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Commitd503f5d

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authored
Merge pull request#252 from minjk-bl/devops
Devops for v3.0.1
2 parentsb195d05 +25bd448 commitd503f5d

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6 files changed

+39
-20
lines changed

6 files changed

+39
-20
lines changed

‎visualpython/html/m_ml/evaluation.html‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -38,7 +38,7 @@
3838
<label><inputtype="checkbox"id="accuracy"class="vp-state"><span>Accuracy</span></label>
3939
<label><inputtype="checkbox"id="precision"class="vp-state"><span>Precision</span></label>
4040
<label><inputtype="checkbox"id="recall"class="vp-state"><span>Recall</span></label>
41-
<label><inputtype="checkbox"id="f1_score"class="vp-state"><span>F1-scorev</label>
41+
<label><inputtype="checkbox"id="f1_score"class="vp-state"><span>F1-score</label>
4242
<!-- <hr style="margin: 5px;"/> -->
4343
<!-- <label><input type="checkbox" id="roc_curve" class="vp-eval-check vp-state" data-type="roc-auc"><span>ROC Curve</span></label>
4444
<label><input type="checkbox" id="auc" class="vp-eval-check vp-state" data-type="roc-auc"><span>AUC</span></label> -->

‎visualpython/js/m_apps/Frame.js‎

Lines changed: 17 additions & 12 deletions
Original file line numberDiff line numberDiff line change
@@ -115,10 +115,10 @@ define([
115115
id:'encoding',
116116
label:'Encoding',
117117
axis:FRAME_AXIS.COLUMN,
118-
selection:FRAME_SELECT_TYPE.SINGLE,
118+
selection:FRAME_SELECT_TYPE.MULTI,
119119
child:[
120-
{id:'label_encoding',label:'Label encoding',axis:FRAME_AXIS.COLUMN,selection:FRAME_SELECT_TYPE.SINGLE,menuType:FRAME_EDIT_TYPE.LABEL_ENCODING},
121-
{id:'one_hot_encoding',label:'Onehot encoding',axis:FRAME_AXIS.COLUMN,selection:FRAME_SELECT_TYPE.SINGLE,menuType:FRAME_EDIT_TYPE.ONE_HOT_ENCODING},
120+
{id:'label_encoding',label:'Label encoding',axis:FRAME_AXIS.COLUMN,selection:FRAME_SELECT_TYPE.MULTI,menuType:FRAME_EDIT_TYPE.LABEL_ENCODING},
121+
{id:'one_hot_encoding',label:'Onehot encoding',axis:FRAME_AXIS.COLUMN,selection:FRAME_SELECT_TYPE.MULTI,menuType:FRAME_EDIT_TYPE.ONE_HOT_ENCODING},
122122
]
123123
},
124124
{
@@ -2767,7 +2767,7 @@ define([
27672767
varcondText=$(condTextTag[i]).prop('checked');
27682768
varoperConn=$(operConnTag[i]).val();
27692769
varcondObj={};
2770-
if(col!==''&&oper!==''&&cond!==''){
2770+
if(col!==''&&oper!==''&&(oper=='isnull()'||oper==='notnull()'||cond!=='')){
27712771
condObj={
27722772
oper:oper,
27732773
cond:com_util.convertToStr(cond,condText)
@@ -2808,7 +2808,7 @@ define([
28082808
varcondText=$(condTextTag[i]).prop('checked');
28092809
varoperConn=$(operConnTag[i]).val();
28102810
varcondObj={};
2811-
if(col!==''&&oper!==''&&cond!==''){
2811+
if(col!==''&&oper!==''&&(oper=='isnull()'||oper==='notnull()'||cond!=='')){
28122812
condObj={
28132813
colName:col,
28142814
oper:oper,
@@ -2861,7 +2861,7 @@ define([
28612861
varcondText=$(condTextTag[i]).prop('checked');
28622862
varoperConn=$(operConnTag[i]).val();
28632863
varcondObj={};
2864-
if(col!==''&&oper!==''&&cond!==''){
2864+
if(col!==''&&oper!==''&&(oper=='isnull()'||oper==='notnull()'||cond!=='')){
28652865
condObj={
28662866
colName:col,
28672867
oper:oper,
@@ -2894,7 +2894,7 @@ define([
28942894
varcondText=$(condTextTag[i]).prop('checked');
28952895
varoperConn=$(operConnTag[i]).val();
28962896
varcondObj={};
2897-
if(col!==''&&oper!==''&&cond!==''){
2897+
if(col!==''&&oper!==''&&(oper=='isnull()'||oper==='notnull()'||cond!=='')){
28982898
condObj={
28992899
oper:oper,
29002900
cond:com_util.convertToStr(cond,condText)
@@ -3237,13 +3237,18 @@ define([
32373237
break;
32383238
caseFRAME_EDIT_TYPE.LABEL_ENCODING:
32393239
if(axis==FRAME_AXIS.COLUMN){
3240-
letencodedColName=this.state.selected.map(col=>{
3240+
letencodedColNameList=this.state.selected.map(col=>{
32413241
if(col.code!==col.label){
3242-
returncom_util.formatString("'{0}'",col.label+'_label');
3242+
return{'origin':com_util.formatString("'{0}'",col.label),'encoded':com_util.formatString("'{0}'",col.label+'_label')};
32433243
}
3244-
returncol.label+'_label'
3245-
}).join(',');
3246-
code.appendFormat("{0}[{1}] = pd.Categorical({2}[{3}]).codes",tempObj,encodedColName,tempObj,selectedName);
3244+
return{'origin':col.label,'encoded':col.label+'_label'};
3245+
});
3246+
encodedColNameList.forEach((encodedColObj,idx)=>{
3247+
if(idx>0){
3248+
code.appendLine();
3249+
}
3250+
code.appendFormat("{0}[{1}] = pd.Categorical({2}[{3}]).codes",tempObj,encodedColObj['encoded'],tempObj,encodedColObj['origin']);
3251+
});
32473252
}
32483253
break;
32493254
caseFRAME_EDIT_TYPE.ONE_HOT_ENCODING:

