Assume I have a DataFrame sales of timestamp values timestamp sales office 2014-01-01 09 01 00 Cincinnati 2014-01-01 09 11 00 San Francisco 2014-01-01 15 22 00 Chicago 2014-01-01 19 01 00 Chicago I would like to create a new column time hour I can create it by writing a short function as so and using apply to apply it iteratively def hr func ts return ts hour sales time hour sales timestamp apply hr func I would then see this result timestamp sales office time hour 2014-01-01 09 01 00 Cincinnati 9 2014-01-01 09 11 00 San Francisco 9 2014-01-01 15 22 00 Chicago 15 2014-01-01 19 01 00 Chicago 19 What I d like to achieve is some shorter transformation like this which I know is erroneous but gets at the spirit sales time hour sales timestamp hour Obviously the column is of type Series and as such doesn t have those attributes but it seems there s a simpler way to make use of matrix operations Is there a more-direct approach

Pandas: Return Hour from Datetime Column Directly

The Solution to Pandas: Return Hour from Datetime Column Directly is

For posterity: as of 0.15.0, there is a handy .dt accessor you can use to pull such values from a datetime/period series (in the above case, just sales.timestamp.dt.hour!

~ Answered on 2015-06-08 19:20:23

Pandas: Return Hour from Datetime Column Directly

The Solution to Pandas: Return Hour from Datetime Column Directly is

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