From b443382695c84489ad18d2fcb1a66d632eda4042 Mon Sep 17 00:00:00 2001 From: Rohan Alexander Date: Tue, 25 Nov 2025 12:37:43 -0500 Subject: [PATCH 1/2] Fix typos --- 01_materials/slides/10_numpy.ipynb | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/01_materials/slides/10_numpy.ipynb b/01_materials/slides/10_numpy.ipynb index 924e4458f..7c4d07fb1 100644 --- a/01_materials/slides/10_numpy.ipynb +++ b/01_materials/slides/10_numpy.ipynb @@ -223,7 +223,7 @@ "id": "c24cee39" }, "source": [ - "We can also create arrays by specifying a range of values through `arange()` or generating random ones through functions like `random.randint()` and `random.random()`." + "We can also create arrays by specifying a range of values through `arrange()` or generating random ones through functions like `random.randint()` and `random.random()`." ] }, { @@ -239,7 +239,7 @@ }, "outputs": [], "source": [ - "# create a 1D array from 1 til 10 in steps of 2\n", + "# create a 1D array from 1 until 10 in steps of 2\n", "np.arange(1, 10, 2)" ] }, @@ -1163,7 +1163,7 @@ "source": [ "## Logic and filtering\n", "\n", - "`numpy` arrays work with boolean expressions. Each element is checked, and the result is an array of `True`/`False` values. They resulting arrays sometimes called _masks_ because they are used to mask, or filter, data." + "`numpy` arrays work with Boolean expressions. Each element is checked, and the result is an array of `True`/`False` values. They resulting arrays sometimes called _masks_ because they are used to mask, or filter, data." ] }, { @@ -1231,7 +1231,7 @@ "id": "bae12ead" }, "source": [ - "To filter use a boolean expression as a mask, pass it into square brackets after the array to mask." + "To filter use a Boolean expression as a mask, pass it into square brackets after the array to mask." ] }, { @@ -1299,7 +1299,7 @@ "id": "cb4a4676" }, "source": [ - "We can even use masks to generate new arrays with conditionals. `np.where()` takes as its arguments a boolean expression, an expression to evaluate if `True`, and an expression to evaluate elsewise. This is analagous to creating a new array based on an old one with a `for` loop and `if`/`else` statements, but much faster." + "We can even use masks to generate new arrays with conditionals. `np.where()` takes as its arguments a Boolean expression, an expression to evaluate if `True`, and an expression to evaluate elsewise. This is analogous to creating a new array based on an old one with a `for` loop and `if`/`else` statements, but much faster." ] }, { From 4e407fa27ba0bd3819a2a518f0a734db3aa02e07 Mon Sep 17 00:00:00 2001 From: Rohan Alexander Date: Wed, 26 Nov 2025 11:22:05 -0500 Subject: [PATCH 2/2] Update 10_numpy.ipynb --- 01_materials/slides/10_numpy.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/01_materials/slides/10_numpy.ipynb b/01_materials/slides/10_numpy.ipynb index 7c4d07fb1..ebd0e056a 100644 --- a/01_materials/slides/10_numpy.ipynb +++ b/01_materials/slides/10_numpy.ipynb @@ -223,7 +223,7 @@ "id": "c24cee39" }, "source": [ - "We can also create arrays by specifying a range of values through `arrange()` or generating random ones through functions like `random.randint()` and `random.random()`." + "We can also create arrays by specifying a range of values through `arange()` or generating random ones through functions like `random.randint()` and `random.random()`." ] }, {