‎visualpython/js/m_apps/Groupby.js‎

Lines changed: 12 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -177,7 +177,7 @@ define([
177177
varcolList=event.dataList;
178178
that.state.display=colList;
179179

180-
if(colList&&colList.length==1){
180+
if((colList&&colList.length==1)||that.state.method==='size'){
181181
$(that.wrapSelector('#vp_gbToFrame')).parent().show();
182182
}else{
183183
$(that.wrapSelector('#vp_gbToFrame')).parent().hide();
@@ -196,6 +196,12 @@ define([
196196
varmethod=$(this).val();
197197
that.state.method=method;
198198
$(that.wrapSelector('#vp_gbMethod')).val(method);
199+
200+
if(method==='size'||(that.state.display&&that.state.display.length==1)){
201+
$(that.wrapSelector('#vp_gbToFrame')).parent().show();
202+
}else{
203+
$(that.wrapSelector('#vp_gbToFrame')).parent().hide();
204+
}
199205
});
200206

201207
// advanced checkbox event
@@ -744,7 +750,7 @@ define([
744750
// Display columns
745751
//====================================================================
746752
varcolStr='';
747-
if(display){
753+
if(display&&display.length>0){
748754
if(toFrame||display.length>1){
749755
// over 2 columns
750756
colStr='[['+display.join(',')+']]';
@@ -891,6 +897,10 @@ define([
891897
methodStr.appendFormat('{0}(numeric_only=True)',method);
892898
}else{
893899
methodStr.appendFormat('{0}()',method);
900+
if(method==='size'&&toFrame===true){
901+
// if to_Frame on size() method
902+
methodStr.append(".to_frame(name='size')");
903+
}
894904
}
895905
}
896906
}

‎visualpython/js/m_apps/Subset.js‎

Lines changed: 6 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -1810,6 +1810,10 @@ define([
18101810
rowSelection.append(')');
18111811
}else{
18121812
rowSelection.appendFormat('({0}',varName);
1813+
if(colName=='.index'){
1814+
// index
1815+
rowSelection.append('.index');
1816+
}
18131817
oper&&rowSelection.appendFormat(' {0}',oper);
18141818
if(cond){
18151819
// condition value as text
@@ -1863,7 +1867,7 @@ define([
18631867
varcolList=[];
18641868
for(vari=0;i<colTags.length;i++){
18651869
varcolValue=$(colTags[i]).data('code');
1866-
if(colValue){
1870+
if(colValue!==undefined){
18671871
colList.push(colValue);
18681872
}
18691873
}
@@ -1873,7 +1877,7 @@ define([
18731877
$(this.wrapSelector('.'+VP_DS_TO_FRAME)).parent().show();
18741878

18751879
// to frame
1876-
if(this.state.toFrame){
1880+
if(this.state.toFrame===true){
18771881
colSelection.appendFormat('[{0}]',colList.toString());
18781882
this.state.returnType='DataFrame';
18791883
}else{

‎visualpython/js/m_ml/evaluation.js‎

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -276,8 +276,8 @@ define([
276276
// }
277277
if(r_squared){
278278
code=newcom_String();
279-
code.appendLine("# Rsquare");
280-
code.appendFormat("print('Rsquare: {}'.format(metrics.r2_score({0}, {1})))",targetData,predictData);
279+
code.appendLine("# Rsquared");
280+
code.appendFormat("print('Rsquared: {}'.format(metrics.r2_score({0}, {1})))",targetData,predictData);
281281
codeCells.push(code.toString());
282282
}
283283
if(mae){

‎visualpython/python/userCommand.py‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -130,7 +130,7 @@ def vp_create_permutation_importances(model, X_train, y_train, scoring=None, sor
130130
ifisinstance(X_train,_vp_pd.core.frame.DataFrame):
131131
feature_names=X_train.columns
132132
else:
133-
feature_names= ['X{}'.format(i)foriinrange(len(model.feature_importances_)) ]
133+
feature_names= ['X{}'.format(i)foriinrange(X_train.shape[1]) ]
134134

135135
imp=permutation_importance(model,X_train,y_train,scoring=scoring)
136136

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