data-visualization

I am using a seaborn pairplot to plot a scatter plot of different dimensions of my datapoints. However, I want the markers of the datapoints to have a size that corresponds to one of the dimensions of the datapoints. I have the following code: markersize = 1000* my_dataframe['dim_size'] / sum(my_dataframe['dim_size']) sns.set_context("notebook", font_scale=1.5, rc={'figure.figsize': [11, 8]}) sns.set_style("darkgrid", {"axes.facecolor": ".9"}) kws = dict(s=markersize, linewidth=.5, edgecolor="w") sbax = sns.pairplot(my_dataframe, hue='dim_hue' x_vars=['dim_1', 'dim_2'], y_vars=['dim_3', 'dim_4

I was able to find several packages to create a waterfall chart in R which look like this: But I could not find a way to create a stacked waterfall charts which look like this: A work around is to use stacked bar chart. But that is not an elegant way. So, I wanted to know if there is a better way to create stacked waterfall chart in R. You can easily create the "main" plot with ggplot2 once you have the "right" data. To replicate the plot you want with the choices of color, text, lines, etc., takes more work, but is doable. The trick to plot waterfall charts with ggplot2 is to create a data

I've been able to build a Force Directed Graph using a Force Layout. Most features work great but the one big issue I'm having is that, on starting the layout, it bounces all over the page (in and out of the canvas boundary) before settling to its location on the canvas. I've tried using alpha to control it but it doesn't seem to work: // Create a force layout and bind Nodes and Links var force = d3.layout.force() .charge(-1000) .nodes(nodeSet) .links(linkSet) .size([width/8, height/10]) .linkDistance( function(d) { if (width < height) { return width*1/3; } else { return height*1/3 } } ) //

I've been trying to add legend to my ggplot, but failed miserably. I tried the function scale_colour_manual() , but the legend doesn't show up. ggplot()+ geom_line(data=Summary,aes(y=Y1,x= X),colour="darkblue",size=1 )+ geom_line(data=Summary,aes(y=Y2,x= X),colour="red",size=1 ) My dataframe 'Summary' is as follows: X Y1 Y2 139 1.465477e+16 7.173075e+15 277 1.044803e+16 9.275002e+15 415 1.059258e+16 8.562518e+15 553 1.033283e+16 8.268984e+15 691 9.548019e+15 1.022248e+16 830 1.008212e+16 8.641891e+15 968 9.822061e+15 9.315856e+15 1106 9.948143e+15 9.178694e+15 1244 1.013922e+16 8.825904e+15

The official documentation of bokeh 0.12.1 in the link give the below code for creating a dropdown. http://bokeh.pydata.org/en/latest/docs/user_guide/interaction/widgets.html#userguide-interaction-widgets But its doesn't clearly mention how to capture the value of the dropdown widget when someone click and selects a value from the dropdown. from bokeh.io import output_file, show from bokeh.layouts import widgetbox from bokeh.models.widgets import Dropdown output_file("dropdown.html") menu = [("Item 1", "item_1"), ("Item 2", "item_2"), None, ("Item 3", "item_3")] dropdown = Dropdown(label=

For the sample dataset below, I would like to just plot the y as a smooth line with fill under the line using R. I am able to get smooth line but not the color filled curve. Could someone please help me here? date, y 2015-03-11, 71.12 2015-03-10, 34.0 2015-03-09, 11.1 2015-03-08, 9.62 2015-03-07, 25.97 2015-03-06, 49.7 2015-03-05, 38.05 2015-03-04, 38.05 2015-03-03, 29.75 2015-03-02, 35.85 2015-03-01, 30.65 The code I used to plot the smooth line is as follows. I am unable to get fill the portion under the line with a color y <- df$y x <- 1:length(y) plot(x, y, type='n') smooth = smooth.spline