group-by

问题 I have a 'Service' table with millions of rows. Each row corresponds to a service provided by a staff in a given date and time interval (Each row has a unique ID). There are cases where a staff might provide services in overlapping time frames. I need to write a query that merges overlapping time intervals and returns the data in the format shown below. I tried grouping by StaffID and Date fields and getting the Min of BeginTime and Max of EndTime but that does not account for the non

问题 I'm looking for a way to select the most occurring value, e.g. the person who posted most for each thread; SELECT MOST_OCCURRING(user_id) FROM thread_posts GROUP BY thread_id Is there a good way to do this? 回答1: If you want a count on a per thread basis, I think you can use a nested query; grouping by thread first and then by user: SELECT thread_id AS tid, (SELECT user_id FROM thread_posts WHERE thread_id = tid GROUP BY user_id ORDER BY COUNT(*) DESC LIMIT 0,1) AS topUser FROM thread_posts

问题 I'm looking for a way to select the most occurring value, e.g. the person who posted most for each thread; SELECT MOST_OCCURRING(user_id) FROM thread_posts GROUP BY thread_id Is there a good way to do this? 回答1: If you want a count on a per thread basis, I think you can use a nested query; grouping by thread first and then by user: SELECT thread_id AS tid, (SELECT user_id FROM thread_posts WHERE thread_id = tid GROUP BY user_id ORDER BY COUNT(*) DESC LIMIT 0,1) AS topUser FROM thread_posts

问题 Suppose I have a list:- person_name = ['zakesh', 'oldman LLC', 'bikash', 'goldman LLC', 'zikash','rakesh'] I am trying to group the list in such a way so the Levenshtein distance between two strings is maximum. For finding out the ratio between two words, I am using a python package fuzzywuzzy. Examples :- >>> from fuzzywuzzy import fuzz >>> combined_list = ['rakesh', 'zakesh', 'bikash', 'zikash', 'goldman LLC', 'oldman LLC'] >>> fuzz.ratio('goldman LLC', 'oldman LLC') 95 >>> fuzz.ratio(

问题 This question already has an answer here : PostgreSQL, SQL state: 42601 (1 answer) Closed 4 months ago . I have a query, that I want to make, it is an INSERT FROM a SELECT GROUP BY, but I get the error: ERROR: INSERT has more target columns than expressions LINE 15: INSERT INTO "KPI_MEASURE" (id, created_at, kpi_project_id, k... _____________________________________^ HINT: The insertion source is a row expression containing the same number of columns expected by the INSERT. Did you

问题 I have a dataframe: import pandas as pd df = pd.DataFrame([[1, 'a'], [1, 'a'], [1, 'b'], [1, 'a'], [2, 'a'], [2, 'b'], [2, 'a'], [2, 'b'], [3, 'b'], [3, 'a'], [3, 'b'], ], columns=['session', 'issue']) df I would like to rank issues within sessions. I tried with: df.groupby(['session', 'issue']).size().rank(ascending=False, method='dense') session issue 1 a 1.0 b 3.0 2 a 2.0 b 2.0 3 a 3.0 b 2.0 dtype: float64 What I need is result like this one: for group session=1, there are three a issues

问题 I have a dataframe which looks like this: pd.DataFrame({'category': [1,1,1,2,2,2,3,3,3,4], 'order_start': [1,2,3,1,2,3,1,2,3,1], 'time': [1, 4, 3, 6, 8, 17, 14, 12, 13, 16]}) Out[40]: category order_start time 0 1 1 1 1 1 2 4 2 1 3 3 3 2 1 6 4 2 2 8 5 2 3 17 6 3 1 14 7 3 2 12 8 3 3 13 9 4 1 16 I would like to create a new column which contains the mean of the previous times of the same category. How can I create it ? The new column should look like this: pd.DataFrame({'category': [1,1,1,2,2,2

问题 I have a dataframe which looks like this: pd.DataFrame({'category': [1,1,1,2,2,2,3,3,3,4], 'order_start': [1,2,3,1,2,3,1,2,3,1], 'time': [1, 4, 3, 6, 8, 17, 14, 12, 13, 16]}) Out[40]: category order_start time 0 1 1 1 1 1 2 4 2 1 3 3 3 2 1 6 4 2 2 8 5 2 3 17 6 3 1 14 7 3 2 12 8 3 3 13 9 4 1 16 I would like to create a new column which contains the mean of the previous times of the same category. How can I create it ? The new column should look like this: pd.DataFrame({'category': [1,1,1,2,2,2

问题 I have a SQL below which is able to get the interval average of timestamp column grouped by icao_address, flight_number, flight_date. I'm trying to do the same for standard deviation and although I get a figure, it is wrong. The standard deviation that I get back is 14.06 (look at image below to see) while it should be around 1.8. Below is what I'm using for stddev calculation. STDDEV_POP(UNIX_SECONDS(timestamp))as standard_deviation Below is my SQL #standardSQL select DATE(timestamp) as

问题 I have a SQL below which is able to get the interval average of timestamp column grouped by icao_address, flight_number, flight_date. I'm trying to do the same for standard deviation and although I get a figure, it is wrong. The standard deviation that I get back is 14.06 (look at image below to see) while it should be around 1.8. Below is what I'm using for stddev calculation. STDDEV_POP(UNIX_SECONDS(timestamp))as standard_deviation Below is my SQL #standardSQL select DATE(timestamp) as