I am generating histogram graphs and pie charts (using pandas) for a descriptive analysis presentation and the audience would like to click on the graph to go to the data/excel file of the graph.
Is there a way I can automate this 'hyperlink' when generating the figures?
I have looked at (https://docs.eyesopen.com/toolkits/python/depicttk/svg.html) but I am not sure how to implement it with respect to my scenario.
Any guidance would be appreciated
Related
Last days I play around with Highcharts in Python Dash with dash_alternative_viz library.
Link: https://github.com/plotly/dash-alternative-viz
I can create various charts, but I have major problem with creating Bubble chart. I do not know how to input data to this kind of chart. I tried many ways but as a result I get error or empty chart.
Like here below simple bar chart:
Does anybody used this package and somehow generated the Bubble chart, and can share source code so I can see how to deliver input in right format.
Thanks,
Albert
Does anyone know how I can export a plotly sunburst plot as a standalone file which can keep all the functionalities, like annotation while hovering and expansion by click?
Visualizing a hierarchical data with plotly.sunburst in python is a beautiful and beneficial way of presenting it in the best order, while you are able to hover the values to see the annotation, click on each parent section to collapse and expand the child values, etc.. But to present the visualized data (plot) independently without having to open the Python notebook, needs the plot to be saved and exported in a standalone file format that allows keeping every functionality available.
Does anyone know how to do this? and what file format can give this luxury to us?
Thanks
Saving to an HTML file will do the trick:
doc
EDIT: For some reason I've been downvoted twice for posting this question (it hurts ppl) so I've rejigged it.
How do you combine multiple heatmaps in a stacked way with same color scale like to following image?
Additionally, does anyone know how to create the Augmented suffix tree?
Background:
I've worked through the python jupyter notebooks at the following link on how to create the heatmaps of (any) daily consumption profiles using seaborn
http://www.datadrivenbuilding.org/
...however there's a realllllllly cool combination graphic I'd love to be able to reproduce.
That image is an edited version of an image from this paper:
C. Miller, Z. Nagy, A. Schlueter, Automated daily pattern filtering of
measured building performance data, Automation in Construction 49,
Part A (2015) 1–17. doi:10.1016/j.autcon.2014.09.004. URL
http://www.sciencedirect.com/science/article/pii/S0926580514002015
They came up with the visualisation techniques themselves and describe them there. It looks like C. Miller is the one who wrote the notebook that you already found that shows how to draw the stacked heatmaps.
The augmented suffix tree is a type of visualization called a Sankey Diagram. You can plot these very beautifully using Plotly for example, or pySankey if you want to use matplotlib.
I am a graduate student with only limited knowledge of the Python programming language. I am currently working on creating a streaming visualization of EEG data. I am able to generate the individual topographical figures using matplotlib, but cannot find a way of dynamically updating a single plot in the output at specific intervals.
Is there some way of taking a list of Figure objects and dynamically displaying each one in turn after some interval in python 2.7? Perhaps using a Graphics object similar to the ones found in Java's Swing? Or would it be better simply to save my plots as images and use JavaScript to display them as desired?
Thank you in advance for any help or suggestions you may offer.
If you want to make an animation with Python, then there are plenty of ways. For example:
https://jakevdp.github.io/blog/2012/08/18/matplotlib-animation-tutorial/
http://matplotlib.org/examples/animation/double_pendulum_animated.html
http://matplotlib.org/examples/animation/dynamic_image2.html
I'm preparing a set of reports using open source ReportLab. The reports contain a number of charts. Everything works well so far.
I've been asked to take a (working) bar chart that shows two series of data and overlay a fitted curve for each series.
I can see how I could overlay a segmented line on the bar graph by creating both a line chart and bar chart in the same ReportLab drawing. I can't find any reference for fitted curves in ReportLab, however.
Does anyone have any insight into plotting a fitted curve to a series of data in ReportLab or, failing that, a suggestion about how to accomplish this task (I'm thinking that chart would need to be produced in matplotlib instead)?
I would recommend using MatPlotLib. This is exactly the sort of thing it's designed to handle and it will be much easier than trying to piece together something in ReportLab alone, especially since you'll have to do all the calculation of the line on your own and figure out the details of how to draw it in just the right place. MatPlotLib integrates easily with ReportLab; I've used the combination several times with great results.