np_shift
- pyhelpers.ops.np_shift(array, step, fill_value=nan)
Shift an array by desired number of rows.
See also [OPS-NS-1]
- Parameters:
array (numpy.ndarray) – an array of numbers
step (int) – number of rows to shift
fill_value (float or int) – values to fill missing rows due to the shift, defaults to
NaN
- Returns:
shifted array
- Return type:
numpy.ndarray
Examples:
>>> from pyhelpers.ops import np_shift >>> from pyhelpers._cache import example_dataframe >>> arr = example_dataframe(osgb36=True).to_numpy() >>> arr array([[530039.5588445, 180371.6801655], [406705.8870136, 286868.1666422], [383830.0390357, 398113.0558309], [430147.4473539, 433553.3271173]]) >>> np_shift(arr, step=-1) array([[406705.8870136, 286868.1666422], [383830.0390357, 398113.0558309], [430147.4473539, 433553.3271173], [ nan, nan]]) >>> np_shift(arr, step=1, fill_value=0) array([[ 0, 0], [530039, 180371], [406705, 286868], [383830, 398113]])