<jupyter_start><jupyter_text>NAV open data | Employment ads<jupyter_code>import sys
import pandas as pd
import os
%load_ext autoreload
%autoreload 2
from src.data import make_work_ads_data_set<jupyter_output><empty_output><jupyter_text>Fetch data from data API endpoint<jupyter_code>filepath = make_work_ads_data_set.make_data_set_for_year(2017, "test_data.csv")
test_df = pd.read_csv(filepath, sep=';', index_col='stillingsnummer')
test_df.info()
test_df.arbeidssted_fylke.value_counts()
test_df.arbeidssted_fylke.value_counts().plot("bar");<jupyter_output><empty_output><jupyter_text>Reasonable errors for data fetching<jupyter_code>filepath = make_arbeid_dataset.make_nav_work_dataset_for_year(2329391239, "2016-test_data.csv")<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1013157894736842, 'fraction_numerical': 0.025, 'mean_word_length': 12.350877192982455, 'pattern_counts': {'":': 0, '<': 13, '<?xml version=': 0, '>': 13, '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': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '421352', 'license': 'MIT', 'n_tokens_mistral': 310, 'n_tokens_neox': 293, 'n_words': 40, 'path': 'notebooks/1.0-sonhal-fun-with-open-datasets.ipynb', 'repo_name': 'sonhal/open-data', 'size': '760'}