merge_machine/abstract_data_project.py
def load_data(self, module_name, file_name, nrows=None, columns=None):
        '''Load data as pandas DataFrame to memory. Overwritten in normalize
        
        Creates two properties for self:
            - mem_data: is a generator which generates pandas DataFrames
            - mem_data_info: contains information on the data currently in memory
            
        INPUT:
            - module_name:
            - file_name:
            - nrows: how many rows to read from the file
            - columns: what columns to load
        '''
        logging.debug('Columns selected to load are: {0}'.format(columns))

        file_path = self.path_to(module_name, file_name)     
        self.mem_data = self._static_load_data(file_path, nrows, columns)
        self.mem_data_info = {'file_name': file_name,
                              'module_name': module_name,
                              'nrows': nrows, 
                              'columns': columns,
                              'data_was_transformed': False}
Load data as pandas DataFrame to memory. Overwritten in normalize
        
        Creates two properties for self:
            - mem_data: is a generator which generates pandas DataFrames
            - mem_data_info: contains information on the data currently in memory
            
        INPUT:
            - module_name:
            - file_name:
            - nrows: how many rows to read from the file
            - columns: what columns to load
        
Load data as pandas DataFrame to memory. Overwritten in normalize
Creates two properties for self:
mem_data: is a generator which generates pandas DataFrames
mem_data_info: contains information on the data currently in memory


Load data as pandas DataFrame to memory . Overwritten in normalize Creates two properties for self : mem_data : is a generator which generates pandas DataFrames mem_data_info : contains information on the data currently in memory
def load_data(self, module_name, file_name, nrows=None, columns=None):
        logging.debug('Columns selected to load are: {0}'.format(columns))
        file_path = self.path_to(module_name, file_name)     
        self.mem_data = self._static_load_data(file_path, nrows, columns)
        self.mem_data_info = {'file_name': file_name,
                              'module_name': module_name,
                              'nrows': nrows, 
                              'columns': columns,
                              'data_was_transformed': False}
def load_data ( self , module_name , file_name , nrows = None , columns = None ) : logging . debug ( 'Columns selected to load are: {0}' . format ( columns ) ) file_path = self . path_to ( module_name , file_name ) self . mem_data = self . _static_load_data ( file_path , nrows , columns ) self . mem_data_info = { 'file_name' : file_name , 'module_name' : module_name , 'nrows' : nrows , 'columns' : columns , 'data_was_transformed' : False }
Load data as pandas DataFrame to memory.
Load data as pandas DataFrame to memory .
'''Load data as pandas DataFrame to memory. Overwritten in normalize
        
        Creates two properties for self:
            - mem_data: is a generator which generates pandas DataFrames
            - mem_data_info: contains information on the data currently in memory
            
        INPUT:
            - module_name:
            - file_name:
            - nrows: how many rows to read from the file
            - columns: what columns to load
        '''
self
module_name
file_name
nrows
columns