Merge pull request #17 from ScaDS/dataviz-final-touches

Dataviz final touches
ScaDS · May 7, 2024 · 1ea60f0 · 1ea60f0
2 parents 281ba09 + f5c3f87
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diff --git a/_toc.yml b/_toc.yml
@@ -89,11 +89,11 @@ parts:
     - file: day3.3b_advanced_plotting/readme.md 
       sections: 
       - file: day3.3b_advanced_plotting/00_getdata.ipynb 
-      - file: day3.3b_advanced_plotting/01_seabornobj_open.ipynb 
+#     - file: day3.3b_advanced_plotting/01_seabornobj_open.ipynb 
       - file: day3.3b_advanced_plotting/01_seabornobj_solution.ipynb 
-      - file: day3.3b_advanced_plotting/02_dataviz_MLunsupervised_open.ipynb 
+#     - file: day3.3b_advanced_plotting/02_dataviz_MLunsupervised_open.ipynb 
       - file: day3.3b_advanced_plotting/02_dataviz_MLunsupervised_solution.ipynb 
-      - file: day3.3b_advanced_plotting/03_dataviz_MLsupervised_open.ipynb 
+#     - file: day3.3b_advanced_plotting/03_dataviz_MLsupervised_open.ipynb 
       - file: day3.3b_advanced_plotting/03_dataviz_MLsupervised_solution.ipynb 
 
 
@@ -110,4 +110,4 @@ parts:
     - file: CONDUCT
     - file: CONTRIBUTING
     - file: LICENSE
-    - file: imprint
+    - file: imprint
diff --git a/day3.2_data_visualization/DataViz_theory_BIDS2024_public.pdf b/day3.2_data_visualization/DataViz_theory_BIDS2024_public.pdf
diff --git a/day3.2_data_visualization/readme.md b/day3.2_data_visualization/readme.md
@@ -1,3 +1,6 @@
 # Data Visualization
 
 In this session we will dive into the concepts of data visualization. We will learn how to produce data visualizations optimal for human perception.
+In addition, we will give practical advice with dos and don'ts in data visualization and will have some fun with bad examples. 
+
+You can download the slides [here](https://github.com/ScaDS/BIDS-training-2024/blob/dataviz-final-touches/day3.2_data_visualization/DataViz_theory_BIDS2024_public.pdf) 
diff --git a/day3.3a_basic_plotting/readme.md b/day3.3a_basic_plotting/readme.md
@@ -1,4 +1,4 @@
-# Plotting
+# Plotting Basics
 
 Note that the plotting training is divided into two distinct sessions.
 
@@ -12,4 +12,4 @@ Parallel session (Day 3.3b - Advanced Plotting):
 
 - _Focus_: This session explores the use of Seaborn's grammar of graphics objects. This involves a more detailed manipulation of plot elements and integration with Matplotlib for enhanced customization.
 - _Content_: We will dive into how to structure plots using the grammar of graphics philosophy, which provides a powerful framework for understanding and creating complex visualizations. This includes modifying aesthetic attributes and integrating multiple plots.
-- _Audience_: This session is aimed at participants who feel more comfortable with coding and are ready to explore more advanced data visualization techniques. It is best for those looking to gain deeper insights into the graphical representation of data and how to manipulate these visualizations programmatically.
+- _Audience_: This session is aimed at participants who feel more comfortable with coding and are ready to explore more advanced data visualization techniques. It is best for those looking to gain deeper insights into the graphical representation of data and how to manipulate these visualizations programmatically.
diff --git a/day3.3b_advanced_plotting/00_getdata.ipynb b/day3.3b_advanced_plotting/00_getdata.ipynb
@@ -4,8 +4,14 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Part 0: Get data set for plotting ###\n",
-    "using meteostat API (https://dev.meteostat.net/python/) and list of capital cities around the globe (capitals_id.txt)"
+    "# Part 0: Get data set for plotting ###\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "using meteostat API (https://dev.meteostat.net/python/) and list of capital cities around the globe (capitals_id.txt) "
    ]
   },
   {

