Metadata-Version: 1.1
Name: iplotter
Version: 0.4.2
Summary: JavaScript Charting for iPython/Jupyter notebooks
Home-page: https://github.com/niloch/iplotter
Author: csulliva
Author-email: csulliva@brandeis.edu
License: MIT
Description: IPlotter
        ========
        
        |PyPI version|
        
        JavaScript charting in ipython/jupyter notebooks
        ------------------------------------------------
        
        .. raw:: html
        
           <!-- MarkdownTOC -->
        
        -  `Installation <#installation>`__
        -  `C3.js <#c3js>`__
        -  `plotly.js <#plotlyjs>`__
        -  `Chart.js <#chartjs>`__
        -  `Chartist.js <#chartistjs>`__
        -  `Google Charts <#google-charts>`__
        -  `Usage <#usage>`__
        -  `Examples <#examples>`__
        
           -  `C3 Stacked Area Spline Chart <#c3-stacked-area-spline-chart>`__
           -  `plotly.js HeatMap <#plotlyjs-heatmap>`__
           -  `Chart.js Radar Chart <#chartjs-radar-chart>`__
           -  `Chartist.js Bipolar Area
              Chart <#chartistjs-bipolar-area-chart>`__
           -  `Google Charts stacked Column
              Chart <#google-charts-stacked-column-chart>`__
        
        -  `Multple Charts and Mixing
           Libraries <#multple-charts-and-mixing-libraries>`__
        -  `Exporting plots to PNG images with
           Selenium <#exporting-plots-to-png-images-with-selenium>`__
        
        .. raw:: html
        
           <!-- /MarkdownTOC -->
        
        iplotter is a simple package for generating interactive charts in
        ipython/jupyter notebooks using popular JavaScript Libraries from python
        data structures (dictionaries, lists, etc.)
        
         ## Installation To install the most recent stable release run
        ``pip install iplotter``.
        
        To install the latest version run
        ``pip install git+git://github.com/niloch/iplotter.git@master`` or
        ``git clone https://github.com/niloch/iplotter.git`` followed by
        ``pip install -e iplotter/``
        
         ## `C3.js <http://c3js.org/>`__
        
        C3 is a charting library based on d3.js for making interactive and easy
        to understand charts, graphs, and plots. Charts have animated
        transitions for hiding/displaying data.
        
         ## `plotly.js <https://plot.ly/javascript/>`__
        
        Plotly.js is a charting library based on d3.js. While plotly provides a
        native client in python, it requires the user to create an account and
        by default makes all plots public. plotly.js can be used without
        creating an account and are rendered locally to keep data private.
        
         ## `Chart.js <http://www.chartjs.org/>`__
        
        Chart.js provides 6 chart types via HTML5 canvas elements with
        tooltips/hover events in very a lightweight library.
        
         ## `Chartist.js <http://gionkunz.github.io/chartist-js/index.html>`__
        
        Simple and Responsive SVG charts with media queries and animations.
        
         ## `Google Charts <https://developers.google.com/chart/>`__
        
        Simple and Powerful interactive charts with SVG/VML formats.
        
         ## Usage
        
        iplotter attempts to maintain a consistent API across JavaScript
        Libraries as much as possible, with slight parameter variations. Each
        library class supports the following functions: ``render``, ``plot``,
        ``save``, ``plot_and_save``. The python chart data,layout,options must
        be structured according to the JSON equivalent for each library (see
        `C3.js <http://c3js.org/>`__,
        `plotly.js <https://plot.ly/javascript/>`__,\ `Chart.js <http://www.chartjs.org/>`__,
        `Chartist.js <http://gionkunz.github.io/chartist-js/index.html>`__ and
        `Google Charts <https://developers.google.com/chart/>`__ for more
        examples). Plots can be rendered in ipython notebooks and saved to the
        current directory as html files.
        
