I would just add group_id to the GROUP BY. When SELECTing a column that is not part of the GROUP BY there could be multiple values for that column within the groups, but there will only be space for a single value in the results. So, the database usually needs to be told exactly how … Read more
You could use GROUP_CONCAT aggregated function to get all years into a single column, grouped by id and ordered by rate: SELECT id, GROUP_CONCAT(year ORDER BY rate DESC) grouped_year FROM yourtable GROUP BY id Result: ———————————————————– | ID | GROUPED_YEAR | ———————————————————– | p01 | 2006,2003,2008,2001,2007,2009,2002,2004,2005,2000 | | p02 | 2001,2004,2002,2003,2000,2006,2007 | ———————————————————– And then … Read more
Use GroupBy.sum: df.groupby([‘Fruit’,’Name’]).sum() Out[31]: Number Fruit Name Apples Bob 16 Mike 9 Steve 10 Grapes Bob 35 Tom 87 Tony 15 Oranges Bob 67 Mike 57 Tom 15 Tony 1
Most efficient method to groupby on an array of objects
DISTINCT ON is typically simplest and fastest for this in PostgreSQL. (For performance optimization for certain workloads see below.) SELECT DISTINCT ON (customer) id, customer, total FROM purchases ORDER BY customer, total DESC, id; Or shorter (if not as clear) with ordinal numbers of output columns: SELECT DISTINCT ON (2) id, customer, total FROM purchases … Read more
We start by answering the first question: Question 1 Why do I get ValueError: Index contains duplicate entries, cannot reshape This occurs because pandas is attempting to reindex either a columns or index object with duplicate entries. There are varying methods to use that can perform a pivot. Some of them are not well suited … Read more