plotly.express.density_contour

plotly.express.density_contour(data_frame=None, x=None, y=None, z=None, color=None, facet_row=None, facet_col=None, facet_col_wrap=0, hover_name=None, hover_data=None, animation_frame=None, animation_group=None, category_orders={}, labels={}, orientation=None, color_discrete_sequence=None, color_discrete_map={}, marginal_x=None, marginal_y=None, trendline=None, trendline_color_override=None, log_x=False, log_y=False, range_x=None, range_y=None, histfunc=None, histnorm=None, nbinsx=None, nbinsy=None, title=None, template=None, width=None, height=None)

In a density contour plot, rows of data_frame are grouped together into contour marks to visualize the 2D distribution of an aggregate function histfunc (e.g. the count or sum) of the value z.

Parameters
  • data_frame (DataFrame or array-like or dict) – This argument needs to be passed for column names (and not keyword names) to be used. Array-like and dict are tranformed internally to a pandas DataFrame. Optional: if missing, a DataFrame gets constructed under the hood using the other arguments.

  • x (str or int or Series or array-like) – Either a name of a column in data_frame, or a pandas Series or array_like object. Values from this column or array_like are used to position marks along the x axis in cartesian coordinates. Either x or y can optionally be a list of column references or array_likes, in which case the data will be treated as if it were ‘wide’ rather than ‘long’.

  • y (str or int or Series or array-like) – Either a name of a column in data_frame, or a pandas Series or array_like object. Values from this column or array_like are used to position marks along the y axis in cartesian coordinates. Either x or y can optionally be a list of column references or array_likes, in which case the data will be treated as if it were ‘wide’ rather than ‘long’.

  • z (str or int or Series or array-like) – Either a name of a column in data_frame, or a pandas Series or array_like object. Values from this column or array_like are used to position marks along the z axis in cartesian coordinates. For density_heatmap and density_contour these values are used as the inputs to histfunc.

  • color (str or int or Series or array-like) – Either a name of a column in data_frame, or a pandas Series or array_like object. Values from this column or array_like are used to assign color to marks.

  • facet_row (str or int or Series or array-like) – Either a name of a column in data_frame, or a pandas Series or array_like object. Values from this column or array_like are used to assign marks to facetted subplots in the vertical direction.

  • facet_col (str or int or Series or array-like) – Either a name of a column in data_frame, or a pandas Series or array_like object. Values from this column or array_like are used to assign marks to facetted subplots in the horizontal direction.

  • facet_col_wrap (int) – Maximum number of facet columns. Wraps the column variable at this width, so that the column facets span multiple rows. Ignored if 0, and forced to 0 if facet_row or a marginal is set.

  • hover_name (str or int or Series or array-like) – Either a name of a column in data_frame, or a pandas Series or array_like object. Values from this column or array_like appear in bold in the hover tooltip.

  • hover_data (list of str or int, or Series or array-like, or dict) – Either a list of names of columns in data_frame, or pandas Series, or array_like objects or a dict with column names as keys, with values True (for default formatting) False (in order to remove this column from hover information), or a formatting string, for example ‘:.3f’ or ‘|%a’ or list-like data to appear in the hover tooltip or tuples with a bool or formatting string as first element, and list-like data to appear in hover as second element Values from these columns appear as extra data in the hover tooltip.

  • animation_frame (str or int or Series or array-like) – Either a name of a column in data_frame, or a pandas Series or array_like object. Values from this column or array_like are used to assign marks to animation frames.

  • animation_group (str or int or Series or array-like) – Either a name of a column in data_frame, or a pandas Series or array_like object. Values from this column or array_like are used to provide object-constancy across animation frames: rows with matching `animation_group`s will be treated as if they describe the same object in each frame.

