Per numpy docs:. When operating on two arrays, NumPy compares their shapes element-wise. It starts with the trailing dimensions, and works its way forward.

2012年3月20日 · Use this code, it is working perfectly. I have create a sql function that accept two parameters, the first param is the long string that we want to search into it,and it can accept string length up to 1500 character(of course you can extend it or even change it to text datatype).

2023年8月1日 · Note that the reserved DOS device names and the rule about filenames ending in a dot or spaces are applied by the runtime library when converting a DOS path to a native NT path.

2011年8月17日 · I have a table as follows: Filename - varchar Creation Date - Date format dd/mm/yyyy hh24:mi:ss Oldest cdr date - Date format dd/mm/yyyy hh24:mi:ss How can I calcuate the difference in hours minu...

2017年8月11日 · Viewed 99k times 14 I am trying to make a graph (like a bar graph, number of occurrences on the y and value on the x) that will show each value in a column and the number of times it occurs.

2008年9月8日 · Try the Bash built-in help: help for Output for: for NAME [in WORDS ... ;] do COMMANDS; done The `for' loop executes a sequence of commands for each member in a list of items.

2008年10月25日 · @olibre "at least ctime is closer to the real creation time than mtime" - no it isn't; this is something I've seen stated several times but it's totally false. Unless you've manually messed with the values in your inode, ctime should always be equal to or later than mtime , because an mtime change causes a ctime change (because the mtime itself ...

Excel expects dates and times to be stored as a floating point number whose value depends on the Date1904 setting of the workbook, plus a number format such as "mm/dd/yyyy" or "hh:mm:ss" or "mm/dd/yyyy hh:mm:ss" so that the number is displayed to the user as a date / time.

Explanation: timeit executes the anonymous function 1 million times by default and the result is given in seconds. Therefore the result for 1 single execution is the same amount but in microseconds on average.

and if data in "age" column has similar records (i.e. many people are 25 years old, many others are 32 and so on), it causes confusion in aligning right count to each student. in order to avoid it, I joined the tables on student ID as well.