<jupyter_start><jupyter_text>Load CSV<jupyter_code>dicFile = 'enron_small_dic.csv'

csvLoader = sqlContext.read.format('com.databricks.spark.csv')
dic = csvLoader.options(delimiter='\t', header='false', inferschema='true').load(dicFile)
dic = dic.select(dic['C0'].alias('id'), dic['C1'].alias('word'), dic['C2'].alias('count'))
dic.columns
dic1<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.20588235294117646, 'fraction_numerical': 0.0106951871657754, 'mean_word_length': 10.029411764705882, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, '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': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '502606', 'license': 'Apache-2.0', 'n_tokens_mistral': 155, 'n_tokens_neox': 149, 'n_words': 15, 'path': 'Avro loading data.ipynb', 'repo_name': 'nlesc-sherlock/corpora-vis', 'size': '374'}