# Hello Project! https://hackmd.io/@story645/pyd2lt What is open source? Technically this .. image But what we mean is ... image

Hello Project! https://hackmd.io/@story645/pyd2lt What is open source? Technically this .. image But what we mean is ... image

https://nyc2023.pydata.org/cfp/talk/9CGTC7/ In this tutorial we will explore Matplotlib's interactive capabilities by visualizing weather and climate data. We first build static bar charts, timeseries plots, and heatmaps, then show how to make those charts interactive by using an interactive backend. We use these charts to build up to a custom dashboard that links them together, and we finish by showing how to convert some interactions into an animation. In doing so, this tutorial will unpack some of the fundamental concepts that underlie the architecture of Matplotlib, hopefully providing attendees with the foundation for creating effective visualizations using Matplotlib. Matplotlib is a big library, and it can be difficult to know where to start. This tutorial is a guided tour through many of the essential features and concepts of Matplotlib so you can get started making publication-quality, animated, and interactive figures. We will be using weather and climate data as a case study. This schedule/dataset is subject to change, but the rough plan is: setup - 20 minutes

Hi! https://hackmd.io/@story645/rkpjEbxN3 grad student at GC studying viz matplotlib community manager (contributor/maintainer since $\approx$ 2016) on most of the socials: @story645 email: haizenman@gmail.com What do visualization libraries do? Flow chart where boxes are small and arrows are big and purple. Box 1 contains images of data containers: an array, data frame, and nested list. Arrow from 1 to 2. Box 2 has images of visual encodings: a light blue circle, black line, purple to yellow gradient, and blue and orange boxes. Arrow from 2 to 3. Box 3 has graphics: histogram, line plot, image, and 3D surface. Arrow going from 3 to 1.

#Hannah when do readers need to know what? representing data in a visualization have the same structure, two mathmatitical ways to describe it: homomorphism on typology of the data (line, dots,continuous space) & other. the relationship between visualization and data and the mathmamatical structure (eco variants) Alicia midsummers night dream chapter feedback: organization not working About indian boatress in midsummers night dream as describied by titania

What gallery enteries interest you? setup/install What worked, didn't work, was a pain? on Windows and codespaces: errors about ipython kernel and pipRunning cells with '/usr/bin/python' requires the ipykernel package. There is no Pip installer available in the selected environment. Managed to get it to work with Codelab at https://colab.research.google.com/github/story645/pydata_nyc_2023/blob/main/N1_static.ipynb and adding the 'data' folder with penguins.csv For second notebook: https://colab.research.google.com/github/story645/pydata_nyc_2023/blob/main/N2_animated.ipynb For third notebook: https://colab.research.google.com/github/story645/pydata_nyc_2023/blob/main/N3_interactive.ipynb

The following issue is restricted to folks participating in-person at the PyData New York Sprints on Oct 31st. Eventually we plan to open participation to everyone, but are starting with a small group to work out how to scale this in a managable way. Introduction We're improving the user experience of Matplotlib's gallery of examples by implementing tags for better organization and navigability. Over the last few months, we developed tagging guidelines and began to tag some examples. Now we're ready to see what we can do with more brains on the project. Participants Hey folks, thanks for helping us tag our gallery. This sprint has two stages: NO CODE: Tag gallery examples in our tagging spreadsheet LOW CODE (optional): Add tags to gallery examples using the tag directive

haizenman@ccny.cuny.edu github/twitter/most socials: @story645 linked in: https://www.linkedin.com/in/hannah-aizenman/ Education PhD Candidate, Computer Science, GC CUNY, 10/2010-present B.E. Computer Engineering, CCNY, 2005-2010 Research GC CUNY/CCNY, 10/2007-present

Review 1 The Review The paper proposes a model to map from data to visual encoding with very useful properties, such as equivariance that enables converting from the visual encoding back to the data. The main issue I have with the submission is readability, even for a theory paper. Justification The submission proposes a model to map data to visual representation such that visualization libraries can be data-type agnostic and to ensure mapping continuity between data and representation. These are very useful and beneficial properties for a model and can greatly formalize the development of visualization libraries. * break away from data type agnostic, define type + continuity agnostic but not in an auto generation * generalize about continuity rather than data type agnostics

https://hackmd.io/@story645/scipy2021mpl tag: @story645, @matplotlib Thanks CZI EOSS 1 & 3 for supporting Thomas Caswell, Michael Grossberg, and me Thomas Caswell & Michael Grossberg Sam & Melissa YT for making the best presentations to steal ideas from the Matplotlib team :hearts:

We are interested in having a conversation with you about how you think about your data and visualization. Would you be up for at least a quick meeting to learn about your work and to present what we have been working on? intro questions from Dan & Eric understanding MNE's needs How did you go about implementing your visualization API? What design decisions were involved? Was it organic, planned, based on a different API? acretion, started off small, grew as needs grew, CZI tasked w/ unification-unified maybe 10 percent of API interactive continous data browsing windows all work together and share underlying class representation

Write high level version that makes sure they can do everything Also check that they can get the data & it doesn't take forever 1 notebook: 3 Problems: Problem 1 Data Set: Sklearn Breast Cancer

# https://tinyurl.com/qt53dvb * dates * tags * numbers - integers * ID numbers # Quantative ## continous ## discrete # Qualitative ## Catagorical ### nominal ### ordinal # Visualizations: * Heatmap * GIS: Choropleth (polygons) # Dataset https://github.com/story645/dhworkbooks/blob/master/data/titanicfull.csv # Viz notes https://github.com/story645/dhworkbooks/blob/master/itp_viz.ipynb https://www.amazon.com/Street-Journal-Guide-Information-Graphics/dp/0393347281 #GIS https://kepl