plotly.express.line

plotly.express.line(data_frame=None, x=None, y=None, line_group=None, color=None, line_dash=None, symbol=None, hover_name=None, hover_data=None, custom_data=None, text=None, facet_row=None, facet_col=None, facet_col_wrap=0, facet_row_spacing=None, facet_col_spacing=None, error_x=None, error_x_minus=None, error_y=None, error_y_minus=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, orientation=None, color_discrete_sequence=None, color_discrete_map=None, line_dash_sequence=None, line_dash_map=None, symbol_sequence=None, symbol_map=None, markers=False, log_x=False, log_y=False, range_x=None, range_y=None, line_shape=None, render_mode='auto', title=None, template=None, width=None, height=None) → plotly.graph_objects._figure.Figure

In a 2D line plot, each row of data_frame is represented as vertex of a polyline mark in 2D space.

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 transformed 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’.

  • line_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 group rows of data_frame into lines.

  • 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.

  • line_dash (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 dash-patterns to lines.

  • symbol (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 symbols to marks.

  • 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 (str, or list of str or int, or Series or array-like, or dict) – Either a name or 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.

  • custom_data (str, or list of str or int, or Series or array-like) – Either name or list of names of columns in data_frame, or pandas Series, or array_like objects Values from these columns are extra data, to be used in widgets or Dash callbacks for example. This data is not user-visible but is included in events emitted by the figure (lasso selection etc.)

  • text (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 the figure as text labels.

  • 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.

  • facet_row_spacing (float between 0 and 1) – Spacing between facet rows, in paper units. Default is 0.03 or 0.07 when facet_col_wrap is used.

  • facet_col_spacing (float between 0 and 1) – Spacing between facet columns, in paper units Default is 0.02.

  • error_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 size x-axis error bars. If error_x_minus is None, error bars will be symmetrical, otherwise error_x is used for the positive direction only.

  • error_x_minus (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 size x-axis error bars in the negative direction. Ignored if error_x is None.

  • error_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 size y-axis error bars. If error_y_minus is None, error bars will be symmetrical, otherwise error_y is used for the positive direction only.

  • error_y_minus (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 size y-axis error bars in the negative direction. Ignored if error_y is None.

  • 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.

  • line_dash_sequence (list of str) – Strings should define valid plotly.js dash-patterns. When line_dash is set, values in that column are assigned dash-patterns by cycling through line_dash_sequence in the order described in category_orders, unless the value of line_dash is a key in line_dash_map.

  • line_dash_map (dict with str keys and str values (default {})) – Strings values define plotly.js dash-patterns. Used to override line_dash_sequences to assign a specific dash-patterns to lines corresponding with specific values. Keys in line_dash_map should be values in the column denoted by line_dash. Alternatively, if the values of line_dash are valid line-dash names, the string 'identity' may be passed to cause them to be used directly.

  • symbol_sequence (list of str) – Strings should define valid plotly.js symbols. When symbol is set, values in that column are assigned symbols by cycling through symbol_sequence in the order described in category_orders, unless the value of symbol is a key in symbol_map.

  • symbol_map (dict with str keys and str values (default {})) – String values should define plotly.js symbols Used to override symbol_sequence to assign a specific symbols to marks corresponding with specific values. Keys in symbol_map should be values in the column denoted by symbol. Alternatively, if the values of symbol are valid symbol names, the string 'identity' may be passed to cause them to be used directly.

  • markers (boolean (default False)) – If True, markers are shown on lines.

  • 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.

  • line_shape (str (default 'linear')) – One of 'linear', 'spline', 'hv', 'vh', 'hvh', or 'vhv'

  • render_mode (str) – One of 'auto', 'svg' or 'webgl', default 'auto' Controls the browser API used to draw marks. 'svg' is appropriate for figures of less than 1000 data points, and will allow for fully-vectorized output. 'webgl' is likely necessary for acceptable performance above 1000 points but rasterizes part of the output. 'auto' uses heuristics to choose the mode.

  • 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