| # === Analyze Oregon lab results === | |
| # # Visualize market share by lab by month as a timeseries. | |
| # market_share = results.groupby(['month', 'lab_id']).size().unstack().fillna(0) | |
| # market_share = market_share.div(market_share.sum(axis=1), axis=0) | |
| # market_share.plot.area( | |
| # title='Market Share by Lab by Month in Oregon', | |
| # figsize=(13, 8), | |
| # legend=None, | |
| # ) | |
| # plt.xlabel('') | |
| # plt.savefig(f'{assets_dir}/or-market-share-by-lab-by-month.png', dpi=300, bbox_inches='tight', transparent=False) | |
| # plt.show() | |
| # # Visualize tests per capita by month. | |
| # or_population = { | |
| # 2023: 4_233_358, | |
| # 2022: 4_239_379, | |
| # 2021: 4_256_465, | |
| # 2020: 4_245_044, | |
| # 2019: 4_216_116, | |
| # } | |
| # results['year'] = results['date'].dt.year | |
| # results['population'] = results['year'].map(or_population) | |
| # fig, ax = plt.subplots(figsize=(13, 8)) | |
| # or_tests_per_capita = results.groupby('month').size() / (results.groupby('month')['population'].first() / 100_000) | |
| # or_tests_per_capita.plot(ax=ax, title='Cannabis Tests per 100,000 People by Month in Oregon') | |
| # ax.set_ylabel('Tests per 100,000 People') | |
| # plt.show() | |
| # # Visualize average total THC by month over time. | |
| # results['total_thc'] = results['total_thc'].astype(float) | |
| # average_total_thc = results.groupby('month')['total_thc'].mean() | |
| # fig, ax = plt.subplots(figsize=(13, 8)) | |
| # average_total_thc.index = average_total_thc.index.to_timestamp() | |
| # ax.plot(average_total_thc.index, average_total_thc.values, label='Monthly Average Total THC', color='royalblue', lw=5) | |
| # ax.scatter(results['date'], results['total_thc'], color='royalblue', s=10, alpha=0.5, label='Daily Individual Results') | |
| # ax.set_xlabel('') | |
| # ax.set_ylabel('Total THC (%)') | |
| # ax.set_title('Average Total THC by Month in Oregon') | |
| # ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m')) | |
| # ax.xaxis.set_major_locator(mdates.MonthLocator((1,4,7,10))) | |
| # plt.xticks(rotation=45) | |
| # plt.ylim(0, 45) | |
| # plt.savefig(f'{assets_dir}/or-total-thc.png', dpi=300, bbox_inches='tight', transparent=False) | |
| # plt.show() | |
| # # Visualize average total CBD by month over time. | |
| # results['total_cbd'] = results['total_cbd'].astype(float) | |
| # sample = results.loc[results['total_cbd'] < 1] | |
| # average_total_cbd = sample.groupby('month')['total_cbd'].mean() | |
| # fig, ax = plt.subplots(figsize=(13, 8)) | |
| # average_total_cbd.index = average_total_cbd.index.to_timestamp() | |
| # ax.plot(average_total_cbd.index, average_total_cbd.values, label='Monthly Average Total CBD', color='royalblue', lw=5) | |
| # ax.scatter(sample['date'], sample['total_cbd'], color='royalblue', s=10, alpha=0.5, label='Daily Individual Results') | |
| # ax.set_xlabel('') | |
| # ax.set_ylabel('Total CBD (%)') | |
| # ax.set_title('Average Total CBD by Month in Oregon in Low CBD Samples (<1%)') | |
| # ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m')) | |
| # ax.xaxis.set_major_locator(mdates.MonthLocator((1,4,7,10))) | |
| # plt.xticks(rotation=45) | |
| # plt.ylim(0, 0.75) | |
| # plt.savefig(f'{assets_dir}/or-total-cbd.png', dpi=300, bbox_inches='tight', transparent=False) | |
| # plt.show() |