<jupyter_start><jupyter_text>The percent above should multiply 100! We can see the first 6 columns have too much of missing values. We can drop them from our RVD (the ChangeData table will never be modified: all the actions are only on our RVD).<jupyter_code># Drop table in database if it exists
drop_table("cm3rm1",cur)

# Read CSV data
cm3rm1=read_csv('../datasets/cm3rm1.csv',cur)
cm3rm1
# Read CSV data
cm4rm1=read_csv('../datasets/cm4rm1.csv',cur)
cm4rm1.describe()
# Read CSV data
cicm4r=read_csv('../datasets/cicm4r.csv',cur)
cicm4r.describe()
print (cicm4r)
cm3rm1.count()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.11292962356792144, 'fraction_numerical': 0.03927986906710311, 'mean_word_length': 5.725274725274725, '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': '652637', 'license': 'Apache-2.0', 'n_tokens_mistral': 241, 'n_tokens_neox': 230, 'n_words': 67, 'path': 'notebooks/SmartChange_MergeData.ipynb', 'repo_name': 'wangjin2000/Vertica-ML-Python', 'size': '611'}