Add files via upload

README.md

-## Welcome to PyCaret !
+## Welcome to PyCaret!
 PyCaret is a free software and an open source low-code machine learning library for supervised and unsupervised machine learning techniques in Python programming language. Its primary objective is to reduce the cycle time from hypothesis to insights and make data scientists more productive in their experiments. It does so by providing a high-level API which is sophisticated yet easy to use and consistent across all modules. PyCaret enables data scientists and analysts to perform iterative end-to-end data science experiments in very efficient way allowing them to reach the conclusions faster. Through the use of its high-level low-code API, the amount of time spent in coding experiments reduce drastically, allowing business to restructure their machine learning workflows and re-evaluate the value chain of data science projects. PyCaret is essentially a python wrapper around several machine learning frameworks and libraries such as scikit-learn, XGBoost, Microsoft LightGBM, spaCy to name a few.
 
 ___
 
 ## Current Release
-The current release is beta 0.0.36 (as of 07/02/2020). A full public release is expected by end of Feb 2020. 
+The current release is beta 0.0.37 (as of 08/02/2020). A full public release is expected by end of Feb 2020. 
 
 ___
 

anomaly.py

@@ -303,7 +303,7 @@ def setup(data,
                 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)):
+            if data[k].nunique() != 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:

classification.py

@@ -428,7 +428,7 @@ def setup(data,
                 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)):
+            if data[k].nunique() != 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:

clustering.py

@@ -304,7 +304,7 @@ def setup(data,
                 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)):
+            if data[k].nunique() != 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:

regression.py

@@ -436,7 +436,7 @@ def setup(data,
                 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)):
+            if data[k].nunique() != 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:

setup.py

@@ -27,7 +27,7 @@ def readme():
 
 setup(
     name="pycaret",
-    version="0.0.36",
+    version="0.0.37",
     description="A Python package for supervised and unsupervised machine learning.",
     long_description=readme(),
     long_description_content_type="text/markdown",