<jupyter_start><jupyter_text>DBWheels_read.py Small add-on that helps read in data from excel. There are currently 8 methods implemented to read in: sets, subsets, mappings, variables, parameters, scalar variables, scalar parameters, and one method for reading 2d variables arranged in separate sheets. The data should be arranged as in the file 'DBWheels_read.xlsx'. We specify how the data is read by adding key = type of function we use to read in and values = list of sheets to apply the given function on.<jupyter_code>readlike = {'sets': ['sheet_sets'], 
            'subsets': ['sheet_subsets'],
            'variables': ['sheet_variables'],
            'parameters': ['sheet_parameters'],
            'scalar_variables': ['sheet_scalar_variables'],
            'scalar_parameters': ['sheet_scalar_parameters'],
            'variable2D': ['sheet_variable2D']}<jupyter_output><empty_output><jupyter_text>The following statement creates a ```Database.SeriesDB``` database instance with the symbols that are declared in the excel file. Note that if a symbol is declared in multiple sheets, they will be merged using this function:<jupyter_code>dbSeries =  SeriesDB_from_wb(d['data']+'\\DBWheels_read.xlsx',readlike)<jupyter_output><empty_output><jupyter_text>The resulting symbols can then be accessed:<jupyter_code>'_'.join(['a'])
dbSeries.database<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.09978308026030369, 'fraction_numerical': 0.0028922631959508315, 'mean_word_length': 5.123893805309734, 'pattern_counts': {'":': 0, '<': 13, '<?xml version=': 0, '>': 13, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '471882', 'license': 'MIT', 'n_tokens_mistral': 385, 'n_tokens_neox': 378, 'n_words': 134, 'path': 'Wheels_read.ipynb', 'repo_name': 'ChampionApe/GPM_v06', 'size': '1383'}