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DOC: Update interpolation docstring #49681

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Merged
merged 3 commits into from
Nov 14, 2022
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DOC: Update interpolation docstring #49681

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DOC: Update interpolation docstring to highlight slinear and spline d…
milosz-martynow Nov 13, 2022
d1ce4ca
Fix typos.
milosz-martynow Nov 14, 2022
bf44925
Shorter docstring comment.
milosz-martynow Nov 14, 2022
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9 changes: 6 additions & 3 deletions pandas/core/generic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7247,12 +7247,15 @@ def interpolate(
given length of interval.
* 'index', 'values': use the actual numerical values of the index.
* 'pad': Fill in NaNs using existing values.
* 'nearest', 'zero', 'slinear', 'quadratic', 'cubic', 'spline',
* 'nearest', 'zero', 'slinear', 'quadratic', 'cubic',
'barycentric', 'polynomial': Passed to
`scipy.interpolate.interp1d`. These methods use the numerical
`scipy.interpolate.interp1d`, whereas 'spline' is assed to
`scipy.interpolate.UnivariateSpline`. These methods use the numerical
values of the index. Both 'polynomial' and 'spline' require that
you also specify an `order` (int), e.g.
``df.interpolate(method='polynomial', order=5)``.
``df.interpolate(method='polynomial', order=5)``. Note that, Scipy
`slinear` method refers to the Scipy first order spline instead
of Pandas first order spline.
* 'krogh', 'piecewise_polynomial', 'spline', 'pchip', 'akima',
'cubicspline': Wrappers around the SciPy interpolation methods of
similar names. See `Notes`.
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