#| Source code

This is source code that is either used in the presentation, or was developed to create it. There is some material not covered in the presentation as well.

• Python version: at least 3.6
• Packages (names listed that can be used with pip or conda to install):
  • pandas
  • xlrd
  • seaborn
  • holoviews
  • sqlalchemy
  • matplotlib
  • scipy
  • geopandas
  • shapely
  • beautifulsoup4
  • networkx
  • jupyter
  • folium (with conda, use -c conda-forge)
  • xarray
  • dash

• altair: illustration of an interactive plot using Altair.
• dash: illustration of creating a simple dashboard using dash.
• db-access: illustration of accessing SQLite databases and using SQLAlchemy, including object-relational mapping.
• gis: illustrations of working with geospatial data, including geopandas.
• holoviews: illustrations of using HoloViews for convenient visualizations.
• networkx: illustration of using the networkx library for graph representation and algorithms.
• pandas: illustrations of using pandas and seaborn.
• regexes: illustrations of using regular expressions for validation and information extraction from textual data.
• seaborn: illustrations of using Seaborn to create plots.
• streamlit: illustration of a simple dashboard created with streamlit.
• web-scraping: illustration of web scraping using beautiful soup and graph representation using networkx.
• xarray: illustrates the xarray library for pandas-like operations on multi-dimensional arrays.