#Label points scatter plot matplotlib pdf#

Legend ( bool) – Whether or not to show the legend in the resulting figure. Size ( int) – Size of markers in screen space units. When multiple labels are given, a dropdown will be displayed with the different options.Ĭan be used with categorical or continuous expressions. Used to color each point w.r.t its label. Label ( Expression or Dict]) – Either a single expression (if a single label is desired), or aĭictionary of label name -> label value for x and y values. Y ( NumericExpression or (str, NumericExpression)) – List of y-values to be plotted. X ( NumericExpression or (str, NumericExpression)) – List of x-values to be plotted. Hovering on points will display their coordinates, labels and any additional fields specified in hover_fields. Note that using many different labelling schemes in the same plots, particularly if those labels contain manyĭifferent classes could slow down the plot interactions.

To specify your colorįor CategoricalMapper for categorical labels, and for LinearColorMapper and LogColorMapperįor categorical labels, clicking on one of the items in the legend will hide/show all points with the corresponding label. The corresponding entry of colors if provided (otherwise a default scheme is used). Points will be colored by one of the labels defined in the label using the color scheme defined in a containing the interactive scatter plot a .Select dropdown selection widget for labels If no label or a single label is provided, then returns If passed as a tuple the first element is used as the hover label. a tuple (str, NumericExpression) from the same Table. a NumericExpression from the same Table. scatter ( x, y, label = None, title = None, xlabel = None, ylabel = None, size = 4, legend = True, hover_fields = None, colors = None, width = 800, height = 800, collect_all = False, n_divisions = 500, missing_label = 'NA' ) ¶

Height ( int) – Plot height (default 600px).Ĭolors ( List) – List of colors (hex codes, or strings as describedī ot. Width ( int) – Plot width (default 600px). The range will be computed from the data. If this value is None, or either of the inner lists is None, All values outside of this range will be considered outliersĪnd not tallied in the histogram. Range ( None or ((float, float), (float, float))) – The leftmost and rightmost edges of the bins along each dimension: If, the number of bins in each dimension (nx, ny = bins). If int, the number of bins for the two dimensions (nx = ny = bins). Y ( NumericExpression) – Expression for y-axis (from the same Hail table as x).īins ( int or ) – The bin specification: X ( NumericExpression) – Expression for x-axis (from a Hail table). y, bins = 10, range = (( 0, 1 ), None )) Parameters If x_range or y_range are not provided, the function will do a pass through the data to determine X and y must both be a NumericExpression from the same Table. histogram2d ( x, y, bins = 40, range = None, title = None, width = 600, height = 600, colors =, log = False ) ¶ cumulative_histogram ( data, range = None, bins = 50, legend = None, title = None, normalize = True, log = False ) ¶Ĭreate a cumulative histogram. Range ( Tuple) – Range of x values in the histogram.īins ( int) – Number of bins in the histogram.ī ot. histogram ( data, range = None, bins = 50, legend = None, title = None, log = False, interactive = False ) ¶ĭata can be a Float64Expression, or the result of the hist() Interactive ( bool) – If True, return a handle to pass to bokeh.io.show().įigure ( ) – If not None, add density plot to figure. Log ( bool) – Plot the log10 of the bin counts. Smoothing ( float) – Degree of smoothing. smoothed_pdf ( data, k = 350, smoothing = 0.5, legend = None, title = None, log = False, interactive = False, figure = None ) ¶

#Label points scatter plot matplotlib pdf#

pdf ( data, k = 1000, confidence = 5, legend = None, title = None, log = False, interactive = False ) ¶ ot. Log ( bool) – Whether or not the y-axis should be of type log.ī ot. Normalize ( bool) – Whether or not the cumulative data should be normalized. Legend ( str) – Label of data on the x-axis.

K ( int) – Accuracy parameter (passed to approx_cdf()). Parametersĭata ( Struct or Float64Expression) – Sequence of data to plot. cdf ( data, k = 350, legend = None, title = None, normalize = True, log = False ) ¶Ĭreate a cumulative density plot. Configure the Bokeh output state to generate output in notebook cells when bokeh.io.show() is called.