matplotlib 2.0 supports Python 2.7, and 3.4+

New in matplotlib-2.0

New rcParams

The parameters ``xtick.top``, ``xtick.bottom``, ``ytick.left``

and ``ytick.right`` were added to control where the ticks

are drawn.

Furthermore, the parameters ``xtick.major.top``, ``xtick.major.bottom``,

``xtick.minor.top``, ``xtick.minor.bottom``, ``ytick.major.left``,

``ytick.major.right``, ``ytick.minor.left``, and ``ytick.minor.right`` were

added to control were ticks are drawn.

``hist.bins`` to control the default number of bins to use in

`~matplotlib.axes.Axes.hist`. This can be an `int`, a list of floats, or

``'auto'`` if numpy >= 1.11 is installed.

Improved color conversion API and RGBA support

The :module:`~matplotlib.colors` gained a new color conversion API with

full support for the alpha channel. The main public functions are

:func:`~matplotlib.colors.is_color_like`, :func:`matplotlib.colors.to_rgba`,

:func:`matplotlib.colors.to_rgba_array` and :func:`~matplotlib.colors.to_hex`.

RGBA quadruplets are encoded in hex format as `#rrggbbaa`.

A side benefit is that the Qt options editor now allows setting the alpha

channel of the artists as well.

Configuration (rcParams)

| Parameter | Description |

|`date.autoformatter.year` | foramt string for 'year' scale dates |

|`date.autoformatter.month` | format string for 'month' scale dates |

|`date.autoformatter.day` | format string for 'day' scale dates |

|`date.autoformatter.hour` | format string for 'hour' scale times |

|`date.autoformatter.minute` | format string for 'minute' scale times |

|`date.autoformatter.second` | format string for 'second' scale times |

|`date.autoformatter.microsecond` | format string for 'microsecond' scale times |

|`scatter.marker` | default marker for scatter plot |

|`svg.hashsalt` | see note |

Added ``svg.hashsalt`` key to rcParams

If ``svg.hashsalt`` is ``None`` (which it is by default), the svg

backend uses ``uuid4`` to generate the hash salt. If it is not

``None``, it must be a string that is used as the hash salt instead of

``uuid4``. This allows for deterministic SVG output.

Removed the ``svg.image_noscale`` rcParam

As a result of the extensive changes to image handling, the

``svg.image_noscale`` rcParam has been removed. The same

functionality may be achieved by setting ``interpolation='none'`` on

individual images or globally using the ``image.interpolation``

rcParam.

Qualitative colormaps

ColorBrewer's "qualitative" colormaps ("Accent", "Dark2", "Paired",

"Pastel1", "Pastel2", "Set1", "Set2", "Set3") were intended for discrete

categorical data, with no implication of value, and therefore have been

converted to ``ListedColormap`` instead of ``LinearSegmentedColormap``, so

the colors will no longer be interpolated and they can be used for

choropleths, labeled image features, etc.

Axis offset label now responds to `labelcolor`

Axis offset labels are now colored the same as axis tick markers when `labelcolor` is altered.

Improved offset text choice

The default offset-text choice was changed to only use significant digits that

are common to all ticks (e.g. 1231..1239 -> 1230, instead of 1231), except when

they straddle a relatively large multiple of a power of ten, in which case that

multiple is chosen (e.g. 1999..2001->2000).

Style parameter blacklist

In order to prevent unexpected consequences from using a style, style

files are no longer able to set parameters that affect things

unrelated to style. These parameters include::

Change in default font

The default font used by matplotlib in text has been changed to DejaVu Sans and

DejaVu Serif for the sans-serif and serif families, respectively. The DejaVu

font family is based on the previous matplotlib default --Bitstream Vera-- but

includes a much wider range of characters.

The default mathtext font has been changed from Computer Modern to the DejaVu

family to maintain consistency with regular text. Two new options for the

``mathtext.fontset`` configuration parameter have been added: ``dejavusans``

(default) and ``dejavuserif``. Both of these options use DejaVu glyphs whenever

possible and fall back to STIX symbols when a glyph is not found in DejaVu. To

return to the previous behavior, set the rcParam ``mathtext.fontset`` to ``cm``.

Faster text rendering

Rendering text in the Agg backend is now less fuzzy and about 20%

faster to draw.

Improvements for the Qt figure options editor

Various usability improvements were implemented for the Qt figure options

editor, among which:

- Line style entries are now sorted without duplicates.

- The colormap and normalization limits can now be set for images.

- Line edits for floating values now display only as many digits as necessary

to avoid precision loss. An important bug was also fixed regarding input

validation using Qt5 and a locale where the decimal separator is ",".

- The axes selector now uses shorter, more user-friendly names for axes, and

does not crash if there are no axes.

- Line and image entries using the default labels ("_lineX", "_imageX") are now

sorted numerically even when there are more than 10 entries.

Improved image support

Prior to version 2.0, matplotlib resampled images by first applying

the color map and then resizing the result. Since the resampling was

performed on the colored image, this introduced colors in the output

image that didn't actually exist in the color map. Now, images are

resampled first (and entirely in floating-point, if the input image is

floating-point), and then the color map is applied.

In order to make this important change, the image handling code was

almost entirely rewritten. As a side effect, image resampling uses

less memory and fewer datatype conversions than before.

The experimental private feature where one could "skew" an image by

setting the private member ``_image_skew_coordinate`` has been

removed. Instead, images will obey the transform of the axes on which

they are drawn.

Support for HiDPI (Retina) displays in the NbAgg and WebAgg backends

The NbAgg and WebAgg backends will now use the full resolution of your

high-pixel-density display.

New in matplotlib-1.5