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mdehoonmdehoon
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Getting the pdfs.
Merge branch 'master' of git://github.com/matplotlib/matplotlib into fixForIssue4977MacOSX
2 parents 9dfec01 + b9bc7d1 commit 6c1dc52

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‎.gitignore‎

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.project
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.pydevproject
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.swp
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.idea
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# Compiled source #
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###################

‎.travis.yml‎

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- secure: "dfjNqGKzQG5bu3FnDNwLG8H/C4QoieFo4PfFmZPdM2RY7WIzukwKFNT6kiDfOrpwt+2bR7FhzjOGlDECGtlGOtYPN8XuXGjhcP4a4IfakdbDfF+D3NPIpf5VlE6776k0VpvcZBTMYJKNFIMc7QPkOwjvNJ2aXyfe3hBuGlKJzQU="
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- BUILD_DOCS=false
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- NUMPY=numpy
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- PANDAS=
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- NPROC=2
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- TEST_ARGS=--no-pep8
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- python: 2.6
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env: NUMPY=numpy==1.6 MOCK=mock==1.0.1
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- python: 2.7
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env: MOCK=mock
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env: MOCK=mock PANDAS=pandas
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- python: 3.3
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- python: 3.4
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- python: 2.7
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env: TEST_ARGS=--pep8
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- python: 2.7
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env: BUILD_DOCS=true MOCK=mock
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- python: "3.5.0rc2"
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- python: "3.5.0rc4"
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env: PRE=--pre
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before_install:
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pip install --upgrade setuptools
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# Install only from travis wheelhouse
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- if [ -z "$PRE" ]; then
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wheelhouse_pip_install python-dateutil $NUMPY pyparsing pillow sphinx!=1.3.0;
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wheelhouse_pip_install python-dateutil $NUMPY $PANDAS pyparsing pillow sphinx!=1.3.0;
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else
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pip install $PRE python-dateutil $NUMPY pyparsing pillow sphinx!=1.3.0;
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fi

‎boilerplate.py‎

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itself, whereas the generatable content must be edited via templates in
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this file.
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This file is python 3 only due to the use of `inspect`
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"""
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# We did try to do the wrapping the smart way,
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# with callable functions and new.function, but could never get the
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mappable = ''
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# Get argspec of wrapped function
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args, varargs, varkw, defaults = inspect.getargspec(getattr(Axes, func))
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base_func = getattr(Axes, func)
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has_data = 'data' in inspect.signature(base_func).parameters
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work_func = inspect.unwrap(base_func)
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args, varargs, varkw, defaults = inspect.getargspec(work_func)
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args.pop(0) # remove 'self' argument
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if defaults is None:
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defaults = ()
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def_edited.append(val)
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defaults = tuple(def_edited)
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# Add a data keyword argument if needed (fmt is PLOT_TEMPLATE) and
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# possible (if *args is used, we can't just add a data
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# argument in front of it since it would gobble one of the
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# arguments the user means to pass via *args)
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# This needs to be done here so that it goes into call
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if not varargs and fmt is PLOT_TEMPLATE and has_data:
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args.append('data')
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defaults = defaults + (None,)
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# How to call the wrapped function
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call = []
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for i, arg in enumerate(args):
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else:
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call.append('%s=%s' % (arg, arg))
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# remove the data keyword as it was needed above to go into the
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# call but should go after `hold` in the signature.
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# This is janky as all get out, but hopefully boilerplate will
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# be retired soon.
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if not varargs and fmt is PLOT_TEMPLATE and has_data:
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args.pop()
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defaults = defaults[:-1]
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if varargs is not None:
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call.append('*' + varargs)
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if varkw is not None:
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elif fmt is PLOT_TEMPLATE:
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args.append('hold')
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defaults = defaults + (None,)
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if has_data:
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args.append('data')
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defaults = defaults + (None,)
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sethold = ''
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# Now we can build the argspec for defining the wrapper

‎doc/users/whats_new/2015-07-30_unpack_labeled_data.rst‎

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Working with labeled data like pandas DataFrames
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------------------------------------------------
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Plot methods which take arrays as inputs can now also work with labeled data
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and unpack such data.
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This means that the following two examples produce the same plot:
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Example ::
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df = pandas.DataFrame({"var1":[1,2,3,4,5,6], "var2":[1,2,3,4,5,6]})
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plt.plot(df["var1"], df["var2"])
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Example ::
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plt.plot("var1", "var2", data=df)
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This works for most plotting methods, which expect arrays/sequences as
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inputs. ``data`` can be anything which supports ``__getitem__``
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(``dict``, ``pandas.DataFrame``, ``h5py``, ...) to access ``array`` like
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values with string keys.
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In addition to this, some other changes were made, which makes working with
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labeled data (ex ``pandas.Series``) easier:
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* For plotting methods with ``label`` keyword argument, one of the
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data inputs is designated as the label source. If the user does not
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supply a ``label`` that value object will be introspected for a
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label, currently by looking for a ``name`` attribute. If the value
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object does not have a ``name`` attribute but was specified by as a
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key into the ``data`` kwarg, then the key is used. In the above
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examples, this results in an implicit ``label="var2"`` for both
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cases.
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* ``plot()`` now uses the index of a ``Series`` instead of
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``np.arange(len(y))``, if no ``x`` argument is supplied.

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