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README.md

@@ -2,10 +2,10 @@
 PyCaret is end-to-end open source machine learning library for python programming language. Its primary objective is to reduce the cycle time of hypothesis to insights by providing an easy to use high level unified API. PyCaret's vision is to become defacto standard for teaching machine learning and data science. Our strength is in our easy to use unified interface for both supervised and unsupervised learning. It saves time and effort that citizen data scientists, students and researchers spent on coding or learning to code using different interfaces, so that now they can focus on business problem.
 
 ## Current Release
-The current release is beta 0.0.30 (as of 31/01/2020). A full release is targetted in the first week of February 2020.
+The current release is beta 0.0.31 (as of 01/02/2020). A full release is targetted in the first week of February 2020.
 
 ## Features Currently Available
-As per beta 0.0.30 following modules are generally available:
+As per beta 0.0.31 following modules are generally available:
 * pycaret.datasets <br/>
 * pycaret.classification (binary and multiclass) <br/>
 * pycaret.regression <br/>
@@ -31,7 +31,7 @@ pip install pycaret
 ```
 
 ## Quick Start
-As of beta 0.0.30 classification, regression, nlp, arules, anomaly and clustering modules are available.
+As of beta 0.0.31 classification, regression, nlp, arules, anomaly and clustering modules are available.
 
 ### Classification / Regression
 

classification.py

@@ -403,14 +403,14 @@ def setup(data,
         data_cols = data_cols.drop(target)
         ord_keys = ordinal_features.keys()
                         
-        for k in ord_keys:
-            if len(data[k].unique()) != len(ordinal_features.get(k)):
-                sys.exit("(Value Error) Levels passed in ordinal_features param doesnt match with levels in data. ")
-                
         for i in ord_keys:
             if i not in data_cols:
                 sys.exit("(Value Error) Column name passed as a key in ordinal_features param doesnt exist. ")
                 
+        for k in ord_keys:
+            if len(data[k].unique()) != len(ordinal_features.get(k)):
+                sys.exit("(Value Error) Levels passed in ordinal_features param doesnt match with levels in data. ")
+
         for i in ord_keys:
             value_in_keys = ordinal_features.get(i)
             value_in_data = list(data[i].unique())
@@ -898,9 +898,9 @@ def setup(data,
     #generate values for grid show
     missing_values = data_before_preprocess.isna().sum().sum()
     if missing_values > 0:
-        missing_flag = 'True'
+        missing_flag = True
     else:
-        missing_flag = 'False'
+        missing_flag = False
     
     if normalize is True:
         normalize_grid = normalize_method
@@ -928,9 +928,9 @@ def setup(data,
         rare_level_threshold_grid = 'None'
     
     if bin_numeric_features is None:
-        numeric_bin_grid = 'False'
+        numeric_bin_grid = False
     else:
-        numeric_bin_grid = 'True'
+        numeric_bin_grid = True
     
     if remove_outliers is False:
         outliers_threshold_grid = None
@@ -977,6 +977,11 @@ def setup(data,
     else:
         unknown_categorical_method_grid = None
     
+    if group_features is not None:
+        group_features_grid = True
+    else:
+        group_features_grid = False
+    
     learned_types = preprocess.dtypes.learent_dtypes
     learned_types.drop(target, inplace=True)
 
@@ -1226,7 +1231,7 @@ def setup(data,
                                          ['Polynomial Degree ', polynomial_degree_grid], #new
                                          ['Trignometry Features ', trigonometry_features], #new
                                          ['Polynomial Threshold ', polynomial_threshold_grid], #new
-                                         ['Group Features ', group_features], #new
+                                         ['Group Features ', group_features_grid], #new
                                          ['Feature Selection ', feature_selection], #new
                                          ['Features Selection Threshold ', feature_selection_threshold_grid], #new
                                          ['Feature Interaction ', feature_interaction], #new
@@ -1318,7 +1323,7 @@ def setup(data,
                                          ['Polynomial Degree ', polynomial_degree_grid], #new
                                          ['Trignometry Features ', trigonometry_features], #new
                                          ['Polynomial Threshold ', polynomial_threshold_grid], #new
-                                         ['Group Features ', group_features], #new
+                                         ['Group Features ', group_features_grid], #new
                                          ['Feature Selection ', feature_selection], #new
                                          ['Features Selection Threshold ', feature_selection_threshold_grid], #new
                                          ['Feature Interaction ', feature_interaction], #new
@@ -1406,7 +1411,7 @@ def setup(data,
                                      ['Polynomial Degree ', polynomial_degree_grid], #new
                                      ['Trignometry Features ', trigonometry_features], #new
                                      ['Polynomial Threshold ', polynomial_threshold_grid], #new
