|
3 | 3 | This is source code that is either used in the presentation, or was developed |
4 | 4 | to create it. There is some material not covered in the presentation as well. |
5 | 5 |
|
6 | | -## Requirements |
7 | | - |
8 | | -* Python version: at least 3.6 |
9 | | -* Packages (names listed that can be used with `pip` or `conda` to install): |
10 | | - * pandas |
11 | | - * xlrd |
12 | | - * seaborn |
13 | | - * holoviews |
14 | | - * sqlalchemy |
15 | | - * matplotlib |
16 | | - * scipy |
17 | | - * geopandas |
18 | | - * shapely |
19 | | - * beautifulsoup4 |
20 | | - * networkx |
21 | | - * jupyter |
22 | | - * folium (with conda, use `-c conda-forge`) |
23 | | - * xarray |
24 | | - * dash |
25 | | - |
26 | 6 | ## What is it? |
27 | 7 | * [`altair`](altair): illustration of an interactive plot using Altair. |
28 | | -* [`dash`](dash): illustration of creating a simple dashboard using dash. |
29 | | -*[`db-access`](db-access): illustration of accessing SQLite databases and using |
30 | | - SQLAlchemy, including object-relational mapping. |
31 | | -*[`gis`](gis): illustrations of working with geospatial data, including geopandas. |
| 8 | +* [`db-access`](db-access): illustration of accessing SQLite databases and |
| 9 | + using SQLAlchemy, including object-relational mapping. |
| 10 | +*[`gis`](gis): illustrations of working with geospatial data, including |
| 11 | + geopandas. |
32 | 12 | * [`holoviews`](holoviews): illustrations of using HoloViews for convenient |
33 | 13 | visualizations. |
34 | 14 | * [`networkx`](networkx): illustration of using the networkx library for graph |
35 | 15 | representation and algorithms. |
36 | 16 | * [`pandas`](pandas): illustrations of using pandas and seaborn. |
37 | | -* [`regexes`](regexes): illustrations of using regular expressions for validation |
38 | | - and information extraction from textual data. |
| 17 | +* [`regexes`](regexes): illustrations of using regular expressions for |
| 18 | + validation and information extraction from textual data. |
39 | 19 | * [`seaborn`](seaborn): illustrations of using Seaborn to create plots. |
40 | | -* [`streamlit`](streamlit): illustration of a simple dashboard created with streamlit. |
41 | | -* [`web-scraping`](web-scraping): illustration of web scraping using beautiful soup |
42 | | - and graph representation using networkx. |
| 20 | +* [`web-scraping`](web-scraping): illustration of web scraping using beautiful |
| 21 | + soup and graph representation using networkx. |
43 | 22 | * [`xarray`](xarray): illustrates the xarray library for pandas-like operations |
44 | 23 | on multi-dimensional arrays. |
| 24 | + |
| 25 | +**Note:** material on dashboards has been moved to a [dedicated |
| 26 | +repository](https://github.com/gjbex/Python-dashboards). |
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