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Overview

Since version 0.2.3, pyspread can generate matplotlib charts. Each cell which yields a matplotlib figure displays the figure as a bitmap and is stretched to the cell’s extents.

The Macros -> Insert chart... option provides an easy way of generating matplotlib figures. They generate code of a special class charts.ChartFigure that is provided. This class subclasses the matplotlib Figure class. The subclass takes matplotlib arguments and creates a figure in one step. The dialog creates the code for doing that. It also parses any code starting with charts.ChartFigure and figures out, which choice had been made last time. This may very well fail if you changed the cell code manually. For further reference, the matplotlib web site is recommended.

Note: Cells display all types of matplotlib figures. The chart dialog just provides a convenient user to create and edit common chart types.

Since version 0.4, six chart types are supported by the chart dialog: Plots, i.e. line charts, bar charts, histograms, box plots, pie charts and annotations. Note that pie charts cannot be combined with other chart type yet. Please suggest other chart types that you find usable by posting at the issue tracker.

The chart dialog is designed as a fast to use graphical front-end for common matplotlib properties. Attributes correspond to matplotlib function properties. Each property is described in tooltips. The chart dialog consists of three parts (from left to right):

Axes Panel

The Axes panel allows changing X and Y axes attributes. Other axes types such as Z axis in 3D charts are not supported by the chart dialog. The axes panel is structured into three sections: Axes, X-Axis and Y-Axis.

In the first box, overall figure attributes can be set, which is title text, the title text font and color and id a legend is drawn. The text entry field for the title text accepts Python expressions, i.e. if you want a specific string to be displayed as the title, you have to quote the text. However, if you want a certain global variable of cell content to be displayed then you can enter the object name. Functions and operators are also allowed as long as they return a string or unicode like object. Note that this applies for all fields of the chart dialog unless otherwise specified.

In the second box, X-axis attributes are specified. The X-axis label is provided again as a Python expression. Font and color can be specified. Next, X-axis scaling can be set to linear (no check) or logarithmic (check), and the X-axis grid can be turned on and off. If the X-axis shall display a date instead of values and if a datetime.date object is provided as input for the x-axis values then the date format field should be filled with a strftime format string. Details about the format string are given in the tooltip. The ticks field accepts a list or a tuple of numbers or floats. At these locations, axis ticks are set when specified. If left empty, axis ticks are set automatically. The label field lets the user specify arbitrary text as label at a tick. Font and color of the labels can be specified here. The secondary ticks option allows ticks to be displayed on the opposide side of the chart, i.e. on the top as at the bottom. The outside, inside, both choice specifies, where the ticks are situated at the axis. Padding allows setting the distance between label text and axis. Size lets the user specify text size if no explicit labels are given in the labels field.

In the third box, Y-axis attributes are specified. Attributes match those of the X-axis both in content and format with the exception of the date format field, which is not available for the Y-axis.

Series Panel

The Series panel allows adding one or more series to the axes. In order to add a new series, click on the + tab at the bottom of the panel. A series is deleted with the x right of the tabs. You can switch between series by clicking on the respective tabs.

Each data series can be of a specific type that is chosen from the list that is on the left side of the Series panel. In version 1.0.3 there are eight series types: plot, bar, hist, boxplot, pie, annotate, contour and Sankey. Note that the series type names correspond to the respective matplotlib names. Other types of matplotlib series are not supported in the chart dialog. If such a need arises please post an e-mail to the issue tracker.

Colors

Colors below are expressed with the following:

Plot chart

When the plot chart type is selected then on the right panel, Data, Line and Marker boxes are displayed.

In the Data box, a data label can be specified that appears in the legend if it is activated. The X field is optional. It has to be an iterable of the same length of Y and allows specifying the X values of each data point. In the Y field, Y values of each point are specified in an iterable.

In the Line box, the line style chosen from solid, dashed, dash-dotted and frozen. Its width can be specified in points (integer values only) as well as its color.

In the Marker box, the marker style for the actual data points may be chosen from a range of 22 styles. The marker size can be specified (integer values only) as well as its face and egde colors. The marker alpha value is set with a floating point value, where 1.0 is solid and 0.0 is fully transparent.

Bar chart

When the bar chart type is selected then on the right panel, Data and Bar boxes are displayed.