         ## Examples
        
         ### C3 Stacked Area Spline Chart
        
        .. code:: python
        
            from iplotter import C3Plotter
        
            plotter = C3Plotter()
        
            chart = {
                "data": {
                    "columns": [
                        ['data1', 300, 350, 300, 0, 0, 120],
                        ['data2', 130, 100, 140, 200, 150, 50],
                        ['data3', 180, 75, 265, 100, 50, 100]
                    ],
                    "types": {
                        "data1": 'area-spline',
                        "data2": 'area-spline',
                        "data3": 'area-spline'
                    },
                    "groups": [['data1', 'data2', 'data3']]
                }
            }
        
            plotter.plot(chart)
        
        .. figure:: https://github.com/niloch/iplotter/blob/master/imgs/plot1.png?raw=true
           :alt: Plot 1
        
           Plot1
        
         ### plotly.js HeatMap
        
        .. code:: python
        
            from iplotter import PlotlyPlotter
        
            plotter = PlotlyPlotter()
        
            data = [
                {
                    'colorscale': 'YIGnBu',
                    'reversescale': True,
                    'type': 'heatmap',
                    'x': ['class1', 'class2', 'class3'],
                    'y': ['class1', 'class2', 'class3'],
                    'z': [[0.7,  0.2,  0.1],
                          [0.2,  0.7,  0.1],
                          [0.15,  0.27,  0.56]]
                }
            ]
        
            layout = {
                "title": 'Title',
                "xaxis": {
                    "tickangle": -45
                },
            }
        
            plotter.plot_and_save(data, layout=layout, w=600, h=600, filename='heatmap1', overwrite=True)
        
        .. figure:: https://github.com/niloch/iplotter/blob/master/imgs/plot3.png?raw=true
           :alt: Plot 3
        
           Plot3
        
         ### Chart.js Radar Chart
        
        .. code:: python
        
            from iplotter import ChartJSPlotter
        
            plotter = ChartJSPlotter()
        
            data = {
                "labels": ["Eating", "Drinking", "Sleeping", "Designing", "Coding",
                           "Cycling", "Running"],
                "datasets": [
                    {
                        "label": "Trace 1",
                        "backgroundColor": "rgba(179,181,198,0.2)",
                        "borderColor": "rgba(179,181,198,1)",
                        "pointBackgroundColor": "rgba(179,181,198,1)",
                        "pointBorderColor": "#fff",
                        "pointHoverBackgroundColor": "#fff",
                        "pointHoverBorderColor": "rgba(179,181,198,1)",
                        "data": [65, 59, 30, 81, 56, 55, 40]
                    }, {
                        "label": "Trace 2",
                        "backgroundColor": "rgba(255,99,132,0.2)",
                        "borderColor": "rgba(255,99,132,1)",
                        "pointBackgroundColor": "rgba(255,99,132,1)",
                        "pointBorderColor": "#fff",
                        "pointHoverBackgroundColor": "#fff",
                        "pointHoverBorderColor": "rgba(255,99,132,1)",
                        "data": [28, 48, 40, 19, 96, 27, 100]
                    }
                ]
            }
        
            plotter.plot_and_save(data, 'radar', options=None)
        
        .. figure:: https://github.com/niloch/iplotter/blob/master/imgs/plot4.png?raw=true
           :alt: Plot 4
        
           Plot4
        
         ### Chartist.js Bipolar Area Chart
        
        .. code:: python
        
            from iplotter import ChartistPlotter
        
            plotter = ChartistPlotter()
        
            data = {
                "labels": [1, 2, 3, 4, 5, 6, 7, 8],
                "series": [
                    [1, 2, 3, 1, -2, 0, 1, 0], [-2, -1, -2, -1, -2.5, -1, -2, -1],
                    [0, 0, 0, 1, 2, 2.5, 2, 1], [2.5, 2, 1, 0.5, 1, 0.5, -1, -2.5]
                ]
            }
            options = {
                "high": 4,
                "low": -3,
                "showArea": True,
                "showLine": False,
                "showPoint": False,
                "height": 420,
                "width": 700
            }
        
            plotter.save(data, chart_type="Line", options=options)
        
