<jupyter_start><jupyter_text>Client Test<jupyter_code>import pandas as pd
import numpy as np
import os
import sys
sys.path.append("../../")
import irsparser as irs
%load_ext autoreload
%autoreload 2
client = irs.Client(
    local_data_dir="../../data", ein_filename="eins",
    index_years=[2018], save_xml=False,
    parser="propublica")
client.parse_xmls(add_organization_info=True)
df = client.getFinalDF()
df.columns
df.head()
df.columns
df.shape
client.error_file#['url'].values
df.describe()
df.min()
df[df.TotalRevenue < 0]['URL'].values<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.15156794425087108, 'fraction_numerical': 0.010452961672473868, 'mean_word_length': 5.927710843373494, 'pattern_counts': {'":': 0, '<': 6, '<?xml version=': 0, '>': 5, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 2}, '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': '617473', 'license': 'BSD-2-Clause', 'n_tokens_mistral': 219, 'n_tokens_neox': 206, 'n_words': 41, 'path': 'Notebooks/Parsing/ClientTest.ipynb', 'repo_name': 'jeremyelster/IRS990', 'size': '574'}