diff --git a/00_python_in_a_nutshell/05_content_functions.ipynb b/00_python_in_a_nutshell/05_content_functions.ipynb
index 27c40fa..aed2f4c 100644
--- a/00_python_in_a_nutshell/05_content_functions.ipynb
+++ b/00_python_in_a_nutshell/05_content_functions.ipynb
@@ -418,21 +418,39 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "To access a function inside the [random ![](\"../static/link/to_py.png\")
](https://docs.python.org/3/library/random.html) module, for example, the [random() ](https://docs.python.org/3/library/random.html#random.random) function, we use the `.` operator, formally called the attribute access operator. The [random() ](https://docs.python.org/3/library/random.html#random.random) function simply returns a random decimal number between `0` and `1`."
+ "To access a function inside the [random ](https://docs.python.org/3/library/random.html) module, for example, the [seed() ](https://docs.python.org/3/library/random.html#random.seed) function, we use the `.` operator, formally called the attribute access operator. \n",
+ "\n",
+ "We use [random.seed() ](https://docs.python.org/3/library/random.html#random.seed) to make the random numbers *replicable* on separate runs of this notebook."
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
+ "outputs": [],
+ "source": [
+ "random.seed(42)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "The [random() ](https://docs.python.org/3/library/random.html#random.random) function simply returns a random decimal number between `0` and `1`."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 17,
+ "metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "0.7021021034327006"
+ "0.6394267984578837"
]
},
- "execution_count": 16,
+ "execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
@@ -450,16 +468,16 @@
},
{
"cell_type": "code",
- "execution_count": 17,
+ "execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "False"
+ "True"
]
},
- "execution_count": 17,
+ "execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
@@ -477,7 +495,7 @@
},
{
"cell_type": "code",
- "execution_count": 18,
+ "execution_count": 19,
"metadata": {},
"outputs": [
{
@@ -486,7 +504,7 @@
"3"
]
},
- "execution_count": 18,
+ "execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
diff --git a/01_scientific_stack/00_content_numpy.ipynb b/01_scientific_stack/00_content_numpy.ipynb
index b11a41f..ffd42c3 100644
--- a/01_scientific_stack/00_content_numpy.ipynb
+++ b/01_scientific_stack/00_content_numpy.ipynb
@@ -1274,13 +1274,29 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "Let us quickly generate some random data points and draw a scatter plot with [matplotlib ![](\"../static/link/to_plt.png\")
](https://matplotlib.org/)'s [plt.scatter() ](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.scatter.html#matplotlib.pyplot.scatter) function."
+ "First, let's set the [np.random.seed() ![](\"../static/link/to_np.png\")
](https://docs.python.org/3/library/random.html#random.seed) to make the random numbers *replicable* on separate runs of this notebook."
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {},
+ "outputs": [],
+ "source": [
+ "np.random.seed(42)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Then, let us quickly generate some random data points and draw a scatter plot with [matplotlib ](https://matplotlib.org/)'s [plt.scatter() ](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.scatter.html#matplotlib.pyplot.scatter) function."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 45,
+ "metadata": {},
"outputs": [
{
"data": {
@@ -1288,7 +1304,7 @@
""
]
},
- "execution_count": 44,
+ "execution_count": 45,
"metadata": {},
"output_type": "execute_result"
},