        .. figure:: https://github.com/niloch/iplotter/blob/master/imgs/plot6.png?raw=true
           :alt: Plot 6
        
           Plot6
        
         ### Google Charts stacked Column Chart
        
        .. code:: python
        
            from iplotter import GCPlotter
        
            plotter = GCPlotter()
        
            data = [
                ['Genre', 'Fantasy & Sci Fi', 'Romance', 'Mystery/Crime', 'General',
                 'Western', 'Literature', {"role": 'annotation'}],
                ['2010', 10, 24, 20, 32, 18, 5, ''],
                ['2020', 16, 22, 23, 30, 16, 9, ''],
                ['2030', 28, 19, 29, 30, 12, 13, '']
            ]
        
            options = {
                "width": 600,
                "height": 400,
                "legend": {"position": 'top', "maxLines": 3},
                "bar": {"groupWidth": '75%'},
                "isStacked": "true",
            }
        
            plotter.plot(data, chart_type="ColumnChart",chart_package='corechart', options=options)
        
        .. figure:: https://github.com/niloch/iplotter/blob/master/imgs/plot7.png?raw=true
           :alt: Plot 7
        
           Plot7
        
         ## Multple Charts and Mixing Libraries
        
        Saving multiple charts to one file or displaying multiple charts in one
        iframe can be achieved by concatenating html strings returned by the
        render function. The plotter's ``head`` attribute contains the script
        tags for loading the necessary JavasScript libraries and ``div_ids``
        must be unique. Charts from different libraries can be mixed together.
        
        .. code:: python
        
            from iplotter import PlotlyPlotter, C3Plotter
            from IPython.display import HTML
        
            plotly_plotter = PlotlyPlotter()
        
            c3_plotter = C3Plotter()
        
            plotly_chart = [{
                "type": 'choropleth',
                "locationmode": 'USA-states',
                "locations": ["AL", "AK", "AZ", "AR", "CA", "CO", "CT", "DE", "FL", "GA",
                              "HI", "ID", "IL", "IN", "IA", "KS", "KY", "LA", "ME", "MD",
                              "MA", "MI", "MN", "MS", "MO", "MT", "NE", "NV", "NH", "NJ",
                              "NM", "NY", "NC", "ND", "OH", "OK", "OR", "PA", "RI", "SC",
                              "SD", "TN", "TX", "UT", "VT", "VA", "WA", "WV", "WI", "WY"],
                "z": [1390.63, 13.31, 1463.17, 3586.02, 16472.88, 1851.33, 259.62, 282.19,
                      3764.09, 2860.84, 401.84, 2078.89, 8709.48, 5050.23, 11273.76,
                      4589.01, 1889.15, 1914.23, 278.37, 692.75, 248.65, 3164.16, 7192.33,
                      2170.8, 3933.42, 1718, 7114.13, 139.89, 73.06, 500.4, 751.58, 1488.9,
                      3806.05, 3761.96, 3979.79, 1646.41, 1794.57, 1969.87, 31.59, 929.93,
                      3770.19, 1535.13, 6648.22, 453.39, 180.14, 1146.48, 3894.81, 138.89,
                      3090.23, 349.69],
                "text":
                ["Alabama", "Alaska", "Arizona", "Arkansas", " California", "Colorado",
                 "Connecticut", "Delaware", "Florida", "Georgia", "Hawaii", "Idaho",
                 "Illinois", "Indiana", "Iowa", "Kansas", "Kentucky", "Louisiana", "Maine",
                 "Maryland", "Massachusetts", "Michigan", "Minnesota", "Mississippi",
                 "Missouri", "Montana", "Nebraska", "Nevada", "New Hampshire",
                 "New Jersey", "New Mexico", "New York", "North Carolina", "North Dakota",
                 "Ohio", "Oklahoma", "Oregon", "Pennsylvania", "Rhode Island",
                 "South Carolina", "South Dakota", "Tennessee", "Texas", "Utah", "Vermont",
                 "Virginia", "Washington", "West Virginia", "Wisconsin", "Wyoming"],
                "zmin": 0,
                "zmax": 17000,
                "colorscale": [
                    [0, 'rgb(242,240,247)'], [0.2, 'rgb(218,218,235)'],
                    [0.4, 'rgb(188,189,220)'], [0.6, 'rgb(158,154,200)'],
                    [0.8, 'rgb(117,107,177)'], [1, 'rgb(84,39,143)']
                ],
                "colorbar": {
                    "title": 'Millions USD',
                    "thickness": 0.2
                },
                "marker": {
                    "line": {
                        "color": 'rgb(255,255,255)',
                        "width": 2
                    }
                }
            }]
        
