Plots Not Working
Posted By admin On 28/03/22Manipulate Plot Sliders Not Working duplicate Ask Question Asked 4 years, 6 months ago. Active 4 years, 6 months ago. Viewed 1k times 2 $begingroup$ This question already has answers here: How are parameters evaluated for a Plot in Manipulate (6 answers) Closed 4 years ago. Activate this venv in the terminal and try to plot something. In my case there's no issues - I get a GUI pop up with a plot. Then try adding this new venv as new interpreter in PyCharm, and try to plot something. Don't forget to disable 'Show plots in tool window' in SciView settings. Plot does not work. Hello everyone The following two commands plot.default(seq(1,5),seq(2,6)) plot(seq(1,5),seq(2,6)) plot nothing. One day ago this would create a simple plot diagram but.
Note
Smart narrative visuals can be created and viewed in both Power BI Desktop and the Power BI service. The steps and illustrations in this article are from Power BI Desktop.
A scatter chart always has two value axes to show: one set of numerical data along a horizontal axis and another set of numerical values along a vertical axis. The chart displays points at the intersection of an x and y numerical value, combining these values into single data points. Power BI may distribute these data points evenly or unevenly across the horizontal axis. It depends on the data the chart represents.
You can set the number of data points, up to a maximum of 10,000.
When to use a scatter chart, bubble chart, or a dot plot chart
Scatter and bubble charts
A scatter chart shows the relationship between two numerical values. A bubble chart replaces data points with bubbles, with the bubble size representing an additional third data dimension.
Scatter charts are a great choice:
To show relationships between two numerical values.
To plot two groups of numbers as one series of x and y coordinates.
To use instead of a line chart when you want to change the scale of the horizontal axis.
To turn the horizontal axis into a logarithmic scale.
To display worksheet data that includes pairs or grouped sets of values.
Tip
In a scatter chart, you can adjust the independent scales of the axes to reveal more information about the grouped values.
To show patterns in large sets of data, for example by showing linear or non-linear trends, clusters, and outliers.
To compare large numbers of data points without regard to time. The more data that you include in a sScatter chart, the better the comparisons that you can make.
In addition to what Scatter charts can do for you, bubble charts are a great choice:
If your data has three data series that each contains a set of values.
To present financial data. Different bubble sizes are useful to visually emphasize specific values.
To use with quadrants.
Dot plot charts
A dot plot chart is similar to a bubble chart and scatter chart, but is instead used to plot categorical data along the X-Axis.
They're a great choice if you want to include categorical data along the X-Axis.
Prerequisites
This tutorial uses the Retail Analysis sample PBIX file.
From the upper left section of the menubar, select File > Open
Find your copy of the Retail Analysis sample PBIX file
Open the Retail Analysis sample PBIX file in report view .
Select to add a new page.
Note
Sharing your report with a Power BI colleague requires that you both have individual Power BI Pro licenses or that the report is saved in Premium capacity.
Create a scatter chart
Start on a blank report page and from the Fields pane, select these fields:
Sales > Sales Per Sq Ft
Sales > Total Sales Variance %
District > District
In the Visualization pane, select to convert the cluster column chart to a scatter chart.
Drag District from Details to Legend.
Power BI displays a scatter chart that plots Total Sales Variance % along the Y-Axis, and plots Sales Per Square Feet along the X-Axis. The data point colors represent districts:
Now let's add a third dimension.
Create a bubble chart
From the Fields pane, drag Sales > This Year Sales > Value to the Size well. The data points expand to volumes proportionate with the sales value.
Hover over a bubble. The size of the bubble reflects the value of This Year Sales.
To set the number of data points to show in your bubble chart, in the Format section of the Visualizations pane, expand General, and adjust the Data Volume.
You can set the max data volume to any number up to 10,000. As you get into the higher numbers, we suggest testing first to ensure good performance.
Note
More data points can mean a longer loading time. If you do choose to publish reports with limits at the higher end of the scale, make sure to test out your reports across the web and mobile as well. You want to confirm that the performance of the chart matches your users' expectations.
Continue formatting the visualization colors, labels, titles, background, and more. To improve accessibility, consider adding marker shapes to each line. To select the marker shape, expand Shapes, select Marker shape, and select a shape.
Change the marker shape to a diamond, triangle, or square. Using a different marker shape for each line makes it easier for report consumers to differentiate lines (or areas) from each other.
Open the Analytics pane to add additional information to your visualization.
