def get_categories(file_path):
records = ETLUtils.load_json_file(file_path)
# Now we obtain the categories for all the businesses
records = ETLUtils.add_transpose_list_column('categories', records)
BusinessETL.drop_unwanted_fields(records)
return records[0].keys()
def get_categories(file_path):
records = ETLUtils.load_json_file(file_path)
# Now we obtain the categories for all the businesses
records = ETLUtils.add_transpose_list_column('categories', records)
BusinessETL.drop_unwanted_fields(records)
return records[0].keys()
def create_category_matrix(file_path):
"""
Creates a matrix with all the categories for businesses that are
contained in the Yelp Phoenix Business data set. Each column of the
matrix represents a category, and each row a business. This is a binary
matrix that contains a 1 at the position i,j if the business i contains
the category j, and a 0 otherwise.
:rtype : numpy array matrix
:param file_path: the path for the file that contains the businesses
data
:return: a numpy array binary matrix
"""
records = ETLUtils.load_json_file(file_path)
# Now we obtain the categories for all the businesses
records = ETLUtils.add_transpose_list_column('categories', records)
BusinessETL.drop_unwanted_fields(records)
matrix = numpy.array(
[numpy.array(record.values()) for record in records])
return matrix
def create_category_matrix(file_path):
"""
Creates a matrix with all the categories for businesses that are
contained in the Yelp Phoenix Business data set. Each column of the
matrix represents a category, and each row a business. This is a binary
matrix that contains a 1 at the position i,j if the business i contains
the category j, and a 0 otherwise.
:rtype : numpy array matrix
:param file_path: the path for the file that contains the businesses
data
:return: a numpy array binary matrix
"""
records = ETLUtils.load_json_file(file_path)
# Now we obtain the categories for all the businesses
records = ETLUtils.add_transpose_list_column('categories', records)
BusinessETL.drop_unwanted_fields(records)
matrix = numpy.array(
[numpy.array(record.values()) for record in records])
return matrix
