From 68fe189d89a78f6d069e4ccbcc3789beb8d0e81e Mon Sep 17 00:00:00 2001
From: Alexander Hess <alexander@webartifex.biz>
Date: Fri, 16 Oct 2020 00:28:15 +0200
Subject: [PATCH] Streamline slides

---
 05_numbers/02_content.ipynb  | 6 +++++-
 05_numbers/03_appendix.ipynb | 6 +++++-
 2 files changed, 10 insertions(+), 2 deletions(-)

diff --git a/05_numbers/02_content.ipynb b/05_numbers/02_content.ipynb
index 89ff220..e430e90 100644
--- a/05_numbers/02_content.ipynb
+++ b/05_numbers/02_content.ipynb
@@ -1180,7 +1180,11 @@
   {
    "cell_type": "code",
    "execution_count": 35,
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
    "outputs": [],
    "source": [
     "from fractions import Fraction"
diff --git a/05_numbers/03_appendix.ipynb b/05_numbers/03_appendix.ipynb
index 3db9422..c470e82 100644
--- a/05_numbers/03_appendix.ipynb
+++ b/05_numbers/03_appendix.ipynb
@@ -24,7 +24,11 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "skip"
+    }
+   },
    "source": [
     "In this appendix, we look at the `Decimal` and `Fraction` types that can be used as replacements for the built-in `float` type mitigating its imprecision. The content is put in an appendix as the data science practitioner can live without knowing about it for quite some time. Eventually, when working with financial data, for example, knowing how to not use the `float` type in a bad way pays off."
    ]