I hereby claim:
- I am drewfustin on github.
- I am drewfustin (https://keybase.io/drewfustin) on keybase.
- I have a public key ASC-73bOZhc3_DutuKYqamSwo2LEbzz1P1OOaalJXFtU-Qo
To claim this, I am signing this object:
I hereby claim:
To claim this, I am signing this object:
2022-03-15 13:29:15 [32mINFO[m i.a.w.w.WorkerRun(call):49 - Executing worker wrapper. Airbyte version: 0.35.54-alpha | |
2022-03-15 13:29:15 [32mINFO[m i.a.w.t.TemporalAttemptExecution(get):105 - Docker volume job log path: /tmp/workspace/28/0/logs.log | |
2022-03-15 13:29:15 [32mINFO[m i.a.w.t.TemporalAttemptExecution(get):110 - Executing worker wrapper. Airbyte version: 0.35.54-alpha | |
2022-03-15 13:29:15 [32mINFO[m i.a.w.DefaultReplicationWorker(run):104 - start sync worker. job id: 28 attempt id: 0 | |
2022-03-15 13:29:15 [32mINFO[m i.a.w.DefaultReplicationWorker(run):116 - configured sync modes: {public.shortened_urls=full_refresh - append} | |
2022-03-15 13:29:15 [32mINFO[m i.a.w.p.a.DefaultAirbyteDestination(start):69 - Running destination... | |
2022-03-15 13:29:15 [32mINFO[m i.a.c.i.LineGobbler(voidCall):82 - Checking if airbyte/destination-redshift:0.3.27 exists... | |
2022-03-15 13:29:15 [32mINFO[m i.a.c.i.LineGobbler(voidCall):82 - airbyte/destination-redshift:0.3.27 was found locally. | |
2022-03-15 13:29:15 |
My answers for Panel of Hiring Partners: How to Get Hired as a Data Scientist, an event put on by Metis tonight.
I hereby claim:
To claim this, I am signing this object:
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"source": "import pandas as pd\nimport numpy as np\nfrom science.loaders.forecasting.single_well_prod import model_battle_royale\n\nfc_field = 'monthly_well_oil_prod'\nmodels = ['hw', 'aa', 'mc']\n\ndf = pd.DataFrame({\n '{}'.format(fc_field): [7, 10, 12, 12, 14, np.nan],\n '{}_{}_fc'.format(fc_field, models[0]): [np.nan, 10, 11, 12, 13, 14],\n '{}_{}_lb'.format(fc_field, models[0]): [np.nan, 9, 10, 10, 11, 12],\n '{}_{}_ub'.format(fc_field, models[0]): [np.nan, 11, 12, 14, 16, 17],\n '{}_{}_fc'.format(fc_field, models[1]): [np.nan, 12, 9, 5, 4, 4],\n '{}_{}_lb'.format(fc_field, models[1]): [np.nan, 9, 7, 3, 1, 0],\n '{}_{}_ub'.format(fc_field, models[1]): [np.nan, 16, 11, 8, 6, 6],\n '{}_{}_fc'.format(fc_field, models[2]): [np.nan, 10, 11, 12, 10, 11],\n '{}_{}_lb'.format(fc_field, models[2]): [np.nan, 7, 8, 9, 6, 6],\n '{}_{}_ub'.form |