diff --git a/build/lib/pycaret/datasets.py b/build/lib/pycaret/datasets.py
deleted file mode 100644
index a3f5f7acb99f89825d31c3f20b643b2baf82fee1..0000000000000000000000000000000000000000
--- a/build/lib/pycaret/datasets.py
+++ /dev/null
@@ -1,84 +0,0 @@
-# Module: Datasets
-# Author: Moez Ali <moez.ali@queensu.ca>
-# License: MIT
-
-
-def get_data(dataset, save_copy=False, profile=False, verbose=True):
-    
-    """
-      
-    Description:
-    ------------
-    This function loads sample datasets that are available in the pycaret git 
-    repository. The full list of available datasets and their descriptions can
-    be viewed by calling index.
-
-        Example
-        -------
-        data = get_data('index')
-
-        This will display the list of available datasets that can be loaded 
-        using the get_data() function. For example, to load the credit dataset:
-        
-        credit = get_data('credit')
-        
-    Parameters
-    ----------
-    dataset : string 
-    index value of dataset
-    
-    save_copy : bool, default = False
-    When set to true, it saves a copy of the dataset to your local active directory.
-    
-    profile: bool, default = False
-    If set to true, a data profile for Exploratory Data Analysis will be displayed 
-    in an interactive HTML report. 
-
-    verbose: bool, default = True
-    When set to False, head of data is not displayed.
-    
-    Returns:
-    --------
-
-    DataFrame:    Pandas dataframe is returned. 
-    ----------      
-
-    Warnings:
-    ---------
-    - Use of get_data() requires internet connection.
-      
-         
-    """
-    
-    import pandas as pd
-    from IPython.display import display, HTML, clear_output, update_display
-    
-    address = 'https://raw.githubusercontent.com/pycaret/pycaret/master/datasets/'
-    extension = '.csv'
-    filename = dataset
-    
-    complete_address = address + str(dataset) + extension
-    
-    data = pd.read_csv(complete_address)
-    
-    #create a copy for pandas profiler
-    data_for_profiling = data.copy()
-    
-    if save_copy:
-        save_name = str(dataset) + str(extension)
-        data.to_csv(save_name)
-        
-    if dataset == 'index':
-        display(data)
-    
-    else:
-        if profile:
-            import pandas_profiling
-            pf = pandas_profiling.ProfileReport(data_for_profiling)
-            display(pf)
-            
-        else:
-            if verbose:
-                display(data.head())
-        
-    return data
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