Add a Median line. Select Median line > Add. By default, Power BI adds a median line for Sales per sq ft. This isn't very helpful since we can see that there are 10 data points and know that the median will be created with five data points on each side. Instead, switch the Measure to Total sales variance %.
Add symmetry shading to show which points have a higher value of the x-axis measure compared to the y-axis measure, and vice-versa. When you turn symmetry shading on in the Analytics pane, Power BI shows you the background of your scatter chart symmetrically based on your current axis upper and lower boundaries. This is a very quick way to identify which axis measure a data point favors, especially when you have a different axis range for your x- and y-axis.
a. Change the Total sales variance % field to Gross margin last year %
b. From the Analytics pane, add Symmetry shading. We can see from the shading that Hosiery (the green bubble in the pink shaded area) is the only category that favors gross margin rather than its sales per store square footage.
Continue exploring the Analytics pane to discover interesting insights in your data.
Create a dot plot chart
To create a dot plot chart, replace the numerical X-Axis field with a categorical field.
From the X-Axis pane, remove Sales per sq ft and replace it with District > District Manager.
Considerations and troubleshooting
Your scatter chart has only one data point
Does your scatter chart have only one data point that aggregates all the values on the X- and Y-axes? Or maybe it aggregates all the values along a single horizontal or vertical line?
Add a field to the Details well to tell Power BI how to group the values. The field must be unique for each point you want to plot. A simple row number or ID field will do.
If you don't have that in your data, create a field that concatenates your X and Y values together into something unique per point:
To create a new field, use the Power BI Desktop Query Editor to add an Index Column to your dataset. Then add this column to your visualization's Details well.
Next steps
You might also be interested in the following articles:
More questions? Try the Power BI Community
Arrange multiple plots into a grid
Arrange multiple plots into a grid.
Usage
Arguments
List of plots to be arranged into the grid. The plots can be any objects thatthe function as_gtable() can handle (see also examples).
(optional) List of plots to display. Alternatively, the plots can be providedindividually as the first n arguments of the function plot_grid (see examples).
(optional) Specifies whether graphs in the grid should be horizontally ('h') orvertically ('v') aligned. Options are 'none' (default), 'hv' (align in both directions), 'h', and 'v'.
(optional) Specifies whether graphs should be aligned by the left ('l'), right ('r'), top ('t'), or bottom ('b')margins. Options are 'none' (default), or a string of any combination of l, r, t, and b in any order (e.g. 'tblr' or 'rlbt' for aligning all margins).Must be specified if any of the graphs are complex (e.g. faceted) and alignment is specified and desired. See align_plots() for details.
(optional) Number of rows in the plot grid.
(optional) Number of columns in the plot grid.
(optional) Numerical vector of relative columns widths. For example, in a two-columngrid, rel_widths = c(2, 1) would make the first column twice as wide as thesecond column.
(optional) Numerical vector of relative rows heights. Works just asrel_widths does, but for rows rather than columns.
(optional) List of labels to be added to the plots. You can also set labels='AUTO' toauto-generate upper-case labels or labels='auto' to auto-generate lower-case labels.
(optional) Numerical value indicating the label size. Default is 14.
(optional) Font family of the plot labels. If not provided, is taken from the current theme.
(optional) Font face of the plot labels. Default is 'bold'.
Plots Not Working In Rstudio
(optional) Color of the plot labels. If not provided, is taken from the current theme.
(optional) Single value or vector of x positions for plot labels, relative to each subplot.Defaults to 0 for all labels. (Each label is placed all the way to the left of each plot.)
(optional) Single value or vector of y positions for plot labels, relative to each subplot.Defaults to 1 for all labels. (Each label is placed all the way to the top of each plot.)
Adjusts the horizontal position of each label. More negative values move the label furtherto the right on the plot canvas. Can be a single value (applied to all labels) or a vector of values(one for each label). Default is -0.5.
Adjusts the vertical position of each label. More positive values move the label furtherdown on the plot canvas. Can be a single value (applied to all labels) or a vector of values(one for each label). Default is 1.5.
Individual number or vector of numbers greater than 0. Enables you to scale the size of all orselect plots. Usually it's preferable to set margins instead of using scale, but scale cansometimes be more powerful.
(optional) How should margins be adjusted during alignment. See align_plots() for details.
Logical value indicating if the plots should be arrange by row (default) or by column.
Plot Not Working
Deprecated. Use ncol.
Deprecated. Use nrow.
Aliases
- plot_grid