Interpolate values according to different methods.

Please note that only method='linear' is supported for DataFrame/Series with a MultiIndex.

param method
str, default ‘linear’

Interpolation technique to use. One of:

  • ‘linear’: Ignore the index and treat the values as equally

    spaced. This is the only method supported on MultiIndexes.

  • ‘time’: Works on daily and higher resolution data to 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’,

    ‘barycentric’, ‘polynomial’: Passed to scipy.interpolate.interp1d. 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).

  • ‘krogh’, ‘piecewise_polynomial’, ‘spline’, ‘pchip’, ‘akima’:

    Wrappers around the SciPy interpolation methods of similar names. See Notes.

  • ‘from_derivatives’: Refers to

    scipy.interpolate.BPoly.from_derivatives which replaces ‘piecewise_polynomial’ interpolation method in scipy 0.18.

New in version 0.18.1.

Added support for the ‘akima’ method. Added interpolate method ‘from_derivatives’ which replaces ‘piecewise_polynomial’ in SciPy 0.18; backwards-compatible with SciPy < 0.18

param axis
{0 or ‘index’, 1 or ‘columns’, None}, default None

Axis to interpolate along.

param limit
int, optional

Maximum number of consecutive NaNs to fill. Must be greater than 0.

param inplace
bool, default False

Update the data in place if possible.

param limit_direction
{‘forward’, ‘backward’, ‘both’}, default ‘forward’

If limit is specified, consecutive NaNs will be filled in this direction.

param limit_area
{None, ‘inside’, ‘outside’}, default None

If limit is specified, consecutive NaNs will be filled with this restriction.

  • None: No fill restriction.

  • ‘inside’: Only fill NaNs surrounded by valid values


  • ‘outside’: Only fill NaNs outside valid values (extrapolate).

New in version 0.23.0.

param downcast
optional, ‘infer’ or None, defaults to None

Downcast dtypes if possible. **kwargs Keyword arguments to pass on to the interpolating function.


Series or DataFrame Returns the same object type as the caller, interpolated at some or all NaN values.


This feature is currently unsupported by Intel Scalable Dataframe Compiler