            plotly_layout = {
                "title": '2011 US Agriculture Exports by State',
                "geo": {
                    "scope": 'usa',
                    "showlakes": True,
                    "lakecolor": 'rgb(255,255,255)'
                }
            }
        
            c3_chart = {
                "data": {
                    "columns": [
                        ['data1', 300, 350, 300, 0, 0, 120],
                        ['data2', 130, 100, 140, 200, 150, 50],
                        ['data3', 180, 75, 265, 100, 50, 100]
                    ],
                    "type": "pie",
                }
            }
        
            # plotter.head will return the html string containing script tags for loading the plotly.js/C3.js libraries
            multiple_plot_html = plotly_plotter.head + c3_plotter.head
        
            multiple_plot_html += c3_plotter.render(data=c3_chart, div_id="chart_1")
        
            multiple_plot_html += plotly_plotter.render(
                data=plotly_chart, layout=plotly_layout, div_id="chart_2")
        
            # display multiple plots in iframe
            HTML(c3_plotter.iframe.format(source=multiple_plot_html, w=600, h=900))
            # Write multiple plots to file
            with open("multiple_plots.html", 'w') as outfile:
                outfile.write(multiple_plot_html)
        
        .. figure:: https://github.com/niloch/iplotter/blob/master/imgs/plot5.png?raw=true
           :alt: Plot 5
        
           Plot5
        
         ## Exporting plots to PNG images with
        `Selenium <http://www.seleniumhq.org/>`__
        
        Saved interactive HTML plots can be converted to static png images
        programatically for inclusion in other documents via a Selenium helper
        class. The user will need to download a compatible webdriver and include
        it in their PATH. The expected default is the `Chrome
        webdriver <https://sites.google.com/a/chromium.org/chromedriver/>`__
        
        Using the context manager syntax is recommended as in
        ``with VirtualBrowser() as browser`` to ensure the browswer session is
        properly released. However it can be used as a normal object by calling
        ``browser().quit()`` to end the session.
        
        .. code:: python
        
            from iplotter import C3Plotter, ChartJSPlotter, VirtualBrowser
        
            plotter1 = C3Plotter()
            plotter2 = ChartJSPlotter()
        
            ####  specify data for charts here...
        
            plotter1.save(data1, filename="chart1")  # save first plot to chart1.html
            plotter2.dave(data2, filename="chart2")  # save second plot to chart2.html
        
            charts = ["chart1", "chart2"]
        
            with VirtualBrowser() as browser:
                for chart in charts:
                    browser.save_as_png(
                        filename=chart, width=300,
                        height=200)  # save html chart to filename + '.png'
        
        .. |PyPI version| image:: https://badge.fury.io/py/iplotter.svg
           :target: https://badge.fury.io/py/iplotter
        
Keywords: ipython,plotly,c3.js,plot,chart,plotly.js,charts.js,chartist.js,jupyter
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
