From fcf3c11f4846d20b8a91923f638ced300ab7fce5 Mon Sep 17 00:00:00 2001
From: Vindaar <basti90@gmail.com>
Date: Mon, 6 May 2024 11:57:58 +0200
Subject: [PATCH] [recipes] update `col` reference syntax in Newton acc recipe

---
 recipes.org                     | 4 ++--
 recipes/rNewtonAcceleration.nim | 4 ++--
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/recipes.org b/recipes.org
index 2ec5ae31..a5d6bfd3 100644
--- a/recipes.org
+++ b/recipes.org
@@ -2447,7 +2447,7 @@ This gives us two =seq[float]=, but we need a =DataFrame=. So we
 combine the two:
 #+BEGIN_SRC nim :tangle recipes/rNewtonAcceleration.nim
 var df = toDf({ "r / m" : radii,
-                    "g(r) / m s¯²" : a})
+                "g(r) / m s¯²" : a})
 #+END_SRC
 which gives us a data frame with two columns. The names are, as one can
 guess, the given strings. (Note that in practice one might not want to
@@ -2481,7 +2481,7 @@ At this point we might ask "Do we recover the known 9.81 m/s^2 at the
 surface?". Let's see. There's many different ways we could go on about
 this. We'll use summarize:
 #+BEGIN_SRC nim :tangle recipes/rNewtonAcceleration.nim
-let maxG = df.summarize(f{float: "g_max" << max(c"g(r) / m s¯²")})
+let maxG = df.summarize(f{float: "g_max" << max(col("g(r) / m s¯²"))})
 #+END_SRC
 
 An alternative way would be to access the data column directly, like
diff --git a/recipes/rNewtonAcceleration.nim b/recipes/rNewtonAcceleration.nim
index 63b7b6d0..60c059e1 100644
--- a/recipes/rNewtonAcceleration.nim
+++ b/recipes/rNewtonAcceleration.nim
@@ -19,7 +19,7 @@ let radii = linspace(0.0, 35_000_000, 1000) # up to geostationary orbit
 let a = radii.mapIt(newtonAcceleration(it))
 
 var df = toDf({ "r / m" : radii,
-                    "g(r) / m s¯²" : a})
+                "g(r) / m s¯²" : a})
 
 df = df.transmute(f{"r / km" ~ c"r / m" / 1000.0}, f{"g(r) / m s¯²"})
 
@@ -28,7 +28,7 @@ ggplot(df, aes("r / km", "g(r) / m s¯²")) +
   ggtitle("Gravitational acceleration of Earth depending on radial distance") +
   ggsave("media/recipes/rNewtonAcceleration.png")
 
-let maxG = df.summarize(f{float: "g_max" << max(c"g(r) / m s¯²")})
+let maxG = df.summarize(f{float: "g_max" << max(col("g(r) / m s¯²"))})
 
 let maxG_alt = df["g(r) / m s¯²"].toTensor(float).max