![\"Data](\"https://raw.githubusercontent.com/DataForScience/Networks/master/data/D4Sci_logo_ball.png\"){kind=logo}
Interactive Visualization
\n", 10 | "Jupyter ipywidgets
\n", 11 | "Bruno Gonçalves
\n",
12 | " www.data4sci.com
\n",
13 | " @bgoncalves, @data4sci
Bruno Gonçalves
\n",
12 | " www.data4sci.com
\n",
13 | " @bgoncalves, @data4sci
![\"Data](\"data/D4Sci_logo_full.png\"){kind=logo}
\n",
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/LICENSE:
--------------------------------------------------------------------------------
1 | MIT License
2 |
3 | Copyright (c) 2020 Data For Science
4 |
5 | Permission is hereby granted, free of charge, to any person obtaining a copy
6 | of this software and associated documentation files (the "Software"), to deal
7 | in the Software without restriction, including without limitation the rights
8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
9 | copies of the Software, and to permit persons to whom the Software is
10 | furnished to do so, subject to the following conditions:
11 |
12 | The above copyright notice and this permission notice shall be included in all
13 | copies or substantial portions of the Software.
14 |
15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
21 | SOFTWARE.
22 |
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/README.md:
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1 | 
2 | [](https://twitter.com/intent/follow?screen_name=data4sci)
3 | 
4 | 
5 | 
6 |
7 | [](https://data4sci.substack.com/)
8 | [](https://data4sci.com/newsletter)
9 |
10 | [](https://mybinder.org/v2/gh/DataForScience/InteractiveViz/master)
11 |
12 | # Interactive Visualization With Python
13 | ### Code and slides to accompany the online series of webinars: https://data4sci.com/interactive-data-visualization by Data For Science.
14 |
15 | ### Run the code in Binder: [](https://mybinder.org/v2/gh/DataForScience/InteractiveViz/master)
16 |
17 | Our brains are highly developed visual processing machines. We’ve evolved highly sophisticated visual systems to quickly process large quantities of information. The power of visualization rests on its ability to encode data in a way that can be processed intuitively and accurately.
18 |
19 | As the quantity and complexity of data increases, the correct use of visualization will only become more important. In this course, we survey a range of techniques and tools to produce visually appealing and effective interactive visualizations using Jupyter notebooks, Bokeh and Plotly to make your data shine.
20 |
21 | ## Schedule
22 | ### 1. Data Cleaning and Visualization with Pandas
23 | - Data Frames and Series
24 | - GroupBy
25 | - Pivot Tables
26 | - The plot() function
27 | - Customizing pandas plots with matplotlib
28 | - Interactive Pandas plots
29 | Break (10 min)
30 | Q&A (5 min)
31 |
32 |
33 | ### 2. matplotlib animations
34 | - The Matplotlib animation API
35 | - FuncAnimation
36 | - Animation writers
37 |
38 | ### 3. Jupyter ipywidgets
39 | - Ipywidgets as interactive browser controls
40 | - Simple Widget use
41 | - Widget customizing
42 | - Layout
43 | Break (10 min)
44 | Q&A (5 min)
45 |
46 | ### 4. Bokeh
47 | - Basic Plotting
48 | - Styling and Annotations
49 | - Networks
50 | - Geographic Plots
51 |
52 | ### 5. Plotly
53 | - Basic Plotly
54 | - Importing Data
55 | - 3D plotting
56 | - Animated Plots
57 | - Course wrap-up, Q&A, and Next Steps (15 min)
58 |
59 | Slides: https://data4sci.com/landing/interactiveviz
60 |
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/d4sci.mplstyle:
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1 | # Data For Science style
2 | # Author: Bruno Goncalves