Analytics Vidhya Hackathon 4

Stock prices dataset with exogenous variables

@kaggle.saurabhbagchi_av_hackathon_4

Table List

3 tables(2.54 MB)

Samplesubmission Zxscq0o

Test Qqkw4dv

Train Awol0xl

Train Awol0xl

@kaggle.saurabhbagchi_av_hackathon_4.train_awol0xl

2.48 MB
73439 rows
9 columns

id ID	date Date	open Open	high High	low Low	close Close	holiday Holiday	unpredictability_score Unpredictability Score
id_0	Tue Jan 03 2017 00:00:00 GMT+0000 (Coordinated Universal Time)	82.9961	82.7396	82.9144	82.8101	1	7
id_1	Wed Jan 04 2017 00:00:00 GMT+0000 (Coordinated Universal Time)	83.1312	83.1669	83.3779	82.969		7
id_2	Thu Jan 05 2017 00:00:00 GMT+0000 (Coordinated Universal Time)	82.6622	82.7634	82.8984	82.8578		7
id_3	Fri Jan 06 2017 00:00:00 GMT+0000 (Coordinated Universal Time)	83.0279	82.795	82.8425	82.7385		7
id_4	Mon Jan 09 2017 00:00:00 GMT+0000 (Coordinated Universal Time)	82.3761	82.0828	82.1473	81.8641		7
id_5	Tue Jan 10 2017 00:00:00 GMT+0000 (Coordinated Universal Time)	81.7083	81.339	80.9486	80.6796		7
id_6	Wed Jan 11 2017 00:00:00 GMT+0000 (Coordinated Universal Time)	80.5319	80.5793	80.6769	80.5523		7
id_7	Thu Jan 12 2017 00:00:00 GMT+0000 (Coordinated Universal Time)	80.4285	80.7059	80.8127	80.5762		7
id_8	Fri Jan 13 2017 00:00:00 GMT+0000 (Coordinated Universal Time)	80.5637	80.3815	80.525	80.3457		7
id_9	Tue Jan 17 2017 00:00:00 GMT+0000 (Coordinated Universal Time)	79.9198	80.5476	80.3972	80.8544		7


CREATE TABLE train_awol0xl (
  "id" VARCHAR,
  "stock" BIGINT,
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "holiday" BIGINT,
  "unpredictability_score" BIGINT
);