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Commit792dfdf

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Merge pull request#22 from matplotlib/typos
Fixing typos and links
2 parentsfcd1fd7 +7f673d8 commit792dfdf

5 files changed

+13
-15
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‎AnatomyOfMatplotlib-Part1-Figures_Subplots_and_layouts.ipynb

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"[Matplotlib](https://github.com/matplotlib) is hosted by GitHub.\n",
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"\n",
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"### Bug Reports and feature requests\n",
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"So, you think you found a bug? Or maybe you think some feature is just too difficult to use? Or missing altogether? Submit your bug reports [here](https://github.com/matplotlib/matplotlib/issues) at Matplotlib's issue tracker. We even have a process for submitting and discussing Matplotlib Enhancement Proposals ([MEPs](http://matplotlib.org/devdocs/devel/MEP/index.html))."
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"So, you think you found a bug? Or maybe you think some feature is just too difficult to use? Or missing altogether? Submit your bug reports [here](https://github.com/matplotlib/matplotlib/issues) at Matplotlib's issue tracker. We even have a process for submitting and discussing Matplotlib Enhancement Proposals ([MEPs](https://matplotlib.org/devel/MEP/index.html))."
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{
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"\n",
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"However, while we're on the topic, you can control the size of the figure through the ``figsize`` argument, which expects a tuple of ``(width, height)`` in inches.\n",
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"\n",
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"A really useful utility function is [`figaspect`](http://matplotlib.org/api/figure_api.html?highlight=figaspect#matplotlib.figure.figaspect)"
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"A really useful utility function is [`figaspect`](https://matplotlib.org/api/_as_gen/matplotlib.figure.figaspect.html?highlight=figaspect#matplotlib.figure.figaspect)"
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]
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‎AnatomyOfMatplotlib-Part3-HowToSpeakMPL.ipynb

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"- k: black\n",
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"- w: white\n",
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"\n",
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"Other colornames that are allowed are the HTML/CSS colornames such as\"burlywood\" and\"chartreuse\". See the [full list](http://www.w3schools.com/html/html_colornames.asp) of the147 colornames.\n",
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"Other colornames that are allowed are the HTML/CSS colornames such as\"burlywood\" and\"chartreuse\". See the [full list](https://www.w3schools.com/Colors/colors_names.asp) of the140 color names.\n",
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"\n",
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"Matplotlib supports the [xkcd color names](https://xkcd.com/color/rgb/) prefxed by `'xkcd:'`.\n",
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"\n",
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"1 | tickright ||5 | caretright ||\">\" | triangle_right||\"4\" | tri_right\n",
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"2 | tickup ||6 | caretup ||\"^\" | triangle_up ||\"2\" | tri_up\n",
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"3 | tickdown ||7 | caretdown ||\"v\" | triangle_down ||\"1\" | tri_down\n",
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"\"None\" | nothing ||`None` |nothing ||\"\" | nothing ||\"\" | nothing"
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"\"None\" | nothing ||`None` |default ||\"\" | nothing ||\"\" | nothing"
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]
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},
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{
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"\"octagon\",\"square\",\"pentagon\",\"star\",\"vertical bar\",\"horizontal bar\",\"hexagon 1\",\"hexagon 2\",\n",
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"\"tick left\",\"caret left\",\"triangle left\",\"tri left\",\"tick right\",\"caret right\",\"triangle right\",\"tri right\",\n",
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"\"tick up\",\"caret up\",\"triangle up\",\"tri up\",\"tick down\",\"caret down\",\"triangle down\",\"tri down\",\n",
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"\"Nothing\",\"Nothing\",\"Nothing\",\"Nothing\"]\n",
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"\"Nothing\",\"default\",\"Nothing\",\"Nothing\"]\n",
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"fig, ax = plt.subplots(1, 1, figsize=(7.5, 4))\n",
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"for x, y, m, d in zip(xs.T.flat, ys.T.flat, markers, descripts):\n",
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" ax.scatter(x, y, marker=m, s=100)\n",

‎AnatomyOfMatplotlib-Part4-Limits_Legends_and_Layouts.ipynb

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"* A Tick Label is the text that is displayed at that tick.\n",
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"* A [`Ticker`](http://matplotlib.org/api/ticker_api.html#module-matplotlib.ticker) automatically determines the ticks for an Axis and formats the tick labels.\n",
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"\n",
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"[`tick_params()`](http://matplotlib.org/api/axes_api.html#matplotlib.axes.Axes.tick_params) is often used to help configure your tickers."
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"[`tick_params()`](https://matplotlib.org/api/axes_api.html#ticks-and-tick-labels) is often used to help configure your tickers."
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"cell_type":"markdown",
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"metadata": {},
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"source": [
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"A commonly-asked question is\"How do I plotnon-numericalcategories?\"\n",
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"\n",
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"Currently, the easiest way to do this is to\"fake\" the x-values and then change the tick labels to reflect the category.\n",
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"A commonly-asked question is\"How do I plot categories?\"\n",
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"\n",
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"Starting in version 2.0 of mpl, just like any other data.\n",
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"\n",
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"For example:"
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"fruit, value = zip(*data)\n",
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"\n",
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"fig, ax = plt.subplots()\n",
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"x = np.arange(len(fruit))\n",
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"ax.bar(x, value, align='center', color='gray')\n",
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"ax.set(xticks=x, xticklabels=fruit)\n",
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"ax.bar(fruit, value, align='center', color='gray')\n",
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"plt.show()"
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]
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‎AnatomyOfMatplotlib-Part5-Artists.ipynb

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"cell_type":"markdown",
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"metadata": {},
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"source": [
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"To see what properties are set for an artist, use [`getp()`](http://matplotlib.org/api/artist_api.html#matplotlib.artist.getp)"
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"To see what properties are set for an artist, use [`getp()`](https://matplotlib.org/api/artist_api.html#functions)"
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]
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{
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"metadata": {},
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"source": [
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"# Collections\n",
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"In addition to the Figure and Axes containers, there is another special type of container called a [`Collection`](http://matplotlib.org/api/collections_api.html). A Collection usually contains a list of primitives of the same kind that should all be treated similiarly. For example, a [`CircleCollection`](http://matplotlib.org/api/collections_api.html#matplotlib.collections.CircleCollection) would have a list of [`Circle`](http://matplotlib.org/api/artist_api.html#matplotlib.patches.Circle) objects all with the same color, size, and edge width. Individual property values for artists in the collection can also be set (in some cases)."
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"In addition to the Figure and Axes containers, there is another special type of container called a [`Collection`](http://matplotlib.org/api/collections_api.html). A Collection usually contains a list of primitives of the same kind that should all be treated similiarly. For example, a [`CircleCollection`](http://matplotlib.org/api/collections_api.html#matplotlib.collections.CircleCollection) would have a list of [`Circle`](https://matplotlib.org/api/_as_gen/matplotlib.patches.Circle.html) objects all with the same color, size, and edge width. Individual property values for artists in the collection can also be set (in some cases)."
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{

‎solutions/5.1-goldstar.py

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fig,ax=plt.subplots(1,1)
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offsets=zip([0.2,0.4,0.6,0.8], [0.5]*4)
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offsets=list(zip([0.2,0.4,0.6,0.8], [0.5]*4))
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collection=StarPolygonCollection(5,
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offsets=offsets,
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transOffset=ax.transData,

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