From f89551daf00716290c1c8d33ed84c0c6e05a10f2 Mon Sep 17 00:00:00 2001 From: John Vivian Date: Tue, 2 Jan 2024 18:25:25 -0800 Subject: [PATCH 1/8] Update data files --- .../raw/economic/consumption/consumption.csv | 13202 ++++++++-------- .../consumption_durable_goods.csv | 13202 ++++++++-------- .../consumption_nondurable_goods.csv | 13202 ++++++++-------- .../consumption_services.csv | 13202 ++++++++-------- .../consumption_total_goods.csv | 13202 ++++++++-------- .../JHU_case_output.csv | 1973 +++ ...ited_States_Jurisdiction_output_output.csv | 13202 ++++++++-------- 7 files changed, 41579 insertions(+), 39606 deletions(-) create mode 100644 covid19_drdfm/data/raw/pandemic/cases/JHU_ cases_time_series/JHU_case_output.csv diff --git a/covid19_drdfm/data/raw/economic/consumption/consumption.csv b/covid19_drdfm/data/raw/economic/consumption/consumption.csv index df06943..88207e6 100644 --- a/covid19_drdfm/data/raw/economic/consumption/consumption.csv +++ 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-NJ,2015,M06,396817.3 -NJ,2015,M07,397594.0667 -NJ,2015,M08,398370.8333 -NJ,2015,M09,399147.6 -NJ,2015,M10,399924.3667 -NJ,2015,M11,400701.1333 -NJ,2015,M12,401477.9 -NJ,2016,M01,402389.825 -NJ,2016,M02,403301.75 -NJ,2016,M03,404213.675 -NJ,2016,M04,405125.6 -NJ,2016,M05,406037.525 -NJ,2016,M06,406949.45 -NJ,2016,M07,407861.375 -NJ,2016,M08,408773.3 -NJ,2016,M09,409685.225 -NJ,2016,M10,410597.15 -NJ,2016,M11,411509.075 -NJ,2016,M12,412421 -NJ,2017,M01,413326.6083 -NJ,2017,M02,414232.2167 -NJ,2017,M03,415137.825 -NJ,2017,M04,416043.4333 -NJ,2017,M05,416949.0417 -NJ,2017,M06,417854.65 -NJ,2017,M07,418760.2583 -NJ,2017,M08,419665.8667 -NJ,2017,M09,420571.475 -NJ,2017,M10,421477.0833 -NJ,2017,M11,422382.6917 -NJ,2017,M12,423288.3 -NJ,2018,M01,424951.2583 -NJ,2018,M02,426614.2167 -NJ,2018,M03,428277.175 -NJ,2018,M04,429940.1333 -NJ,2018,M05,431603.0917 -NJ,2018,M06,433266.05 -NJ,2018,M07,434929.0083 -NJ,2018,M08,436591.9667 -NJ,2018,M09,438254.925 -NJ,2018,M10,439917.8833 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-NH,2015,M11,42234.71667 -NH,2015,M12,42396.9 -NH,2016,M01,42553.775 -NH,2016,M02,42710.65 -NH,2016,M03,42867.525 -NH,2016,M04,43024.4 -NH,2016,M05,43181.275 -NH,2016,M06,43338.15 -NH,2016,M07,43495.025 -NH,2016,M08,43651.9 -NH,2016,M09,43808.775 -NH,2016,M10,43965.65 -NH,2016,M11,44122.525 -NH,2016,M12,44279.4 -NH,2017,M01,44450.65833 -NH,2017,M02,44621.91667 -NH,2017,M03,44793.175 -NH,2017,M04,44964.43333 -NH,2017,M05,45135.69167 -NH,2017,M06,45306.95 -NH,2017,M07,45478.20833 -NH,2017,M08,45649.46667 -NH,2017,M09,45820.725 -NH,2017,M10,45991.98333 -NH,2017,M11,46163.24167 -NH,2017,M12,46334.5 -NH,2018,M01,46525.75 -NH,2018,M02,46717 -NH,2018,M03,46908.25 -NH,2018,M04,47099.5 -NH,2018,M05,47290.75 -NH,2018,M06,47482 -NH,2018,M07,47673.25 -NH,2018,M08,47864.5 -NH,2018,M09,48055.75 -NH,2018,M10,48247 -NH,2018,M11,48438.25 -NH,2018,M12,48629.5 -NH,2019,M01,48786.075 -NH,2019,M02,48942.65 -NH,2019,M03,49099.225 -NH,2019,M04,49255.8 -NH,2019,M05,49412.375 -NH,2019,M06,49568.95 -NH,2019,M07,49725.525 -NH,2019,M08,49882.1 -NH,2019,M09,50038.675 -NH,2019,M10,50195.25 -NH,2019,M11,50351.825 -NH,2019,M12,50508.4 -NH,2020,M01,50358.64167 -NH,2020,M02,50208.88333 -NH,2020,M03,50059.125 -NH,2020,M04,49909.36667 -NH,2020,M05,49759.60833 -NH,2020,M06,49609.85 -NH,2020,M07,49460.09167 -NH,2020,M08,49310.33333 -NH,2020,M09,49160.575 -NH,2020,M10,49010.81667 -NH,2020,M11,48861.05833 -NH,2020,M12,48711.3 -NH,2021,M01,49035.575 -NH,2021,M02,49359.85 -NH,2021,M03,49684.125 -NH,2021,M04,50008.4 -NH,2021,M05,50332.675 -NH,2021,M06,50656.95 -NH,2021,M07,50981.225 -NH,2021,M08,51305.5 -NH,2021,M09,51629.775 -NH,2021,M10,51954.05 -NH,2021,M11,52278.325 -NH,2021,M12,52602.6 -NH,2022,M01,NA -NH,2022,M02,NA -NH,2022,M03,NA -NH,2022,M04,NA -NH,2022,M05,NA -NH,2022,M06,NA -NH,2022,M07,NA -NH,2022,M08,NA -NH,2022,M09,NA -NH,2022,M10,NA -NH,2022,M11,NA -NH,2022,M12,NA -NJ,2012,M01,245449.3083 -NJ,2012,M02,246121.2167 -NJ,2012,M03,246793.125 -NJ,2012,M04,247465.0333 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-NH,2021,M05,23991.43333 -NH,2021,M06,24305.7 -NH,2021,M07,24619.96667 -NH,2021,M08,24934.23333 -NH,2021,M09,25248.5 -NH,2021,M10,25562.76667 -NH,2021,M11,25877.03333 -NH,2021,M12,26191.3 -NH,2022,M01,NA -NH,2022,M02,NA -NH,2022,M03,NA -NH,2022,M04,NA -NH,2022,M05,NA -NH,2022,M06,NA -NH,2022,M07,NA -NH,2022,M08,NA -NH,2022,M09,NA -NH,2022,M10,NA -NH,2022,M11,NA -NH,2022,M12,NA -NJ,2012,M01,117166.8917 -NJ,2012,M02,117368.2833 -NJ,2012,M03,117569.675 -NJ,2012,M04,117771.0667 -NJ,2012,M05,117972.4583 -NJ,2012,M06,118173.85 -NJ,2012,M07,118375.2417 -NJ,2012,M08,118576.6333 -NJ,2012,M09,118778.025 -NJ,2012,M10,118979.4167 -NJ,2012,M11,119180.8083 -NJ,2012,M12,119382.2 -NJ,2013,M01,119591.975 -NJ,2013,M02,119801.75 -NJ,2013,M03,120011.525 -NJ,2013,M04,120221.3 -NJ,2013,M05,120431.075 -NJ,2013,M06,120640.85 -NJ,2013,M07,120850.625 -NJ,2013,M08,121060.4 -NJ,2013,M09,121270.175 -NJ,2013,M10,121479.95 -NJ,2013,M11,121689.725 -NJ,2013,M12,121899.5 -NJ,2014,M01,122152.05 -NJ,2014,M02,122404.6 -NJ,2014,M03,122657.15 -NJ,2014,M04,122909.7 -NJ,2014,M05,123162.25 -NJ,2014,M06,123414.8 -NJ,2014,M07,123667.35 -NJ,2014,M08,123919.9 -NJ,2014,M09,124172.45 -NJ,2014,M10,124425 -NJ,2014,M11,124677.55 -NJ,2014,M12,124930.1 -NJ,2015,M01,125044.1167 -NJ,2015,M02,125158.1333 -NJ,2015,M03,125272.15 -NJ,2015,M04,125386.1667 -NJ,2015,M05,125500.1833 -NJ,2015,M06,125614.2 -NJ,2015,M07,125728.2167 -NJ,2015,M08,125842.2333 -NJ,2015,M09,125956.25 -NJ,2015,M10,126070.2667 -NJ,2015,M11,126184.2833 -NJ,2015,M12,126298.3 -NJ,2016,M01,126342.2833 -NJ,2016,M02,126386.2667 -NJ,2016,M03,126430.25 -NJ,2016,M04,126474.2333 -NJ,2016,M05,126518.2167 -NJ,2016,M06,126562.2 -NJ,2016,M07,126606.1833 -NJ,2016,M08,126650.1667 -NJ,2016,M09,126694.15 -NJ,2016,M10,126738.1333 -NJ,2016,M11,126782.1167 -NJ,2016,M12,126826.1 -NJ,2017,M01,127080.8333 -NJ,2017,M02,127335.5667 -NJ,2017,M03,127590.3 -NJ,2017,M04,127845.0333 -NJ,2017,M05,128099.7667 -NJ,2017,M06,128354.5 -NJ,2017,M07,128609.2333 -NJ,2017,M08,128863.9667 -NJ,2017,M09,129118.7 -NJ,2017,M10,129373.4333 -NJ,2017,M11,129628.1667 -NJ,2017,M12,129882.9 -NJ,2018,M01,130272.95 -NJ,2018,M02,130663 -NJ,2018,M03,131053.05 -NJ,2018,M04,131443.1 -NJ,2018,M05,131833.15 -NJ,2018,M06,132223.2 -NJ,2018,M07,132613.25 -NJ,2018,M08,133003.3 -NJ,2018,M09,133393.35 -NJ,2018,M10,133783.4 -NJ,2018,M11,134173.45 -NJ,2018,M12,134563.5 -NJ,2019,M01,134994.075 -NJ,2019,M02,135424.65 -NJ,2019,M03,135855.225 -NJ,2019,M04,136285.8 -NJ,2019,M05,136716.375 -NJ,2019,M06,137146.95 -NJ,2019,M07,137577.525 -NJ,2019,M08,138008.1 -NJ,2019,M09,138438.675 -NJ,2019,M10,138869.25 -NJ,2019,M11,139299.825 -NJ,2019,M12,139730.4 -NJ,2020,M01,139960.5833 -NJ,2020,M02,140190.7667 -NJ,2020,M03,140420.95 -NJ,2020,M04,140651.1333 -NJ,2020,M05,140881.3167 -NJ,2020,M06,141111.5 -NJ,2020,M07,141341.6833 -NJ,2020,M08,141571.8667 -NJ,2020,M09,141802.05 -NJ,2020,M10,142032.2333 -NJ,2020,M11,142262.4167 -NJ,2020,M12,142492.6 -NJ,2021,M01,144855.4333 -NJ,2021,M02,147218.2667 -NJ,2021,M03,149581.1 -NJ,2021,M04,151943.9333 -NJ,2021,M05,154306.7667 -NJ,2021,M06,156669.6 -NJ,2021,M07,159032.4333 -NJ,2021,M08,161395.2667 -NJ,2021,M09,163758.1 -NJ,2021,M10,166120.9333 -NJ,2021,M11,168483.7667 -NJ,2021,M12,170846.6 -NJ,2022,M01,NA -NJ,2022,M02,NA -NJ,2022,M03,NA -NJ,2022,M04,NA -NJ,2022,M05,NA -NJ,2022,M06,NA -NJ,2022,M07,NA -NJ,2022,M08,NA -NJ,2022,M09,NA -NJ,2022,M10,NA -NJ,2022,M11,NA -NJ,2022,M12,NA -NM,2012,M01,21328.05833 -NM,2012,M02,21373.81667 -NM,2012,M03,21419.575 -NM,2012,M04,21465.33333 -NM,2012,M05,21511.09167 -NM,2012,M06,21556.85 -NM,2012,M07,21602.60833 -NM,2012,M08,21648.36667 -NM,2012,M09,21694.125 -NM,2012,M10,21739.88333 -NM,2012,M11,21785.64167 -NM,2012,M12,21831.4 -NM,2013,M01,21871.90833 -NM,2013,M02,21912.41667 -NM,2013,M03,21952.925 -NM,2013,M04,21993.43333 -NM,2013,M05,22033.94167 -NM,2013,M06,22074.45 -NM,2013,M07,22114.95833 -NM,2013,M08,22155.46667 -NM,2013,M09,22195.975 -NM,2013,M10,22236.48333 -NM,2013,M11,22276.99167 -NM,2013,M12,22317.5 -NM,2014,M01,22371.00833 -NM,2014,M02,22424.51667 -NM,2014,M03,22478.025 -NM,2014,M04,22531.53333 -NM,2014,M05,22585.04167 -NM,2014,M06,22638.55 -NM,2014,M07,22692.05833 -NM,2014,M08,22745.56667 -NM,2014,M09,22799.075 -NM,2014,M10,22852.58333 -NM,2014,M11,22906.09167 -NM,2014,M12,22959.6 -NM,2015,M01,22974.65 -NM,2015,M02,22989.7 -NM,2015,M03,23004.75 -NM,2015,M04,23019.8 -NM,2015,M05,23034.85 -NM,2015,M06,23049.9 -NM,2015,M07,23064.95 -NM,2015,M08,23080 -NM,2015,M09,23095.05 -NM,2015,M10,23110.1 -NM,2015,M11,23125.15 -NM,2015,M12,23140.2 -NM,2016,M01,23139.04167 -NM,2016,M02,23137.88333 -NM,2016,M03,23136.725 -NM,2016,M04,23135.56667 -NM,2016,M05,23134.40833 -NM,2016,M06,23133.25 -NM,2016,M07,23132.09167 -NM,2016,M08,23130.93333 -NM,2016,M09,23129.775 -NM,2016,M10,23128.61667 -NM,2016,M11,23127.45833 -NM,2016,M12,23126.3 -NM,2017,M01,23173.10833 -NM,2017,M02,23219.91667 -NM,2017,M03,23266.725 -NM,2017,M04,23313.53333 -NM,2017,M05,23360.34167 -NM,2017,M06,23407.15 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-NM,2021,M02,25929.25 -NM,2021,M03,26343.675 -NM,2021,M04,26758.1 -NM,2021,M05,27172.525 -NM,2021,M06,27586.95 -NM,2021,M07,28001.375 -NM,2021,M08,28415.8 -NM,2021,M09,28830.225 -NM,2021,M10,29244.65 -NM,2021,M11,29659.075 -NM,2021,M12,30073.5 -NM,2022,M01,NA -NM,2022,M02,NA -NM,2022,M03,NA -NM,2022,M04,NA -NM,2022,M05,NA -NM,2022,M06,NA -NM,2022,M07,NA -NM,2022,M08,NA -NM,2022,M09,NA -NM,2022,M10,NA -NM,2022,M11,NA -NM,2022,M12,NA -NY,2012,M01,219393.575 -NY,2012,M02,219944.35 -NY,2012,M03,220495.125 -NY,2012,M04,221045.9 -NY,2012,M05,221596.675 -NY,2012,M06,222147.45 -NY,2012,M07,222698.225 -NY,2012,M08,223249 -NY,2012,M09,223799.775 -NY,2012,M10,224350.55 -NY,2012,M11,224901.325 -NY,2012,M12,225452.1 -NY,2013,M01,226055.675 -NY,2013,M02,226659.25 -NY,2013,M03,227262.825 -NY,2013,M04,227866.4 -NY,2013,M05,228469.975 -NY,2013,M06,229073.55 -NY,2013,M07,229677.125 -NY,2013,M08,230280.7 -NY,2013,M09,230884.275 -NY,2013,M10,231487.85 -NY,2013,M11,232091.425 -NY,2013,M12,232695 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a/covid19_drdfm/data/raw/pandemic/vaccinations/19_Vaccinations_in_the_United_States_Jurisdiction_output_output.csv +++ b/covid19_drdfm/data/raw/pandemic/vaccinations/19_Vaccinations_in_the_United_States_Jurisdiction_output_output.csv @@ -1,6601 +1,6601 @@ -State,Year,Period,Pandemic_Response_1,Pandemic_Response_2,Pandemic_Response_3 -AK,2012,M01,0,0,0 -AK,2012,M02,0,0,0 -AK,2012,M03,0,0,0 -AK,2012,M04,0,0,0 -AK,2012,M05,0,0,0 -AK,2012,M06,0,0,0 -AK,2012,M07,0,0,0 -AK,2012,M08,0,0,0 -AK,2012,M09,0,0,0 -AK,2012,M10,0,0,0 -AK,2012,M11,0,0,0 -AK,2012,M12,0,0,0 -AK,2013,M01,0,0,0 -AK,2013,M02,0,0,0 -AK,2013,M03,0,0,0 -AK,2013,M04,0,0,0 -AK,2013,M05,0,0,0 -AK,2013,M06,0,0,0 -AK,2013,M07,0,0,0 -AK,2013,M08,0,0,0 -AK,2013,M09,0,0,0 -AK,2013,M10,0,0,0 -AK,2013,M11,0,0,0 -AK,2013,M12,0,0,0 -AK,2014,M01,0,0,0 -AK,2014,M02,0,0,0 -AK,2014,M03,0,0,0 -AK,2014,M04,0,0,0 -AK,2014,M05,0,0,0 -AK,2014,M06,0,0,0 -AK,2014,M07,0,0,0 -AK,2014,M08,0,0,0 -AK,2014,M09,0,0,0 -AK,2014,M10,0,0,0 -AK,2014,M11,0,0,0 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-NE,2021,M10,0.562,2832860,2336339 -NE,2021,M11,0.574,3135320,2597241 -NE,2021,M12,0.599,3417630,2857010 -NE,2022,M01,0.615,3658590,3004905 -NE,2022,M02,0.625,3769510,3080182 -NE,2022,M03,0.631,3837910,3134556 -NE,2022,M04,0.636,3981110,3207541 -NE,2022,M05,0.638,4092710,3251394 -NE,2022,M06,0.641,4237510,3301814 -NE,2022,M07,0.644,4363240,3348454 -NE,2022,M08,0.647,4478340,3394554 -NE,2022,M09,0.65,4747440,3451226 -NE,2022,M10,0.653,4956140,3529237 -NE,2022,M11,0.658,5131540,3694014 -NE,2022,M12,0.66,5229080,3735602 -NH,2012,M01,0,0,0 -NH,2012,M02,0,0,0 -NH,2012,M03,0,0,0 -NH,2012,M04,0,0,0 -NH,2012,M05,0,0,0 -NH,2012,M06,0,0,0 -NH,2012,M07,0,0,0 -NH,2012,M08,0,0,0 -NH,2012,M09,0,0,0 -NH,2012,M10,0,0,0 -NH,2012,M11,0,0,0 -NH,2012,M12,0,0,0 -NH,2013,M01,0,0,0 -NH,2013,M02,0,0,0 -NH,2013,M03,0,0,0 -NH,2013,M04,0,0,0 -NH,2013,M05,0,0,0 -NH,2013,M06,0,0,0 -NH,2013,M07,0,0,0 -NH,2013,M08,0,0,0 -NH,2013,M09,0,0,0 -NH,2013,M10,0,0,0 -NH,2013,M11,0,0,0 -NH,2013,M12,0,0,0 -NH,2014,M01,0,0,0 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-NH,2018,M06,0,0,0 -NH,2018,M07,0,0,0 -NH,2018,M08,0,0,0 -NH,2018,M09,0,0,0 -NH,2018,M10,0,0,0 -NH,2018,M11,0,0,0 -NH,2018,M12,0,0,0 -NH,2019,M01,0,0,0 -NH,2019,M02,0,0,0 -NH,2019,M03,0,0,0 -NH,2019,M04,0,0,0 -NH,2019,M05,0,0,0 -NH,2019,M06,0,0,0 -NH,2019,M07,0,0,0 -NH,2019,M08,0,0,0 -NH,2019,M09,0,0,0 -NH,2019,M10,0,0,0 -NH,2019,M11,0,0,0 -NH,2019,M12,0,0,0 -NH,2020,M01,0,0,0 -NH,2020,M02,0,0,0 -NH,2020,M03,0,0,0 -NH,2020,M04,0,0,0 -NH,2020,M05,0,0,0 -NH,2020,M06,0,0,0 -NH,2020,M07,0,0,0 -NH,2020,M08,0,0,0 -NH,2020,M09,0,0,0 -NH,2020,M10,0,0,0 -NH,2020,M11,0,0,0 -NH,2020,M12,0,59900,25364 -NH,2021,M01,0,217100,128313 -NH,2021,M02,0,412275,321602 -NH,2021,M03,0.176,788755,614984 -NH,2021,M04,0.298,1304835,1142049 -NH,2021,M05,0.485,1737915,1385761 -NH,2021,M06,0.556,1824650,1515365 -NH,2021,M07,0.583,1913200,1591970 -NH,2021,M08,0.597,2026120,1685080 -NH,2021,M09,0.615,2142720,1753412 -NH,2021,M10,0.628,2353890,1915934 -NH,2021,M11,0.648,2640760,2137363 -NH,2021,M12,0.673,2938530,2405480 -NH,2022,M01,0.688,3155130,2562714 -NH,2022,M02,0.679,3277330,2419178 -NH,2022,M03,0.693,3364730,2472010 -NH,2022,M04,0.702,3539800,2525964 -NH,2022,M05,0.711,3662900,2613308 -NH,2022,M06,0.716,3782100,2663281 -NH,2022,M07,0.719,3895800,2687052 -NH,2022,M08,0.724,4012700,2721533 -NH,2022,M09,0.69,4288400,2582617 -NH,2022,M10,0.704,4522400,2739221 -NH,2022,M11,0.705,4750250,2741100 -NH,2022,M12,0.715,4844640,2906126 -NJ,2012,M01,0,0,0 -NJ,2012,M02,0,0,0 -NJ,2012,M03,0,0,0 -NJ,2012,M04,0,0,0 -NJ,2012,M05,0,0,0 -NJ,2012,M06,0,0,0 -NJ,2012,M07,0,0,0 -NJ,2012,M08,0,0,0 -NJ,2012,M09,0,0,0 -NJ,2012,M10,0,0,0 -NJ,2012,M11,0,0,0 -NJ,2012,M12,0,0,0 -NJ,2013,M01,0,0,0 -NJ,2013,M02,0,0,0 -NJ,2013,M03,0,0,0 -NJ,2013,M04,0,0,0 -NJ,2013,M05,0,0,0 -NJ,2013,M06,0,0,0 -NJ,2013,M07,0,0,0 -NJ,2013,M08,0,0,0 -NJ,2013,M09,0,0,0 -NJ,2013,M10,0,0,0 -NJ,2013,M11,0,0,0 -NJ,2013,M12,0,0,0 -NJ,2014,M01,0,0,0 -NJ,2014,M02,0,0,0 -NJ,2014,M03,0,0,0 -NJ,2014,M04,0,0,0 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-NJ,2018,M09,0,0,0 -NJ,2018,M10,0,0,0 -NJ,2018,M11,0,0,0 -NJ,2018,M12,0,0,0 -NJ,2019,M01,0,0,0 -NJ,2019,M02,0,0,0 -NJ,2019,M03,0,0,0 -NJ,2019,M04,0,0,0 -NJ,2019,M05,0,0,0 -NJ,2019,M06,0,0,0 -NJ,2019,M07,0,0,0 -NJ,2019,M08,0,0,0 -NJ,2019,M09,0,0,0 -NJ,2019,M10,0,0,0 -NJ,2019,M11,0,0,0 -NJ,2019,M12,0,0,0 -NJ,2020,M01,0,0,0 -NJ,2020,M02,0,0,0 -NJ,2020,M03,0,0,0 -NJ,2020,M04,0,0,0 -NJ,2020,M05,0,0,0 -NJ,2020,M06,0,0,0 -NJ,2020,M07,0,0,0 -NJ,2020,M08,0,0,0 -NJ,2020,M09,0,0,0 -NJ,2020,M10,0,0,0 -NJ,2020,M11,0,0,0 -NJ,2020,M12,0,403975,78838 -NJ,2021,M01,0,1232525,795440 -NJ,2021,M02,0,2508320,2065666 -NJ,2021,M03,0.187,5236605,4381035 -NJ,2021,M04,0.361,8623605,7302231 -NJ,2021,M05,0.488,10967005,9110414 -NJ,2021,M06,0.551,11548765,9841494 -NJ,2021,M07,0.584,12103035,10380457 -NJ,2021,M08,0.614,13072255,11005081 -NJ,2021,M09,0.643,14000545,11535180 -NJ,2021,M10,0.664,15176475,12334361 -NJ,2021,M11,0.678,17008125,13498900 -NJ,2021,M12,0.706,18675625,14997030 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00:00:00 2001 From: John Vivian Date: Mon, 22 Jan 2024 10:45:16 -0800 Subject: [PATCH 2/8] Update constants for new data --- covid19_drdfm/constants.py | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/covid19_drdfm/constants.py b/covid19_drdfm/constants.py index d25f57a..911dafe 100644 --- a/covid19_drdfm/constants.py +++ b/covid19_drdfm/constants.py @@ -11,9 +11,9 @@ "Pandemic_10": "Deaths3", "Pandemic_11": "Deaths4", "Pandemic_12": "Deaths5", - "Pandemic_Response_1": "Vax1", + "proportion_vax": "Vax1", "Pandemic_Response_2": "Vax2", - "Pandemic_Response_3": "Vax3", + "Administered": "Vax3", "Pandemic_Response_4": "Gather1", "Pandemic_Response_5": "Gather2", "Pandemic_Response_6": "Gather3", @@ -26,11 +26,11 @@ "Pandemic_Response_13": "ARP", "Pandemic_Response_14": "PPP", "Pandemic_Response_15": "CARES", - "Demand_1": "Cons1", - "Demand_2": "Cons2", - "Demand_3": "Cons3", - "Demand_4": "Cons4", - "Demand_5": "Cons5", + "Consumption": "Cons1", + "TG_Consumption": "Cons2", + "DG_Consumption": "Cons3", + "NDG_Consumption": "Cons4", + "S_Consumption": "Cons5", "Demand_6": "Employment1", "Demand_7": "Employment2", "GDP": "GDP", From 08cbbd54be532f56c322e66eeca9e12450d8866b Mon Sep 17 00:00:00 2001 From: John Vivian Date: Mon, 22 Jan 2024 10:45:29 -0800 Subject: [PATCH 3/8] Update processing for new variables and revert normalization --- covid19_drdfm/processing.py | 22 ++++++++++------------ 1 file changed, 10 insertions(+), 12 deletions(-) diff --git a/covid19_drdfm/processing.py b/covid19_drdfm/processing.py index 4491225..42368c9 100644 --- a/covid19_drdfm/processing.py +++ b/covid19_drdfm/processing.py @@ -36,16 +36,14 @@ def get_df() -> pd.DataFrame: reduce(lambda x, y: pd.merge(x, y, on=["State", "Year", "Period"], how="left"), dfs) .drop(columns=["Monetary_1_x", "Monetary_11_x"]) .rename(columns={"Monetary_1_y": "Monetary_1", "Monetary_11_y": "Monetary_11"}) - .drop( - columns=["Proportion", "proportion_vax2", "Pandemic_Response_8"] - ) #! Columns removed per discussion with AC + .drop(columns=["Proportion", "proportion_vax2", "Pandemic_Response_8", "Distributed"]) + .pipe(fix_names) .pipe(adjust_inflation) .pipe(add_datetime) - .pipe(fix_names) .pipe(adjust_pandemic_response) .pipe(diff_vars, cols=DIFF_COLS) .pipe(diff_vars, cols=LOG_DIFF_COLS, log=True) - .pipe(normalize) + # .pipe(normalize) .drop(index=0) # Drop first row with NaNs from diff ) @@ -83,13 +81,13 @@ def adjust_inflation(df: pd.DataFrame) -> pd.DataFrame: pd.DataFrame: Adjusted DataFrame """ return ( - df.assign(Demand_1=lambda x: x.Demand_1.div(x.Monetary_3 / 100)) - .assign(Demand_2=lambda x: x.Demand_2.div(x.Monetary_3 / 100)) - .assign(Demand_3=lambda x: x.Demand_3.div(x.Monetary_3 / 100)) - .assign(Demand_4=lambda x: x.Demand_4.div(x.Monetary_3 / 100)) - .assign(Demand_5=lambda x: x.Demand_5.div(x.Monetary_3 / 100)) - .assign(GDP=lambda x: x.GDP.div(x.Monetary_3 / 100)) - .assign(Supply_6=lambda x: x.Supply_6.div(x.Monetary_3 / 100)) + df.assign(Cons1=lambda x: x.Cons1.div(x.PCE / 100)) + .assign(Cons2=lambda x: x.Cons2.div(x.PCE / 100)) + .assign(Cons3=lambda x: x.Cons3.div(x.PCE / 100)) + .assign(Cons4=lambda x: x.Cons4.div(x.PCE / 100)) + .assign(Cons5=lambda x: x.Cons5.div(x.PCE / 100)) + .assign(GDP=lambda x: x.GDP.div(x.PCE / 100)) + .assign(FixAss=lambda x: x.FixAss.div(x.PCE / 100)) ) From eef5a541e968c9e3258203a78002e7e5925a3070 Mon Sep 17 00:00:00 2001 From: John Vivian Date: Mon, 22 Jan 2024 10:45:40 -0800 Subject: [PATCH 4/8] Extend max iter for EM algo --- covid19_drdfm/dfm.py | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/covid19_drdfm/dfm.py b/covid19_drdfm/dfm.py index e4cc73a..51f46e0 100644 --- a/covid19_drdfm/dfm.py +++ b/covid19_drdfm/dfm.py @@ -39,8 +39,6 @@ def state_process(df: pd.DataFrame, state: str) -> pd.DataFrame: pd.DataFrame: Processed DataFrame, ready for model """ df = df[df.State == state] - #! The trunctation will be removed when data is updated in OCT - A.C. - df = df[:-12] #! Test double-norm df = normalize(df).fillna(0) #! 