update may 2024

docs/index.md

@@ -1,19 +1,25 @@
+---
+hide:
+  - navigation
+  - toc
+---
+
 # Cheat Sheets for Data Science Learning
 
-This repository serves as a hub for various Cheat Sheets related to 
-the field of Data Science (with Python and R). What sets these Cheat Sheets apart is their 
-multidimensional approach to enhancing the learning experience. 
-Each Cheat Sheet is made available in three distinct formats: 
+This repository is a comprehensive resource for Data Science Cheat Sheets, 
+specifically designed for Python and R. 
+
+These Cheat Sheets offer a multidimensional approach to learning, available in three distinct formats:
 
 * **PDF**: <img src="https://img.shields.io/badge/Open in PDF-%23FF0000.svg?style=flat-square&logo=adobe&logoColor=white"/> 
 * **Streamlit**: <img src="https://static.streamlit.io/badges/streamlit_badge_black_white.svg"/>
 * **Google Colab**: <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
 
-## Content
+## Sections
 
-### Python
+### 📗 Python
 
-::cards:: cols=3
+::cards:: cols=4
 
 - title: Python
   content: "
@@ -37,6 +43,11 @@ Each Cheat Sheet is made available in three distinct formats:
   image: https://upload.wikimedia.org/wikipedia/commons/thumb/2/22/Pandas_mark.svg/1200px-Pandas_mark.svg.png
   url: ./examples/pandas/pandas/
 
+::/cards::
+
+
+::cards:: cols=4
+
 - title: Matplotlib
   content: "
   Matplotlib is a Python library for creating high-quality 2D plots in various formats and interactive platforms.
@@ -60,9 +71,9 @@ Each Cheat Sheet is made available in three distinct formats:
 
 ::/cards::
 
-### R
+### 📘 R
 
-::cards:: cols=3
+::cards:: cols=4
 
 - title: Dplyr
   content: "
@@ -87,9 +98,9 @@ Each Cheat Sheet is made available in three distinct formats:
 
 ::/cards::
 
-> **Note**: The PDF format cheat sheets included here are authored by other contributors and have been used as sources of inspiration for the content presented.
+> 🔑 **Note**: The PDF cheat sheets in this repository are created by various contributors and have inspired the content presented here.
 
-## References
+## 📖 References
 
 * [Data Science Cheat Sheets - DataCamp](https://www.datacamp.com/cheat-sheet)
 * [Cheatsheets and Handouts - Matplotlib](https://matplotlib.org/cheatsheets/)

mkdocs.yml

@@ -44,13 +44,19 @@ theme:
   name: material
   language: en
   logo: images/rpython.svg
-  favicon: images/logo_fam.png
+  favicon: images/icon.png
   features:
-    - navigation.instant
-    - navigation.top
-    - content.code.annotate
-    - search.suggest
-    - search.highlight
+  - search.suggest
+  - search.highlight
+  - content.tabs.link
+  - navigation.indexes
+  - content.tooltips
+  - navigation.path
+  - content.code.annotate
+  - content.code.copy
+  - content.code.select
+  - navigation.tabs
+  - navigation.footer
   palette:
     # Light mode
     - media: '(prefers-color-scheme: light)'
@@ -94,20 +100,18 @@ plugins:
 
 # TOC
 nav:
-    - Home: index.md
-    - Cheat Sheets:
-        - Python:
-            - Python: examples/python/python.ipynb
-            - Numpy: examples/numpy/numpy.ipynb
-            - Pandas: examples/pandas/pandas.ipynb
-            - Matplotlib: examples/matplotlib/matplotlib.ipynb
-            - Scikit-Learn: examples/scikit-learn/sklearn.ipynb
-            - Polars: examples/polars/polars.ipynb
-        - R:
-            - Dplyr: examples/dplyr/dplyr.ipynb
-            - Ggplot2: examples/ggplot2/ggplot2.ipynb
-            - Forcats: examples/forcats/forcats.ipynb
-
+    - 🏠 Home: index.md
+    - 📗 Python:
+        - Python: examples/python/python.ipynb
+        - Numpy: examples/numpy/numpy.ipynb
+        - Pandas: examples/pandas/pandas.ipynb
+        - Matplotlib: examples/matplotlib/matplotlib.ipynb
+        - Scikit-Learn: examples/scikit-learn/sklearn.ipynb
+        - Polars: examples/polars/polars.ipynb
+    - 📘 R:
+        - Dplyr: examples/dplyr/dplyr.ipynb
+        - Ggplot2: examples/ggplot2/ggplot2.ipynb
+        - Forcats: examples/forcats/forcats.ipyn