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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.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', ... ) >>> fig.show() Example 2: Two Way Faceting >>> 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', ... ) >>> fig.show() Example 3: Categorical Coloring >>> import plotly.figure_factory as ff >>> import pandas as pd >>> mtcars = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/mtcars.csv') >>> mtcars.cyl = mtcars.cyl.astype(str) >>> fig = ff.create_facet_grid( ... mtcars, ... x='mpg', ... y='wt', ... facet_col='cyl', ... color_name='cyl', ... color_is_cat=True, ... ) >>> fig.show() z3'pandas' must be installed for this figure_factory.z"You must input a pandas DataFrame.rvz`You need to input 'x' and 'y' if you are you are using a trace_type of 'scatter' or 'scattergl'.NzIx, y, facet_row, facet_col and color_name must be keys in your dataframe.free)rfree_xfree_yrz?'scales' must be set to 'fixed', 'free_x', 'free_y' and 'free'.z'trace_type' must be in {}rgQ?gQ?ryr.r-r opacityg333333?radarkgreyr r\zrgb(31, 119, 180)z rgb(0, 0, 0)FrTrgbzxIf using 'colormap' as a dictionary, make sure all the values of the colormap column are in the keys of your dictionary.zlIf 'colormap' is a string, it must be the name of a Plotly Colorscale. 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