<jupyter_start><jupyter_text><jupyter_code>import pandas as pd
!wget 'https://raw.githubusercontent.com/unburied/DiY-Help/master/Help%20Section%20Articles-February%2013%2C%202020%20(1).csv' 
# Load data and confirm shape equates to web scraped export
data ='Help Section Articles-February 13, 2020 (1).csv'
df = pd.read_csv(data)

assert df.shape == (427,4)
import unicodedata as uc

# clean content data
def normaled_unicode(x):
  return uc.normalize('NFKD', str(x))
df['content'] = df.content.apply(normaled_unicode)

# get word count to output
def word_count(x):
  return len(x.split())
df['word_count'] = df.content.apply(word_count)
VERBOSE = 75

result = df[df.word_count > VERBOSE]
result.tail()
from datetime import date

today = date.today()
today = today.strftime("%B %d, %Y")

file_name = 'Word Counts' + today + '.csv'

result.to_csv(file_name, index = False)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.14095449500554938, 'fraction_numerical': 0.03440621531631521, 'mean_word_length': 5.833333333333333, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 6, 'https://': 1, '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': '268495', 'license': 'MIT', 'n_tokens_mistral': 366, 'n_tokens_neox': 328, 'n_words': 77, 'path': 'DiY_HelpSection_Eda.ipynb', 'repo_name': 'unburied/DiY-Help', 'size': '901'}