extracting days from a numpy.timedelta64 value

by

You can convert it to a timedelta with a day precision. To extract the integer value of days you divide it with a timedelta of one day.

>>> x = np.timedelta64(2069211000000000, 'ns')
>>> days = x.astype('timedelta64[D]')
>>> days / np.timedelta64(1, 'D')
23

Or, as @PhillipCloud suggested, just days.astype(int) since the timedelta is just a 64bit integer that is interpreted in various ways depending on the second parameter you passed in ('D', 'ns', …).

You can find more about it here.

More Related Contents:

  1. Fast punctuation removal with pandas
  2. String concatenation of two pandas columns
  3. How to one-hot-encode from a pandas column containing a list?
  4. How can I split a column of tuples in a Pandas dataframe?
  5. Calculate average of every x rows in a table and create new table
  6. Find column name in pandas that matches an array
  7. Efficiently return the index of the first value satisfying condition in array
  8. Group duplicate column IDs in pandas dataframe
  9. Most efficient way to forward-fill NaN values in numpy array
  10. Select multiple ranges of columns in Pandas DataFrame
  11. Suppressing scientific notation in pandas? [duplicate]
  12. How to one hot encode variant length features?
  13. Ambiguity in Pandas Dataframe / Numpy Array “axis” definition
  14. Counting unique values in a column in pandas dataframe like in Qlik?
  15. pandas equivalent of np.where
  16. how to read certain columns from Excel using Pandas – Python
  17. which is faster for load: pickle or hdf5 in python
  18. Saving Matplotlib graphs to image as full screen
  19. How can I count the number of consecutive TRUEs in a DataFrame?
  20. Pandas Latitude-Longitude to distance between successive rows [duplicate]
  21. pd.Timestamp versus np.datetime64: are they interchangeable for selected uses?
  22. Create new column based on values from other columns / apply a function of multiple columns, row-wise in Pandas
  23. Pandas in AWS lambda gives numpy error
  24. Pandas groupby with categories with redundant nan
  25. Filling in date gaps in MultiIndex Pandas Dataframe
  26. Different std in pandas vs numpy
  27. Python numpy: cannot convert datetime64[ns] to datetime64[D] (to use with Numba)
  28. Split Python sequence (time series/array) into subsequences with overlap
  29. Add density curve on the histogram
  30. Numpy.dtype has the wrong size, try recompiling

Leave a Comment