diff --git a/day3.3b_advanced_plotting/01_seabornobj_open.ipynb b/day3.3b_advanced_plotting/01_seabornobj_open.ipynb
@@ -1,5 +1,12 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Part 1: Time series and other simple plots"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -18,13 +25,6 @@
     "import plotly.express as px"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Part 1: Time series and other simple plots"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,

diff --git a/day3.3b_advanced_plotting/01_seabornobj_solution.ipynb b/day3.3b_advanced_plotting/01_seabornobj_solution.ipynb
@@ -1,5 +1,12 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Part 1: Time series and other simple plots"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -18,13 +25,6 @@
     "import plotly.express as px"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Part 1: Time series and other simple plots"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 2,

diff --git a/day3.3b_advanced_plotting/02_dataviz_MLunsupervised_open.ipynb b/day3.3b_advanced_plotting/02_dataviz_MLunsupervised_open.ipynb
@@ -1,5 +1,12 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Part 2 Data exploration by unsupervised learning"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -24,13 +31,6 @@
     "from sklearn.cluster import KMeans"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Part 2 Data exploration by unsupervised learning"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,

diff --git a/day3.3b_advanced_plotting/02_dataviz_MLunsupervised_solution.ipynb b/day3.3b_advanced_plotting/02_dataviz_MLunsupervised_solution.ipynb
@@ -1,5 +1,12 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Part 2 Data exploration by unsupervised learning"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -24,13 +31,6 @@
     "from sklearn.cluster import KMeans"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Part 2 Data exploration by unsupervised learning"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 2,

diff --git a/day3.3b_advanced_plotting/03_dataviz_MLsupervised_open.ipynb b/day3.3b_advanced_plotting/03_dataviz_MLsupervised_open.ipynb
@@ -1,5 +1,12 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Part 3: Machine Learning insights by Data Viz"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -21,13 +28,6 @@
     "from sklearn.model_selection import cross_validate"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Part 3: Machine Learning insights by Data Viz"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,

diff --git a/day3.3b_advanced_plotting/03_dataviz_MLsupervised_solution.ipynb b/day3.3b_advanced_plotting/03_dataviz_MLsupervised_solution.ipynb
@@ -1,5 +1,12 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Part 3: Machine Learning insights by Data Viz"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -21,13 +28,6 @@
     "from sklearn.model_selection import cross_validate"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Part 3: Machine Learning insights by Data Viz"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 2,

diff --git a/day3.3b_advanced_plotting/readme.md b/day3.3b_advanced_plotting/readme.md
@@ -1,14 +1,14 @@
-# Plotting
+# Advanced Plotting
 
 Note that the plotting training is divided into two distinct sessions.
 
-This session (Day 3.3a - Plotting Basics):
+Parallel session (Day 3.3a - Plotting Basics):
 
 - _Focus_: This session is centered on Seaborn's figure-level functions, which provide a high-level interface for drawing statistical graphics.
 - _Content_: We exclusively use Seaborn's built-in functionalities to create comprehensive plots without the need to manually handle Matplotlib objects. This simplifies the process, making it easier for those new to programming. We will learn how to visualize tabular data using the Seaborn library. We will start by visualizing basic relational charts before moving on to distributions and, if time permits, multivariate views.
 - _Audience_: It is specifically designed for beginners who are not yet familiar with programming. The goal is to introduce the basic concepts of data visualization without delving into more complex coding structures.
 
-Parallel session (Day 3.3b - Advanced Plotting):
+This session (Day 3.3b - Advanced Plotting):
 
 - _Focus_: This session explores the use of Seaborn's grammar of graphics objects. This involves a more detailed manipulation of plot elements and integration with Matplotlib for enhanced customization.
 - _Content_: We will dive into how to structure plots using the grammar of graphics philosophy, which provides a powerful framework for understanding and creating complex visualizations. This includes modifying aesthetic attributes and integrating multiple plots.