Well the problem simply-put is that the SUM(TIME) for a specific SSN on your query is a single value, so it’s objecting to MAX as it makes no sense (The maximum of a single value is meaningless). Not sure what SQL database server you’re using but I suspect you want a query more like this … Read more
According to: [Python 3 docs]: Numeric Types – int, float, complex: Integers have unlimited precision. Translated to code: >>> i = 10 ** 100 >>> i 10000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000 >>> len(str(i)) 101 >>> i.bit_length() 333 On the other hand, each C type has a fixed size (depending on platform / architecture), as clearly shown in [CPPReference]: Fundamental … Read more
In PHP 5.2 the only way to do this is to loop through the array. $max = null; foreach ($arr as $item) { $max = $max === null ? $item->dnum : max($max, $item->dnum); } Note: I’ve seeded the result with 0 because if all the dnum values are negative then the now accepted solution will … Read more
Idea is to find max value and get all keys corresponding to that value: count = {‘a’: 120, ‘b’: 120, ‘c’: 100} highest = max(count.values()) print([k for k, v in count.items() if v == highest])
Use max(), array_map(), and strtotime(). $max = max(array_map(‘strtotime’, $arr)); echo date(‘Y-m-j H:i:s’, $max); // 2012-06-11 08:30:49
It picks the first element it sees. See the documentation for max(): If multiple items are maximal, the function returns the first one encountered. This is consistent with other sort-stability preserving tools such as sorted(iterable, key=keyfunc, reverse=True)[0] and heapq.nlargest(1, iterable, key=keyfunc). In the source code this is implemented in ./Python/bltinmodule.c by builtin_max, which wraps the … Read more
Use data.table 🙂 library(data.table) x = c(1,2,3,4,5 ) y = c(2,3,3,1,1 ) z = c(4,3,2,1,1 ) dt<-data.table(x,y,z) dt[, max:=pmax(x,y,z)] dt
You can keep a priority queue of the 100 biggest numbers, iterate through the 1 billion numbers. Whenever you encounter a number greater than the smallest number in the queue (the head of the queue), remove the head of the queue and add the new number to the queue. A priority queue implemented with a … Read more
The max of all the values in the DataFrame can be obtained using df.to_numpy().max(), or for pandas < 0.24.0 we use df.values.max(): In [10]: df.to_numpy().max() Out[10]: ‘f’ The max is f rather than 43.0 since, in CPython2, In [11]: ‘f’ > 43.0 Out[11]: True In CPython2, Objects of different types … are ordered by their … Read more
You can use apply to go through each row apply(df, 1, FUN = min) Where 1 means to apply FUN to each row of df, 2 would mean to apply FUN to columns. To remove missing values, use: apply(df, 1, FUN = min, na.rm = TRUE)