-                                     ['Group Features ', group_features], #new
+                                     ['Group Features ', group_features_grid], #new
                                      ['Feature Selection ', feature_selection], #new
                                      ['Features Selection Threshold ', feature_selection_threshold_grid], #new
                                      ['Feature Interaction ', feature_interaction], #new
@@ -1444,7 +1449,6 @@ def setup(data,
 
 
 
-
 def create_model(estimator = None, 
                  ensemble = False, 
                  method = None, 

regression.py

@@ -3,6 +3,8 @@
 # License: MIT
 
 
+
+
 def setup(data, 
           target, 
           train_size=0.7,
@@ -412,14 +414,14 @@ def setup(data,
         data_cols = data_cols.drop(target)
         ord_keys = ordinal_features.keys()
         
-        for k in ord_keys:
-            if len(data[k].unique()) != len(ordinal_features.get(k)):
-                sys.exit("(Value Error) Levels passed in ordinal_features param doesnt match with levels in data. ")
-
         for i in ord_keys:
             if i not in data_cols:
                 sys.exit("(Value Error) Column name passed as a key in ordinal_features param doesnt exist. ")
                 
+        for k in ord_keys:
+            if len(data[k].unique()) != len(ordinal_features.get(k)):
+                sys.exit("(Value Error) Levels passed in ordinal_features param doesnt match with levels in data. ")
+
         for i in ord_keys:
             value_in_keys = ordinal_features.get(i)
             value_in_data = list(data[i].unique())
@@ -932,9 +934,9 @@ def setup(data,
     #generate values for grid show
     missing_values = data_before_preprocess.isna().sum().sum()
     if missing_values > 0:
-        missing_flag = 'True'
+        missing_flag = True
     else:
-        missing_flag = 'False'
+        missing_flag = False
     
     if normalize is True:
         normalize_grid = normalize_method
@@ -962,9 +964,9 @@ def setup(data,
         rare_level_threshold_grid = 'None'
     
     if bin_numeric_features is None:
-        numeric_bin_grid = 'False'
+        numeric_bin_grid = False
     else:
-        numeric_bin_grid = 'True'
+        numeric_bin_grid = True
     
     if remove_outliers is False:
         outliers_threshold_grid = None
@@ -1011,6 +1013,11 @@ def setup(data,
     else:
         unknown_categorical_method_grid = None
        
+    if group_features is not None:
+        group_features_grid = True
+    else:
+        group_features_grid = False
+        
     learned_types = preprocess.dtypes.learent_dtypes
     learned_types.drop(target, inplace=True)
 
@@ -1205,7 +1212,7 @@ def setup(data,
                                          ['Polynomial Degree ', polynomial_degree_grid], #new
                                          ['Trignometry Features ', trigonometry_features], #new
                                          ['Polynomial Threshold ', polynomial_threshold_grid], #new
-                                         ['Group Features ', group_features], #new
+                                         ['Group Features ', group_features_grid], #new
                                          ['Feature Selection ', feature_selection], #new
                                          ['Features Selection Threshold ', feature_selection_threshold_grid], #new
                                          ['Feature Interaction ', feature_interaction], #new
@@ -1301,7 +1308,7 @@ def setup(data,
                                          ['Polynomial Degree ', polynomial_degree_grid], #new
                                          ['Trignometry Features ', trigonometry_features], #new
                                          ['Polynomial Threshold ', polynomial_threshold_grid], #new
-                                         ['Group Features ', group_features], #new
+                                         ['Group Features ', group_features_grid], #new
                                          ['Feature Selection ', feature_selection], #new
                                          ['Features Selection Threshold ', feature_selection_threshold_grid], #new
                                          ['Feature Interaction ', feature_interaction], #new
@@ -1392,7 +1399,7 @@ def setup(data,
                                      ['Polynomial Degree ', polynomial_degree_grid], #new
                                      ['Trignometry Features ', trigonometry_features], #new
                                      ['Polynomial Threshold ', polynomial_threshold_grid], #new
-                                     ['Group Features ', group_features], #new
+                                     ['Group Features ', group_features_grid], #new
                                      ['Feature Selection ', feature_selection], #new
                                      ['Features Selection Threshold ', feature_selection_threshold_grid], #new
                                      ['Feature Interaction ', feature_interaction], #new
@@ -1435,7 +1442,6 @@ def setup(data,
 
 
 
-
 def create_model(estimator = None, 
                  ensemble = False, 
                  method = None, 

setup.py

@@ -27,7 +27,7 @@ def readme():
 
 setup(
     name="pycaret",
-    version="0.0.30",
+    version="0.0.31",
     description="A Python package for supervised and unsupervised machine learning.",
     long_description=readme(),
     long_description_content_type="text/markdown",