<jupyter_start><jupyter_text>1. All License Issue Year Trends<jupyter_code># getting only active companies in whole license data
active_license = cleaned_license[cleaned_license.license_status == 'Active']
active_license['issue_year'] = active_license['issue_date'].dt.year
years = active_license.groupby('issue_year').size().to_frame('N').reset_index()
years.head()
ax = sns.barplot(x="issue_year", y="N", data=years)
ax.set(xlabel='Issue Year', ylabel='Number of Company')
ax.set_xticklabels(labels=years.issue_year, rotation=45)
plt.show()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.14685314685314685, 'fraction_numerical': 0.005244755244755245, 'mean_word_length': 9.81132075471698, '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': '116801', 'license': 'MIT', 'n_tokens_mistral': 201, 'n_tokens_neox': 192, 'n_words': 34, 'path': 'mwdsbe/Notebooks/By Data/ODP_License/.ipynb_checkpoints/license_issue_year_analysis-checkpoint.ipynb', 'repo_name': 'BinnyDaBin/MWDSBE', 'size': '572'}