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covid19_drdfm/streamlit/runner.py | 25 +++++++++---------------- 1 file changed, 9 insertions(+), 16 deletions(-) diff --git a/covid19_drdfm/streamlit/runner.py b/covid19_drdfm/streamlit/runner.py index fa729a2..8f467d4 100644 --- a/covid19_drdfm/streamlit/runner.py +++ b/covid19_drdfm/streamlit/runner.py @@ -13,26 +13,19 @@ from covid19_drdfm.constants import FACTORS from covid19_drdfm.dfm import state_process from covid19_drdfm.processing import NAME_MAP, get_df, normalize +from collections import defaultdict st.set_page_config(layout="wide") pio.templates.default = "plotly_white" -DEFAULTS = { - "Uncat": ["Monetary_5", "Monetary_9", "Monetary_10", "GDP", "Supply_7"], - "Consumption": ["Demand_3", "Demand_4", "Demand_5"], - "Response": [ - "Pandemic_Response_1", - "Pandemic_Response_3", - "Pandemic_Response_4", - "Pandemic_Response_9", - "Pandemic_Response_10", - "Pandemic_Response_12", - ], - "Employment": ["Supply_2", "Supply_3", "Supply_4", "Demand_7"], - "Inflation": ["Monetary_2", "Monetary_3", "Monetary_1"], - "Pandemic": ["Pandemic_1", "Pandemic_2", "Pandemic_6", "Pandemic_9", "Pandemic_7", "Pandemic_10"], -} -DEFAULTS = {x: [NAME_MAP[z] for z in y] for x, y in DEFAULTS.items()} +FACTORS_GROUPED = defaultdict(list) +for key, (_, second) in FACTORS.items(): + FACTORS_GROUPED[second].append(key) + +FACTORS_GROUPED = dict(FACTORS_GROUPED) +DEFAULTS = FACTORS_GROUPED + +# DEFAULTS = {x: [NAME_MAP[z] for z in y] for x, y in FACTORS_GROUPED.items()} # st.write(DEFAULTS) From 83e732d0b589fd29b352d9cd1cc49552a2048ae0 Mon Sep 17 00:00:00 2001 From: John Vivian Date: Mon, 22 Jan 2024 10:46:03 -0800 Subject: [PATCH 7/8] Update coverage --- .coverage | Bin 69632 -> 69632 bytes coverage.xml | 58 +++++++++++++++++++++++++-------------------------- 2 files changed, 29 insertions(+), 29 deletions(-) diff --git a/.coverage b/.coverage index b0f5e6da129a2daff5c096c08080b448d28f0a30..859debd549494628d6048eac9af5a49364c78520 100644 GIT binary patch delta 4165 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b/tests/test_processing.py index cbed7ce..0638ced 100644 --- a/tests/test_processing.py +++ b/tests/test_processing.py @@ -12,6 +12,7 @@ adjust_pandemic_response, get_df, get_govt_fund_dist, + fix_names, ) @@ -36,13 +37,13 @@ def test_get_govt_fund_dist(): def test_adjust_inflation(raw_data): - input_df = raw_data.copy() + input_df = raw_data.copy().pipe(fix_names) output_df = adjust_inflation(input_df) - assert input_df.Demand_1.iloc[0] < output_df.Demand_1.iloc[0] + assert input_df.Cons1.iloc[0] < output_df.Cons1.iloc[0] -def test_adjust_pandemic_response(sample_data): - input_df = sample_data.copy() +def test_adjust_pandemic_response(raw_data): + input_df = raw_data.copy().pipe(fix_names) #! Note - this is testing functionality, but is used per-state not on whole df out = adjust_pandemic_response(input_df) df = get_df()