# xarray.DataArray.polyfit

#### DataArray.polyfit(dim, deg, skipna=None, rcond=None, w=None, full=False, cov=False)[[source]](https://github.com/pydata/xarray/blob/main/xarray/core/dataarray.py#L5901-L5966)

Least squares polynomial fit.

This replicates the behaviour of numpy.polyfit but differs by skipping
invalid values when skipna = True.

* **Parameters:**
  * **dim** (`Hashable`) – Coordinate along which to fit the polynomials.
  * **deg** ([`int`](https://docs.python.org/3/builtins/functions.html#int)) – Degree of the fitting polynomial.
  * **skipna** ([`bool`](https://docs.python.org/3/builtins/functions.html#bool) or [`None`](https://docs.python.org/3/builtins/constants.html#None), *optional*) – If True, removes all invalid values before fitting each 1D slices of the array.
    Default is True if data is stored in a dask.array or if there is any
    invalid values, False otherwise.
  * **rcond** ([`float`](https://docs.python.org/3/builtins/functions.html#float) or [`None`](https://docs.python.org/3/builtins/constants.html#None), *optional*) – Relative condition number to the fit.
  * **w** (`Hashable`, [array-like](https://numpy.org/doc/stable/glossary.html#term-array_like) or [`None`](https://docs.python.org/3/builtins/constants.html#None), *optional*) – Weights to apply to the y-coordinate of the sample points.
    Can be an array-like object or the name of a coordinate in the dataset.
  * **full** ([`bool`](https://docs.python.org/3/builtins/functions.html#bool), *default*: [`False`](https://docs.python.org/3/builtins/constants.html#False)) – Whether to return the residuals, matrix rank and singular values in addition
    to the coefficients.
  * **cov** ([`bool`](https://docs.python.org/3/builtins/functions.html#bool) or `"unscaled"`, *default*: [`False`](https://docs.python.org/3/builtins/constants.html#False)) – Whether to return to the covariance matrix in addition to the coefficients.
    The matrix is not scaled if cov=’unscaled’.
* **Returns:**
  **polyfit_results** ([`Dataset`](xarray.Dataset.html.md#xarray.Dataset)) – A single dataset which contains:

  polyfit_coefficients
  : The coefficients of the best fit.

  polyfit_residuals
  : The residuals of the least-square computation (only included if full=True).
    When the matrix rank is deficient, np.nan is returned.

  [dim]_matrix_rank
  : The effective rank of the scaled Vandermonde coefficient matrix (only included if full=True)

  [dim]_singular_value
  : The singular values of the scaled Vandermonde coefficient matrix (only included if full=True)

  polyfit_covariance
  : The covariance matrix of the polynomial coefficient estimates (only included if full=False and cov=True)

#### SEE ALSO
[`numpy.polyfit`](https://numpy.org/doc/stable/reference/generated/numpy.polyfit.html#numpy.polyfit), [`numpy.polyval`](https://numpy.org/doc/stable/reference/generated/numpy.polyval.html#numpy.polyval), [`xarray.polyval`](xarray.polyval.html.md#xarray.polyval), [`DataArray.curvefit`](xarray.DataArray.curvefit.html.md#xarray.DataArray.curvefit)