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        "author": "Daniel Hitchcock",
        "author_email": "daniel.s.hitchcock@gmail.com",
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            "License :: OSI Approved :: MIT License",
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            "Programming Language :: Python :: 3"
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        "description": "# Plotxel\n\n*Control your plots down to the pixel!*  \nEver have trouble moving a chart to the right? Moving your axis up? Getting rid of ticks? Then try out Plotxel!\n\nIt's wordy, slow, and unnecessary 99% of the time. But that 1%, you'll be glad you have Plotxel.\n\n## Installation\n\n    pip3 install plotxel\n\n## Example\n\n![Example Image](https://github.com/danhitchcock/plotxel/wiki/example2.png)\n```python\nfrom plotxel import Plotxel, Axis\n\nx = Plotxel()  # our main drawing canvas in x, y\n\n# add some data as a series. The series name, the x data, and y data\nseries1 = [i for i in range(10)]\nx.add_data('series1', series1, series1)\nx.add_data('series2', [1, 2, 3, 4, 5, 10], [5, 2, 1, 4, 3, 10])\nx.add_data('series3', [10, 5, 4, 3, 2, 1], [5, 2, 1, 4, 3, 10])\n\n# left plot -- its name, type, and data it's linked to\nplot1 = x.add_drawable(\"plot1\", \"Scatter\", [\"series1\", 'series2', 'series3'])\nplot1.title = 'Analysis of Goose Encounters'\nplot1.pos = [60, 50]\nplot1.title_offset = 23\nplot1.marker_opacity = {.5}  # this must be a set so it can iterate through data. Will make this more intuitive\n\n# right plot and its position. Same data as plot1\nplot2 = x.add_drawable(\"plot2\", \"Scatter\", \"series1\")\n# set a bunch of attributes at once!\nplot2.setattrs(\n    ylim=[-1, 10],\n    xlim=[-1, 10],\n    pos=[450, 50],\n    marker_shape='square',\n    marker_fill_color=(255, 0, 0),\n    title='Analysis of Goose Encounters (red)',\n    line_width = 0\n)\n\n# add some axes, and link them to our plots. It will copy the size, position, scale, and limits of whichever plot it is linked to\nax1 = x.add_drawable(\"ax1\", 'YAxis', link_to=\"plot1\")\nax1.axis_offset = 10\nax1.title_offset = 25  # distance from the ticks. Will have an auto feature in the future!\nax1.title = \"Near Death Experiences With Geese\"\n\n# all other axes, let's put them flush with the graph by changing the default\n# defaults are copied at the time the object is initialized, so this won't affect ax1\nAxis.defaults['axis_offset'] = -1\nax1b = x.add_drawable('ax1b', 'XAxis', link_to='plot1')\n\n# you can keep setting attributes in bulk\nax1r = x.add_drawable('ax1r', 'YAxis', link_to='plot1', title_offset=20)\nax1r.setattrs(\n    side='right',\n    title_offset=20,\n    title='Ax1 Right Title'\n)\n\nax1t = x.add_drawable('ax1t', 'XAxis', link_to='plot1')\nax1t.setattrs(\n    side='top',\n    title=''\n)\n\n# or use the constructor!\nx.add_drawable(\"ax2\", 'YAxis', link_to=\"plot2\", title_offset=20, side='right', axis_offset=10)\n\nax3 = x.add_drawable(\"ax3\", 'XAxis', link_to=\"plot2\")\nax3.setattrs(\n    side='bottom',\n    axis_offset=10,\n    title=\"Number of Freaking Geese\",\n)\n\n\n# I think I would prefer axes to be blue!\nAxis.defaults['color'] = (0, 0, 255)\n\n# let's add some bar chart data. Since it's a vertical bar chart, we will pull Y data\n# the labels aren't implemented quite yet\nx.add_data('bar_data', ['Sunday', 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday'], [1, 9, 4, 5, 3, 6, 2])\nx.add_data('bar_data2', ['Sunday', 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday'], [1, 7, 4, 3, 4, 5, 1])\nx.add_data('bar_data3', ['Sunday', 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday'], [-3, 14, 2, 1, 2, 7, 9])\n\nplot3 = x.add_drawable('bar1', 'Bar', ['bar_data', 'bar_data2', 'bar_data3'])\n# or unpack a dict\nplot3_attrs = {\n    'pos': (150, 300),\n    'dim': (500, 150),\n    'ylim': [-5, 15],\n    'group_spacing': 30,\n    'bar_spacing': 0,\n    'title': 'Safely Navigating Geese'\n}\nplot3.setattrs(**plot3_attrs)\n\nx.add_drawable('ax4', 'YAxis', link_to=\"bar1\", title='Likelihood of Goose Attack', title_offset=25)\n# x.add_drawable('ax5', 'XAxis', link_to='bar1', title='Day of Week', title_offset=5)\n\n# coming soon, Jupyter magic!\n# x.anti_aliasing=False\nx.show()\n\n# or for SVG\n# svg_html = x.draw()\n\n# or for image  in BytesIO / save to filename\n# x.render(filename='example2.png')\n```\n\n\n\n\nThis program is being developed based on my own needs, and unfortunately I don't do a lot of plotting today, therefore I don't need a lot of features.\n\nIn any case, I'll be prioritizing features, up next is bar charts and histograms! \n\n",
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