In the Data box, a data label can be specified that appears in the legend if it is activated. The left positions field is mandatory. It expects an iterable of left bar values that is as long as the bar heights iterable that defines the upper limits of the bars (not the bar lengths). The bar widths field expects either a number that applies to all bars or an iterable so that specific bars may have different widths. The bar bottoms field is optional and defines the lower limit of the bars. Similarly to the widths field, it allows entering a number or an iterable.

In the Bar box, the bar fill and edge color can be chosen. Furthermore, an alpha value can be specified with a floating point value, where 1.0 is solid and 0.0 is fully transparent.

Note that while bar charts may be morte difficult to use than plot charts, they can be used in order to plot arbitrary rectangles, which makes them also applicable for example to plot simple top down views on room layouts.

Histogram

When the histogram chart type is selected then on the right panel, Data and Histogram boxes are displayed.

In the Data box, a data label can be specified that appears in the legend if it is activated. The data series that has to be provided is an iterable of numerical values. Categorical values are not supported here because this is not supported by matplotlib. Value tuples are also not supported.

In the Histogram box, the number of bin can be specified as an integer value. If Normed is checked then the integral of the histogram will sum to:

If stacked is also True, the sum of the histograms is normalized to 1. If culumative is checked then then a histogram is computed where each bin gives the counts in that bin plus all bins for smaller values. The last bin gives the total number of datapoints. Furthermore, the histogram bar color can be set. The alpha value can be specified with a floating point value, where 1.0 is solid and 0.0 is fully transparent.

Box Plot

When the boxplot chart type is selected then on the right panel, Data and Box plot boxes are displayed.

In the Data box, a sequence of numerical values or a sequence of sequences can be provided. In the latter case, multiple boxplots are combined in one diagram.

In the Box plot box, the box width can be specified as a floatig point value. If vertical is checked then the boxplots are frawn vertical else horizontal. Flier symbols may be chosen from 22 choices. If notch is checked then the main box shows a notch at the median value.

Pie Chart

When the pie chart type is selected then on the right panel, Data and Pie boxes are displayed.

In the Data box, a sequence of numerical values can be provided.

In the Pie box, labels for the wedges can be specified as a sequence of objects (e.g. strings). Wedge colors are provided in the Colors text box as sequence of strings, where colors can be the strings

The pie chart can be rotated with the angle value, which may be a positive or negative integer. The checkbox shadow enables or disables a shadow behind the pie chart.

Chart Annotation

When the annotation chart type is selected then on the right panel, an Annotation box is displayed. There, a text can be entered as a string along with a 2-tuple of coordinates. In a choice box, information, what these coordinates refer to, is given. Annotations mostly make sense as an additional figure layer.

Contour Chart

When the contour chart type is selected then on the right panel, Data and Lines, Areas and Labels boxes are displayed.

In the Data box, x and y values form a mesh for which z values are specified. Note that z must be a one-time nested list. For optimizing performance, the numpy helper functions meshgrid may be used as z may also be a 2D numpy array.

In the Lines box, the style, width, color and alpha value of the contour separating line may be specified. The line wdth must be an Integer value. The colors are provided in the Colors text box as sequence of strings, see colors.

Note that the colors are also used for the filling of the contour. Therefore, two overlaying contour plots may be combined in order to get e.g. black contour lines for a coloured contour.

In the Areas box, filling of the contour can be turned on and off and hatch types can be specified that is overlaid with the filling. The hatch types can be given in a sequence of hatch strings. A hatch string can be one of:

Letters can be combined, in which case all the specified hatchings are done. If same letter repeats, it increases the density of hatching of that pattern. Note that when the color is white then the mesh type is displayed as black on white.

In the Labels box, contour labels can be turned on and off, and the font size can be spezified as an Integer.

Sankey Diagram

When the Sankey chart type is selected then on the right panel, Data and Diagram and Area boxes are displayed.

In the Data box, flows and orientations can be specified as sequences of numbers. Flows have positive numbers for inputs and negative numbers for outputs. The absolute value of the number specifies the arrow width. Orientations may have the values are

If orientations == 0, inputs will break in from the left and outputs will break away to the right. Labels may be specified as a sequence of strings - either one string for all arrows or one per arrow. Each label is followed by the value and the unit. Values are formatted using a Python formatting string

In the Diagram box, rotatation, gap, radius, shoulder, offset and angle can be specified, which control the layout of the Sankey diagram.

In the Area box, the color of the diagram edge and the diagram filling can be set.

The figure panel is automatically updated whenever content of the chart dialog is changed. Should it show no chart then something is wrong with the input so that later in the grid, no chart is shown as well.

© Martin Manns and the pyspread team