stat157 / visualizers Goto Github PK

Video Production Info: Fri Dec 6; 5-6pm at 326 Soda Hall

Shoot Danielle an email if you're interested! This can count towards your grade + final presentation.

"This is what we will need:
-Thoughts towards how to communicate the process of this course via storyboard
-Students taking on script-writing
-Volunteers for actors or interviewers

Storyboard details:
For now, I envision starting with the problem then discussing the process of solving it---i.e. walk through of Github and maybe a behind the scenes of the collaborative process. & Finishing up with why it's important. "

If you can't make it and wanna contribute ideas, just post a comment! Thanks!

Also I added a couple events (including this one + the data science fair) to the Visualizer Facebook group. Feel free to add yourself to the groups and events if you need extra reminders:
https://www.facebook.com/groups/187543704763841/events/

• Christina Ho

hey visualizers!
I think Fernando Pérez briefly displayed Seaborn in his talk on Tuesday, and Edward Tufte just tweeted about it. check it out! it's a library for visualization that uses a lot of the same dependencies we've already been using for plotting in python

http://stanford.edu/~mwaskom/software/seaborn/index.html

http://vimeo.com/35005701

• know the kind of data format for inputs
• understanding the models
• making graphs dynamic
• figuring out what type of graph would be best (easier to understand, representative of the data)
• facilitate comparisons between models
• communicate with curators and analyzers; know what data to expect
• decide how we want the data formatted and negotiate with DC and analyzers

Note: we agreed to look over the Stark's lecture slides to gain a more complete understanding of the types of visuals that would be meaningful from the analysis and to know the variables we need in our input

In my reading I came upon Ggobi, similar to Khoa finding ggplot in Python in issue #8. The tool might be helpful in visualizing earthquake clustering.

GGobi is an open source visualization program for exploring high-dimensional data. In R, you can download the package rggobi. They also have a GitHub repository.

Here's an introduction to rggobi.

In case of using D3 for visualization, this may be useful for visualizers. Try to check for those basic resources.

Homepage for D3.js: http://d3js.org/
D3 Tutorials by Scott Murray: http://alignedleft.com/tutorials/d3
Here is great steps for installing and other general resources: https://github.com/mbostock/d3/wiki
also, you can check the examples of awesome visual graphs : https://github.com/mbostock/d3/wiki/Gallery

Please follow the link below to our repository to view our SMART Goals and work progress on Task 8:

https://github.com/annyeongjs/visualheart.task8

Hey visualizers,

I came across an article a few minutes ago and thought it would be interesting to you guys, especially those who used ggplot2 in R before. There's a brand new package called ggplot for Python that looks very similar to the one in R. You can install it with sudo pip install ggplot and read more about it here.

Here's its Github repo in case you want to raise an issue to the owner of the package.

I tested it out, and it seems like you will have to use it inline by starting with ipython notebook --no-browser --ip=0.0.0.0 --pylab=inline or put the magic function %matplotlib inline at the top of your code to use ggplot with the notebook.

That is all! 👻

Please follow the link below to our repository to view our SMART Goals and work progress on Task 2:

https://github.com/joyyqchen/EarthquakeProject.Team-Chen.Kirschner.Liou.Tsai

https://docs.google.com/document/d/1D5lje1HDzWCsrOsO7tsfdOSBbO8K9KFnfFaH5HTMMh8/edit#

Are any of you guys getting this error when trying to run some of the matplotlib examples?

When I run this code:

from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
import numpy as np
# set up orthographic map projection with
# perspective of satellite looking down at 50N, 100W.
# use low resolution coastlines.
map = Basemap(projection='ortho',lat_0=45,lon_0=-100,resolution='l')
# draw coastlines, country boundaries, fill continents.
map.drawcoastlines(linewidth=0.25)
map.drawcountries(linewidth=0.25)
map.fillcontinents(color='coral',lake_color='aqua')
# draw the edge of the map projection region (the projection limb)
map.drawmapboundary(fill_color='aqua')
# draw lat/lon grid lines every 30 degrees.
map.drawmeridians(np.arange(0,360,30))
map.drawparallels(np.arange(-90,90,30))
# make up some data on a regular lat/lon grid.
nlats = 73; nlons = 145; delta = 2.*np.pi/(nlons-1)
lats = (0.5*np.pi-delta*np.indices((nlats,nlons))[0,:,:])
lons = (delta*np.indices((nlats,nlons))[1,:,:])
wave = 0.75*(np.sin(2.*lats)**8*np.cos(4.*lons))
mean = 0.5*np.cos(2.*lats)*((np.sin(2.*lats))**2 + 2.)
# compute native map projection coordinates of lat/lon grid.
x, y = map(lons*180./np.pi, lats*180./np.pi)
# contour data over the map.
cs = map.contour(x,y,wave+mean,15,linewidths=1.5)
plt.title('contour lines over filled continent background')
plt.show()

I get this error: TclError: no display name and no $DISPLAY environment variable

I tried fixing the error from using the tips from this answer on Stack Overflow (http://stackoverflow.com/questions/2801882/generating-a-png-with-matplotlib-when-display-is-undefined), but I am still getting the same error:

Adding these lines of code don't help:

import matplotlib
matplotlib.use('Agg')