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以 Fixed Time 模式进行交易

Calculate Time Difference Between Two Pandas Columns in Hours 以 Fixed Time 模式进行交易 and Minutes

I have two columns, fromdate and todate , in a dataframe.

I add a new column, diff , to find the difference between the two dates using

I get the diff column, but it contains days , when there's more than 24 hours.

How 以 Fixed Time 模式进行交易 do I convert my results to only hours and minutes (i.e. days are converted to hours)?

3 Answers 3

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Pandas timestamp differences returns a datetime.timedelta object. This 以 Fixed Time 模式进行交易 can easily be converted into hours by using the 以 Fixed Time 模式进行交易 *as_type* method, like so

The astype workaround works, but it is too slow for large (0.5 Million rows) files. Any other suggestions?

This was driving me bonkers as the .astype() solution above didn't work for me. But I found another way. Haven't timed it or anything, but might work for others out there:

. if you want hours. Or:

. if you want minutes.

UPDATE: There used to be a 以 Fixed Time 模式进行交易 helpful comment here that mentioned using .total_seconds() for time periods spanning multiple days. Since it's gone, I've updated the answer.

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Speed up writing to 以 Fixed Time 模式进行交易 files

I've profiled some legacy code I've inherited with cProfile. There were a bunch of changes I've already made that have helped (like using simplejson's C extensions!).

Basically this script is exporting data from one system to an ASCII fixed-width file. Each row is a record, and it has many values. Each line is 7158 characters and contains a ton of spaces. The total record count is 1.5 million records. Each row is generated one at a time, and takes a while (5-10 rows a second).

As each row is generated it's written to disk as simply as possible. The profiling indicates that about 19-20% of the total time is spent in file.write() . For a test case of 1,500 rows that's 20 seconds. I'd like to reduce that number.

Now it seems the next win will be reducing the amount of time spent writing to disk. I'以 Fixed Time 模式进行交易 d like to reduce it, if possible. I can keep a cache of records in memory, but I can't wait until the end and dump it all at once.

My first thought would be to keep a cache of records in a list and write them out in batches. Would that be faster? Something like:

My second thought would be to use another thread, but that makes me want to die inside.