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# matplotlib.pyplot.pcolor

`matplotlib.pyplot.``pcolor`(*args, **kwargs)

  Create a pseudocolor plot of a 2-D array.

  Note

  pcolor can be very slow for large arrays; consider using the similar but much faster `pcolormesh()` instead.

  Call signatures:

      pcolor(C, **kwargs)
      pcolor(X, Y, C, **kwargs)

  C is the array of color values.

  X and Y, if given, specify the (x, y) coordinates of the colored quadrilaterals; the quadrilateral for C[i,j] has corners at:

      (X[i,   j],   Y[i,   j]),
      (X[i,   j+1], Y[i,   j+1]),
      (X[i+1, j],   Y[i+1, j]),
      (X[i+1, j+1], Y[i+1, j+1]).

  Ideally the dimensions of X and Y should be one greater than those of C; if the dimensions are the same, then the last row and column of C will be ignored.

  Note that the column index corresponds to the x-coordinate, and the row index corresponds to y; for details, see the Grid Orientation section below.

  If either or both of X and Y are 1-D arrays or column vectors, they will be expanded as needed into the appropriate 2-D arrays, making a rectangular grid.

  X, Y and C may be masked arrays. If either C[i, j], or one of the vertices surrounding C[i,j] (X or Y at [i, j], [i+1, j], [i, j+1],[i+1, j+1]) is masked, nothing is plotted.

  Keyword arguments:

  > cmap: [ None | Colormap ]
  >   A `matplotlib.colors.Colormap` instance. If None, use rc settings.
  > norm: [ None | Normalize ]
  >   An `matplotlib.colors.Normalize` instance is used to scale luminance data to 0,1. If None, defaults to `normalize()`.
  > vmin/vmax: [ None | scalar ]
  >   vmin and vmax are used in conjunction with norm to normalize luminance data. If either is None, it is autoscaled to the respective min or max of the color array C. If not None, vmin or vmax passed in here override any pre-existing values supplied in the norm instance.
  > edgecolors: [ None | `'none'` | color | color sequence]

  >   If None, the rc setting is used by default.

  >   If `'none'`, edges will not be visible.

  >   An mpl color or sequence of colors will set the edge color

  > alpha: `0 <= scalar <= 1` or None
  >   the alpha blending value
  > snap: bool
  >   Whether to snap the mesh to pixel boundaries.

  Return value is a `matplotlib.collections.Collection` instance.

  The grid orientation follows the MATLAB convention: an array C with shape (nrows, ncolumns) is plotted with the column number as X and the row number as Y, increasing up; hence it is plotted the way the array would be printed, except that the Y axis is reversed. That is, C is taken as C*(*y, x).

  Similarly for `meshgrid()`:

      x = np.arange(5)
      y = np.arange(3)
      X, Y = np.meshgrid(x, y)

  is equivalent to:

      X = array([[0, 1, 2, 3, 4],
                 [0, 1, 2, 3, 4],
                 [0, 1, 2, 3, 4]])

      Y = array([[0, 0, 0, 0, 0],
                 [1, 1, 1, 1, 1],
                 [2, 2, 2, 2, 2]])

  so if you have:

      C = rand(len(x), len(y))

  then you need to transpose C:

      pcolor(X, Y, C.T)

  or:

      pcolor(C.T)

  MATLAB `pcolor()` always discards the last row and column of C, but matplotlib displays the last row and column if X and Y are not specified, or if X and Y have one more row and column than C.

  kwargs can be used to control the `PolyCollection` properties:

  > Property | Description
  > --- | ---
  > `agg_filter` | unknown
  > `alpha` | float or None
  > `animated` | [True | False]
  > `antialiased` or antialiaseds | Boolean or sequence of booleans
  > `array` | unknown
  > `axes` | an `Axes` instance
  > `clim` | a length 2 sequence of floats
  > `clip_box` | a `matplotlib.transforms.Bbox` instance
  > `clip_on` | [True | False]
  > `clip_path` | [ (`Path`, `Transform`) | `Patch` | None ]
  > `cmap` | a colormap or registered colormap name
  > `color` | matplotlib color arg or sequence of rgba tuples
  > `contains` | a callable function
  > `edgecolor` or edgecolors | matplotlib color spec or sequence of specs
  > `facecolor` or facecolors | matplotlib color spec or sequence of specs
  > `figure` | a `matplotlib.figure.Figure` instance
  > `gid` | an id string
  > `hatch` | [ ‘/’ | ‘' | ‘|’ | ‘-‘ | ‘+’ | ‘x’ | ‘o’ | ‘O’ | ‘.’ | ‘*’ ]
  > `label` | string or anything printable with ‘%s’ conversion.
  > `linestyle` or dashes or linestyles | [‘solid’ | ‘dashed’, ‘dashdot’, ‘dotted’ | (offset, on-off-dash-seq) | `'-'` | `'--'` | `'-.'` | `':'` | `'None'` | `' '` | `''`]
  > `linewidth` or linewidths or lw | float or sequence of floats
  > `norm` | unknown
  > `offset_position` | unknown
  > `offsets` | float or sequence of floats
  > `path_effects` | unknown
  > `picker` | [None|float|boolean|callable]
  > `pickradius` | unknown
  > `rasterized` | [True | False | None]
  > `sketch_params` | unknown
  > `snap` | unknown
  > `transform` | `Transform` instance
  > `url` | a url string
  > `urls` | unknown
  > `visible` | [True | False]
  > `zorder` | any number

  Note

  The default antialiaseds is False if the default edgecolors*=”none” is used. This eliminates artificial lines at patch boundaries, and works regardless of the value of alpha. If *edgecolors is not “none”, then the default antialiaseds is taken from rcParams[‘patch.antialiased’], which defaults to True. Stroking the edges may be preferred if alpha is 1, but will cause artifacts otherwise.

  See also

  `pcolormesh()`
    For an explanation of the differences between pcolor and pcolormesh.

  Note

  In addition to the above described arguments, this function can take a data keyword argument. If such a data argument is given, the following arguments are replaced by data[<arg>]:

  - All positional and all keyword arguments.

## Examples using `matplotlib.pyplot.pcolor`

Simple animation examples

Saving an animation