Reorganization

Author: jAniceto

data-analysis/data-viz.md

@@ -1,4 +1,4 @@
-# Python Libraries for Data Science
+# Python Libraries for Data Science and Data Viz
 
 ## General use
 - [numpy](https://numpy.org/)
@@ -14,11 +14,17 @@
 - [pydantic](https://pydantic-docs.helpmanual.io/) - data validation and settings management using python type annotations
 
 ## Data visualization
+
+### Plotting libraries
 - [Matplotlib](https://matplotlib.org/): Python de facto 2D plotting library.
 - [seaborn](http://seaborn.pydata.org/): Based on matplotlib, it provides a high-level interface for drawing attractive and informative statistical graphics.
 - [Altair](https://altair-viz.github.io/): A declarative statistical visualization library for Python, based on Vega and Vega-Lite
+
+
+### Web ready
 - [Bokeh ](https://docs.bokeh.org/en/latest/): Creates interactive, web-ready plots, which can be easily output as JSON objects, HTML documents, or interactive web applications.
 - [Plotly](https://plot.ly/python/): Makes interactive plots, but it offers some charts you won't find in most libraries, like contour plots, dendograms, and 3D charts.
+
+### Geo
 - [Folium](https://python-visualization.github.io/folium/): Folium makes it easy to visualize data that’s been manipulated in Python on an interactive [`leaflet.js`](https://leafletjs.com/) map.
 - [Basemap](https://matplotlib.org/basemap/users/index.html): A matplotlib toolkit library for plotting 2D data on maps in Python.
-

data-analysis/basemap.md renamed to python/basemap.md

@@ -1,4 +1,4 @@
-# Graphical user interface in Python
+# Graphical User Interfaces (GUIs) in Python
 
 ### For simple command line programs