Help on function create_facet_grid in module plotly.figure_factory._facet_grid:

create_facet_grid(df, x=None, y=None, facet_row=None, facet_col=None, color_name=None, colormap=None, color_is_cat=False, facet_row_labels=None, facet_col_labels=None, height=None, width=None, trace_type='scatter', scales='fixed', dtick_x=None, dtick_y=None, show_boxes=True, ggplot2=False, binsize=1, **kwargs)
    Returns figure for facet grid.
    
    :param (pd.DataFrame) df: the dataframe of columns for the facet grid.
    :param (str) x: the name of the dataframe column for the x axis data.
    :param (str) y: the name of the dataframe column for the y axis data.
    :param (str) facet_row: the name of the dataframe column that is used to
        facet the grid into row panels.
    :param (str) facet_col: the name of the dataframe column that is used to
        facet the grid into column panels.
    :param (str) color_name: the name of your dataframe column that will
        function as the colormap variable.
    :param (str|list|dict) colormap: the param that determines how the
        color_name column colors the data. If the dataframe contains numeric
        data, then a dictionary of colors will group the data categorically
        while a Plotly Colorscale name or a custom colorscale will treat it
        numerically. To learn more about colors and types of colormap, run
        `help(plotly.colors)`.
    :param (bool) color_is_cat: determines whether a numerical column for the
        colormap will be treated as categorical (True) or sequential (False).
            Default = False.
    :param (str|dict) facet_row_labels: set to either 'name' or a dictionary
        of all the unique values in the faceting row mapped to some text to
        show up in the label annotations. If None, labeling works like usual.
    :param (str|dict) facet_col_labels: set to either 'name' or a dictionary
        of all the values in the faceting row mapped to some text to show up
        in the label annotations. If None, labeling works like usual.
    :param (int) height: the height of the facet grid figure.
    :param (int) width: the width of the facet grid figure.
    :param (str) trace_type: decides the type of plot to appear in the
        facet grid. The options are 'scatter', 'scattergl', 'histogram',
        'bar', and 'box'.
        Default = 'scatter'.
    :param (str) scales: determines if axes have fixed ranges or not. Valid
        settings are 'fixed' (all axes fixed), 'free_x' (x axis free only),
        'free_y' (y axis free only) or 'free' (both axes free).
    :param (float) dtick_x: determines the distance between each tick on the
        x-axis. Default is None which means dtick_x is set automatically.
    :param (float) dtick_y: determines the distance between each tick on the
        y-axis. Default is None which means dtick_y is set automatically.
    :param (bool) show_boxes: draws grey boxes behind the facet titles.
    :param (bool) ggplot2: draws the facet grid in the style of `ggplot2`. See
        http://ggplot2.tidyverse.org/reference/facet_grid.html for reference.
        Default = False
    :param (int) binsize: groups all data into bins of a given length.
    :param (dict) kwargs: a dictionary of scatterplot arguments.
    
    Examples 1: One Way Faceting
    ```
    import plotly.plotly as py
    import plotly.figure_factory as ff
    
    import pandas as pd
    
    mpg = pd.read_table('https://raw.githubusercontent.com/plotly/datasets/master/mpg_2017.txt')
    
    fig = ff.create_facet_grid(
        mpg,
        x='displ',
        y='cty',
        facet_col='cyl',
    )
    py.iplot(fig, filename='facet_grid_mpg_one_way_facet')
    ```
    
    Example 2: Two Way Faceting
    ```
    import plotly.plotly as py
    import plotly.figure_factory as ff
    
    import pandas as pd
    
    mpg = pd.read_table('https://raw.githubusercontent.com/plotly/datasets/master/mpg_2017.txt')
    
    fig = ff.create_facet_grid(
        mpg,
        x='displ',
        y='cty',
        facet_row='drv',
        facet_col='cyl',
    )
    py.iplot(fig, filename='facet_grid_mpg_two_way_facet')
    ```
    
    Example 3: Categorical Coloring
    ```
    import plotly.plotly as py
    import plotly.figure_factory as ff
    
    import pandas as pd
    
    mpg = pd.read_table('https://raw.githubusercontent.com/plotly/datasets/master/mpg_2017.txt')
    
    fig = ff.create_facet_grid(
        mtcars,
        x='mpg',
        y='wt',
        facet_col='cyl',
        color_name='cyl',
        color_is_cat=True,
    )
    py.iplot(fig, filename='facet_grid_mpg_default_colors')
    ```
    
    Example 4: Sequential Coloring
    ```
    import plotly.plotly as py
    import plotly.figure_factory as ff
    
    import pandas as pd
    
    tips = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/tips.csv')
    
    fig = ff.create_facet_grid(
        tips,
        x='total_bill',
        y='tip',
        facet_row='sex',
        facet_col='smoker',
        color_name='size',
        colormap='Viridis',
    )
    py.iplot(fig, filename='facet_grid_tips_sequential_colors')
    ```
    
    Example 5: Custom labels
    ```
    import plotly.plotly as py
    import plotly.figure_factory as ff
    
    import pandas as pd
    
    mtcars = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/mtcars.csv')
    
    fig = ff.create_facet_grid(
        mtcars,
        x='wt',
        y='mpg',
        facet_col='cyl',
        facet_col_labels={4: "$\alpha$", 6: '$\beta$', 8: '$\sqrt[y]{x}$'},
    )
    
    py.iplot(fig, filename='facet_grid_mtcars_custom_labels')
    ```
    
    Example 6: Other Trace Type
    ```
    import plotly.plotly as py
    import plotly.figure_factory as ff
    
    import pandas as pd
    
    mtcars = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/mtcars.csv')
    
    fig = ff.create_facet_grid(
        mtcars,
        x='wt',
        facet_col='cyl',
        trace_type='histogram',
    )
    
    py.iplot(fig, filename='facet_grid_mtcars_other_trace_type')
    ```

Collecting git+https://github.com/plotly/publisher.git
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Installing collected packages: publisher
  Found existing installation: publisher 0.11
    Uninstalling publisher-0.11:
      Successfully uninstalled publisher-0.11
  Running setup.py install for publisher ... done
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The `IPython.nbconvert` package has been deprecated since IPython 4.0. You should import from nbconvert instead.

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