diff --git a/03_classification/00_content.ipynb b/03_classification/00_content.ipynb
index 731da15..8a9c7e5 100644
--- a/03_classification/00_content.ipynb
+++ b/03_classification/00_content.ipynb
@@ -761,9 +761,9 @@
{
"data": {
"text/plain": [
- "array([1, 0, 2, 2, 1, 0, 1, 1, 1, 0, 0, 2, 2, 0, 0, 2, 0, 1, 0, 0, 2, 2,\n",
- " 0, 2, 1, 0, 2, 2, 2, 1, 0, 1, 1, 2, 0, 1, 2, 1, 2, 1, 2, 1, 0, 1,\n",
- " 0])"
+ "array([2, 1, 2, 1, 2, 2, 1, 1, 0, 2, 0, 0, 2, 2, 0, 2, 1, 0, 0, 0, 1, 0,\n",
+ " 1, 2, 2, 1, 1, 1, 1, 0, 2, 2, 1, 0, 2, 0, 0, 0, 0, 1, 1, 0, 2, 2,\n",
+ " 1])"
]
},
"execution_count": 19,
@@ -772,7 +772,7 @@
}
],
"source": [
- "X_train, X_test, y_train, y_test = train_test_split(X, y, train_size=0.7, test_size=0.3, stratify=y)\n",
+ "X_train, X_test, y_train, y_test = train_test_split(X, y, train_size=0.7, test_size=0.3, random_state=42, stratify=y)\n",
"\n",
"y_test"
]
@@ -869,9 +869,9 @@
{
"data": {
"text/plain": [
- "array([1, 0, 2, 2, 1, 0, 1, 1, 1, 0, 0, 2, 1, 0, 0, 2, 0, 2, 0, 0, 2, 2,\n",
- " 0, 2, 1, 0, 2, 1, 2, 1, 0, 1, 1, 2, 0, 1, 2, 1, 2, 1, 2, 1, 0, 1,\n",
- " 0])"
+ "array([2, 1, 2, 1, 2, 2, 1, 1, 0, 2, 0, 0, 2, 2, 0, 2, 1, 0, 0, 0, 1, 0,\n",
+ " 1, 2, 2, 1, 1, 1, 1, 0, 2, 2, 1, 0, 2, 0, 0, 0, 0, 1, 1, 0, 1, 2,\n",
+ " 1])"
]
},
"execution_count": 23,
@@ -898,9 +898,9 @@
{
"data": {
"text/plain": [
- "array([1, 0, 2, 2, 1, 0, 1, 1, 1, 0, 0, 2, 2, 0, 0, 2, 0, 1, 0, 0, 2, 2,\n",
- " 0, 2, 1, 0, 2, 2, 2, 1, 0, 1, 1, 2, 0, 1, 2, 1, 2, 1, 2, 1, 0, 1,\n",
- " 0])"
+ "array([2, 1, 2, 1, 2, 2, 1, 1, 0, 2, 0, 0, 2, 2, 0, 2, 1, 0, 0, 0, 1, 0,\n",
+ " 1, 2, 2, 1, 1, 1, 1, 0, 2, 2, 1, 0, 2, 0, 0, 0, 0, 1, 1, 0, 2, 2,\n",
+ " 1])"
]
},
"execution_count": 24,
@@ -927,7 +927,7 @@
{
"data": {
"text/plain": [
- "(array([12, 17, 27]),)"
+ "(array([42]),)"
]
},
"execution_count": 25,
@@ -954,7 +954,7 @@
{
"data": {
"text/plain": [
- "np.float64(0.9333333333333333)"
+ "np.float64(0.9777777777777777)"
]
},
"execution_count": 26,
@@ -981,7 +981,7 @@
{
"data": {
"text/plain": [
- "np.float64(0.9523809523809523)"
+ "np.float64(0.9714285714285714)"
]
},
"execution_count": 27,
@@ -1066,35 +1066,35 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "1 0.9555555555555556\n",
- "2 0.9333333333333333\n",
- "3 0.9333333333333333\n",
- "4 0.9333333333333333\n",
- "5 0.9333333333333333\n",
+ "1 0.9333333333333333\n",
+ "2 0.9111111111111111\n",
+ "3 0.9555555555555556\n",
+ "4 0.9555555555555556\n",
+ "5 0.9777777777777777\n",
"6 0.9333333333333333\n",
- "7 0.9111111111111111\n",
- "8 0.9111111111111111\n",
- "9 0.9111111111111111\n",
- "10 0.9333333333333333\n",
- "11 0.9555555555555556\n",
- "12 0.9555555555555556\n",
+ "7 0.9555555555555556\n",
+ "8 0.9333333333333333\n",
+ "9 0.9555555555555556\n",
+ "10 0.9555555555555556\n",
+ "11 0.9333333333333333\n",
+ "12 0.9333333333333333\n",
"13 0.9333333333333333\n",
- "14 0.9111111111111111\n",
- "15 0.9333333333333333\n",
- "16 0.9111111111111111\n",
- "17 0.9333333333333333\n",
- "18 0.9111111111111111\n",
- "19 0.9333333333333333\n",
+ "14 0.9333333333333333\n",
+ "15 0.9555555555555556\n",
+ "16 0.9555555555555556\n",
+ "17 0.9555555555555556\n",
+ "18 0.9555555555555556\n",
+ "19 0.9555555555555556\n",
"20 0.9333333333333333\n",
- "21 0.9333333333333333\n",
+ "21 0.9555555555555556\n",
"22 0.9333333333333333\n",
- "23 0.9111111111111111\n",
- "24 0.9555555555555556\n",
- "25 0.9111111111111111\n",
- "26 0.9333333333333333\n",
- "27 0.9111111111111111\n",
- "28 0.9333333333333333\n",
- "29 0.9555555555555556\n",
+ "23 0.9555555555555556\n",
+ "24 0.9333333333333333\n",
+ "25 0.9333333333333333\n",
+ "26 0.9555555555555556\n",
+ "27 0.9333333333333333\n",
+ "28 0.9111111111111111\n",
+ "29 0.9111111111111111\n",
"30 0.9111111111111111\n"
]
}