Merge pull request #17 from dataiku/fix/webapp-document-references

tmwly · web-flow · commit 81b2773e2354 · 2025-12-12T11:44:14.000+01:00
Bundle JQuery, update angularjs
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -1,5 +1,11 @@
 # Changelog
 
+## Version 1.1.3 (2025-12-10)
+* Bump angularjs to 1.8.2
+* Include jquery in plugin resources, rather than relying on angularjs jquerylite
+* Fix js NPE when checking non-numeric values
+
+
 ## Version 1.1.2 (2025-05-14)
 * Fix issue with webapp not displaying correctly
 * Fix bug in pandas > 2
diff --git a/plugin.json b/plugin.json
@@ -1,10 +1,10 @@
 {
   "id" : "decision-tree-builder",
-  "version" : "1.1.2",
+  "version" : "1.1.3",
   "meta" : {
     "label" : "Interactive Decision Tree Builder",
     "description" : "Build and explore decision trees, and use them to score and evaluate data",
-    "author" : "Dataiku (Agathe Guillemot)",
+    "author" : "Dataiku (Créml Brûlée)",
     "supportLevel": "TIER2_SUPPORT",
     "icon" : "icon-sitemap",
     "licenseInfo" : "Apache Software License",
diff --git a/python-lib/dku_idtb_decision_tree/autosplit.py b/python-lib/dku_idtb_decision_tree/autosplit.py
@@ -1,10 +1,10 @@
 import math
 import pandas as pd
 from sklearn.tree import _tree, DecisionTreeClassifier
-from dku_idtb_compatibility.utils import safe_str
+
 
 def apply_cross_entropy(population):
-    return lambda sample: pd.Series(cross_entropy(population, sample), index=sample.index)
+    return lambda sample: cross_entropy(population, sample)
 
 def cross_entropy(population_distrib, sample):
     sample_distrib = sample.value_counts(normalize=True)
@@ -15,8 +15,8 @@ def cross_entropy(population_distrib, sample):
 
 def convert_categorical_columns(feature_col, target_col):
     target_distrib = target_col.value_counts(normalize=True)
-    entropies = target_col.groupby(feature_col).apply(apply_cross_entropy(target_distrib))
-    return entropies.sort_index().reset_index(drop=True)
+    entropies_by_category = target_col.groupby(feature_col).apply(apply_cross_entropy(target_distrib))
+    return feature_col.map(entropies_by_category)
 
 
 def autosplit(df, feature, target, numerical, max_splits):
diff --git a/resource/angular.min.js b/resource/angular.min.js
diff --git a/resource/jquery.min.js b/resource/jquery.min.js
diff --git a/resource/js/helpers.js b/resource/js/helpers.js
@@ -9,6 +9,9 @@ app.service("Format", function() {
             return text;
         },
         toFixedIfNeeded: function(number, decimals) {
+            if (number == null) {
+                return "";
+            }
             if(Math.round(number) !== number) {
                 return number.toFixed(decimals);
             }
diff --git a/webapps/interactive-decision-tree-builder/body.html b/webapps/interactive-decision-tree-builder/body.html
@@ -1,6 +1,7 @@
 <!DOCTYPE html>
 <html lang="en">
 <head>
+    <script src="/plugins/decision-tree-builder/resource/jquery.min.js" type="text/javascript"></script>
     <script src="/plugins/decision-tree-builder/resource/angular.min.js" type="text/javascript"></script>
     <script src="/plugins/decision-tree-builder/resource/spin.min.js" type="text/javascript"></script>
     <script type="text/javascript">
