<jupyter_start><jupyter_text>Data Cleaning SourceWhere did the data come from? Domain or prior knowledge about the dataThis would be a great place to include the data dictionary if one is available.--- Imports and defined functions<jupyter_code>import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import datetime as dt
from scipy import stats


pd.options.display.float_format = '{:.3f}'.format
sns.set_theme(style='whitegrid', palette='colorblind', font=1.5, color_codes=True)
# Defined functions go here
# Import the data here...<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.07807308970099668, 'fraction_numerical': 0.0049833887043189366, 'mean_word_length': 5.7, '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': '550362', 'license': 'Apache-2.0', 'n_tokens_mistral': 184, 'n_tokens_neox': 178, 'n_words': 70, 'path': 'Data Cleaning.ipynb', 'repo_name': 'owenhw/flood_risk', 'size': '602'}