  • category_orders (dict with str keys and list of str values (default {})) – By default, in Python 3.6+, the order of categorical values in axes, legends and facets depends on the order in which these values are first encountered in data_frame (and no order is guaranteed by default in Python below 3.6). This parameter is used to force a specific ordering of values per column. The keys of this dict should correspond to column names, and the values should be lists of strings corresponding to the specific display order desired.

  • labels (dict with str keys and str values (default {})) – By default, column names are used in the figure for axis titles, legend entries and hovers. This parameter allows this to be overridden. The keys of this dict should correspond to column names, and the values should correspond to the desired label to be displayed.

  • orientation (str, one of 'h' for horizontal or 'v' for vertical.) – (default 'v' if x and y are provided and both continous or both categorical, otherwise 'v'`(‘h’) if `x`(`y) is categorical and y`(`x) is continuous, otherwise 'v'`(‘h’) if only `x`(`y) is provided)

  • color_discrete_sequence (list of str) – Strings should define valid CSS-colors. When color is set and the values in the corresponding column are not numeric, values in that column are assigned colors by cycling through color_discrete_sequence in the order described in category_orders, unless the value of color is a key in color_discrete_map. Various useful color sequences are available in the plotly.express.colors submodules, specifically plotly.express.colors.qualitative.

  • color_discrete_map (dict with str keys and str values (default {})) – String values should define valid CSS-colors Used to override color_discrete_sequence to assign a specific colors to marks corresponding with specific values. Keys in color_discrete_map should be values in the column denoted by color. Alternatively, if the values of color are valid colors, the string 'identity' may be passed to cause them to be used directly.

  • marginal_x (str) – One of 'rug', 'box', 'violin', or 'histogram'. If set, a horizontal subplot is drawn above the main plot, visualizing the x-distribution.

  • marginal_y (str) – One of 'rug', 'box', 'violin', or 'histogram'. If set, a vertical subplot is drawn to the right of the main plot, visualizing the y-distribution.

  • trendline (str) – One of 'ols' or 'lowess'. If 'ols', an Ordinary Least Squares regression line will be drawn for each discrete-color/symbol group. If 'lowess’, a Locally Weighted Scatterplot Smoothing line will be drawn for each discrete-color/symbol group.

  • trendline_color_override (str) – Valid CSS color. If provided, and if trendline is set, all trendlines will be drawn in this color.

  • log_x (boolean (default False)) – If True, the x-axis is log-scaled in cartesian coordinates.

  • log_y (boolean (default False)) – If True, the y-axis is log-scaled in cartesian coordinates.

  • range_x (list of two numbers) – If provided, overrides auto-scaling on the x-axis in cartesian coordinates.

  • range_y (list of two numbers) – If provided, overrides auto-scaling on the y-axis in cartesian coordinates.

  • histfunc (str (default 'count' if no arguments are provided, else 'sum')) – One of 'count', 'sum', 'avg', 'min', or 'max'.Function used to aggregate values for summarization (note: can be normalized with histnorm). The arguments to this function are the values of z.

  • histnorm (str (default None)) – One of 'percent', 'probability', 'density', or 'probability density' If None, the output of histfunc is used as is. If 'probability', the output of histfunc for a given bin is divided by the sum of the output of histfunc for all bins. If 'percent', the output of histfunc for a given bin is divided by the sum of the output of histfunc for all bins and multiplied by 100. If 'density', the output of histfunc for a given bin is divided by the size of the bin. If 'probability density', the output of histfunc for a given bin is normalized such that it corresponds to the probability that a random event whose distribution is described by the output of histfunc will fall into that bin.

  • nbinsx (int) – Positive integer. Sets the number of bins along the x axis.

  • nbinsy (int) – Positive integer. Sets the number of bins along the y axis.

  • title (str) – The figure title.

  • template (str or dict or plotly.graph_objects.layout.Template instance) – The figure template name (must be a key in plotly.io.templates) or definition.

  • width (int (default None)) – The figure width in pixels.

  • height (int (default None)) – The figure height in pixels.

Returns

Return type

plotly.graph_objects.Figure