圖形生成器或圖形框來執行此操作。 另一個是顯示“探索離群值”平台結果的面板框。 我希望當用戶選擇要查看的新列時這兩個面板框都會更新。

 

使用“Big Class.jmp”示例數據文件，我製作了一個我希望它顯示的內容的小模型。 我在最後添加了 JSL。

 

這是用戶界面的當前視圖。

 

這就是當有人單擊感興趣的列（在本例中為：高度）時我希望它看起來如何的概念。

 

然後，當用戶單擊新列（例如：weight）時，顯示會更新並顯示以下內容：

 

我實際上不需要分佈平台中的匯總統計數據，但我想要帶有箱線圖和在其上方繪製的數據點的分佈，以及箱線圖中的附加信息，例如均值、中值和最大50 %數據——例如，您無法在圖形生成器中輕鬆添加這些數據。

 

 

您不必為我完全解決這個問題，但如果有人對如何開始有建議，我真的很感激，因為到目前為止我嘗試過的想法不起作用。 我什至不知道這是否可能，但我希望如此。 我寧願不必將其作為儀表板。

 

在此先感謝您的幫助！ 下面是JSL

 

謝謝！，

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>

 

自動化和腳本編寫基礎數據分析和建模數據探索和可視化分享和交流結果回复：如何在用戶窗口中更新分佈圖並探索異常值平台

我的腦海中浮現出幾個想法：

• 使用帶有尺寸的間隔框強制顯示存儲分佈和探索異常值的框的特定尺寸。 當用戶更改到感興趣的列時 - >刪除舊的分佈並探索異常值並將它們重新製作到相同的位置（附加應該在這里工作）
• 使用隱藏的列切換器並在用戶在列列表中進行更改時更新列選擇

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：如何在用戶窗口中更新分佈圖並探索異常值平台

你好@jthi ,

 

我其實希望你能回复，因為我知道我會得到很好的建議，謝謝！

 

儘管您的建議並不完全是我想要的，但它們給了我一些關於如何進行我想要的改變的好主意。 我最終修改了代碼中的 <

 

我在下面添加了我的代碼，以防有人感興趣。 我確信還有其他方法可以做到這一點，但這足夠通用，適用於幾種不同類型的數據文件，所以我現在對它很滿意。

 

謝謝！，

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>