关于“Weather Data in BigQuery”的评价
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Sameer S. · 评论7 months之前
gg
Rupesh k. · 评论7 months之前
Azlan K. · 评论7 months之前
Aditya N. · 评论7 months之前
Aryan S. · 评论7 months之前
SELECT descriptor, sum(complaint_count) as total_complaint_count, count(wind_speed) as data_count, ROUND(corr(wind_speed, avg_count),3) AS corr_count, ROUND(corr(wind_speed, avg_pct_count),3) AS corr_pct From ( SELECT avg(pct_count) as avg_pct_count, avg(day_count) as avg_count, sum(day_count) as complaint_count, descriptor, wind_speed FROM ( SELECT DATE(timestamp) AS date, wind_speed FROM demos.nyc_weather) a JOIN ( SELECT x.date, descriptor, day_count, day_count / all_calls_count as pct_count FROM (SELECT DATE(created_date) AS date, concat(complaint_type, ": ", descriptor) as descriptor, COUNT(*) AS day_count FROM `bigquery-public-data.new_york.311_service_requests` GROUP BY date, descriptor)x JOIN ( SELECT DATE(timestamp) AS date, COUNT(*) AS all_calls_count FROM `demos.nyc_weather` GROUP BY date )y ON x.date=y.date )b ON a.date = b.date GROUP BY descriptor, wind_speed ) GROUP BY descriptor HAVING total_complaint_count > 5000 AND ABS(corr_pct) > 0.5 AND data_count > 5 ORDER BY ABS(corr_pct) DESC
Syed S. · 评论7 months之前
Aditya K. · 评论7 months之前
SRI CHAITANYA A. · 评论7 months之前
Deep D. · 评论7 months之前
Abhishek S. · 评论7 months之前
Vagish S. · 评论7 months之前
Yaqoob M. · 评论7 months之前
Mrunal S.Naik G. · 评论7 months之前
hemang p. · 评论7 months之前
Glevin D. · 评论7 months之前
Indri S. · 评论7 months之前
Rahul K. · 评论7 months之前
krithikgokul s. · 评论7 months之前
Amar P. · 评论7 months之前
hi
Rajan S. · 评论7 months之前
Shubhro G. · 评论7 months之前
nice
Rakhi G. · 评论7 months之前
Shreyansh K. · 评论7 months之前
Vipul Y. · 评论7 months之前
Arcade Feb 2024
Jonathan M. · 评论7 months之前
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